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Isaac Newton Institute for Mathematical Sciences
List of collections in the Streaming Media Service for
Isaac Newton Institute for Mathematical Sciences
Thu, 09 Jun 2022 19:59:36 +0100
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Isaac Newton Institute for Mathematical Sciences
http://sms.cam.ac.uk/institution/INIMS/collections
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http://sms.cam.ac.uk/institution/INIMS/collections

Complex analysis: techniques, applications and computations
ucs_sms_3064157
http://sms.cam.ac.uk/collection/3064157
Complex analysis is unusual in that it pervades so many apparently disparate areas of mathematics, including analysis, algebra, geometry, algebraic geometry, differential geometry, numerical analysis, spectral theory, integrable systems and the theory of partial differential equations. In recent years, significant advances have been made in some fundamental aspects of the subject, among them the socalled unified transform method of Fokas with its relation to the spectral theory and integrable systems, the development and refinement of numerical methods for RiemannHilbert problems with connections to orthogonal polynomials, random matrices and special function theory, and conformal mapping with the discovery of a new constructive framework for deriving mappings for domains of arbitrary connectivity. Recent years have also witnessed a surge of activity in related freeboundary problems, largely driven by applications in mathematical and statistical physics, biology and medicine: examples include Laplacian growth, diffusionlimited aggregation, stochastic Loewner evolution, cancerous tumour modelling. Complex variables in numerical analysis is also a topic of burgeoning interest and activity. Complexdomain methods play an important role in the studies of finitetime singularity formation in various PDE problems. These investigations represent an area of increasing overlap between scientific computing and PDE analysis. Many of the newly developed tools of complex analysis also pose computational challenges which need to be addressed before these approaches can be used in realworld applications.
This programme is aimed at enhancing these new basic techniques, while assessing their scope and usefulness, and at bringing together key researchers working at the frontiers of these new developments to help steer future endeavours. It takes an integrated view of complex variable theory, computations and applications, and should be accessible to a wide range of attendees from a diverse spectrum of backgrounds. Its goal is to bring together researchers from the mathematics, physics and engineering communities, whose research shares a common theme of using complex analysis to attack realworld problems. In addition to exploring new applications of complex variable theory, the programme will focus on drawing out the unexpected connections between different branches of complex analysis that have been emerging. A key objective of the programme is to engage stakeholders from diverse application areas to learn about, discuss and develop these new methods and applications of complex analysis.
The programme's activities will be built around three main interaction vehicles: (1) workshops; (2) masterclasses; (3) ongoing themes and collaborations, linked to various events during each week of the programme. The three workshops are "The complex analysis toolbox: new techniques and perspectives", "Complex analysis in mathematical physics and applications", and "Computational complex analysis."
3064157

Geometry, compatibility and structure preservation in computational differential equations
ucs_sms_3028099
http://sms.cam.ac.uk/collection/3028099
Computations of differential equations are a fundamental activity in applied mathematics. While historically the main quest was to derive allpurpose algorithms such as finite difference, finite volume and finite element methods for space discretization, Runge–Kutta and linear multistep methods for time integration, in the last 25 years the focus has shifted to special classes of differential equations and purposebuilt algorithms that are tailored to preserve special features of each class. This has given rise to the new fields of geometric numerical integration and of structure preserving discretization. In addition to being quantitatively accurate, these novel methods have the advantage of also being qualitatively accurate as they inherit the key structural properties of their continuum counterparts. This has meant a largescale introduction of geometric and topological thinking into modern numerical mathematics.
During this scientific programme at the Isaac Newton Institute for Mathematical Sciences, we will address fundamental questions in the field of structure preserving discretizations of differential equations on manifolds in space and time. We will bring together two communities that have been pursuing their science along parallel tracks to endeavour breakthroughs in some major scientific applications, which call for advanced numerical simulation techniques. This will lead to the development of a new generation of spacetime discretizations for evolutionary equations.
During the programme we intend to organise three workshops and two focused study periods lasting two weeks on selected application areas.
The core themes of the programme are:
Compatible discretizations.
Geometric numerical integration.
Structure preservation and numerical relativity.
Applications to computations in quantum mechanics.
3028099

New trends and challenges in the mathematics of optimal design
ucs_sms_3000477
http://sms.cam.ac.uk/collection/3000477
The optimal design of structures and materials has recently undergone a burst of activity due to simultaneous progress in methods for the manufacture of new materials and their design, such as the development of additive manufacturing and of
mathematical methods for topology optimization.
The workshop will present the most recent results and challenges in this area and provide an exchange forum for mathematicians, scientists and engineers interested in various applications, having in common the need for optimizing designs, in particular their material properties, shapes and topologies.
3000477

Privacy Enhancing Technologies in Practice  Series of Short Workshops
ucs_sms_3341000
http://sms.cam.ac.uk/collection/3341000
Background
Companies have been repeatedly told that data is one of their most valuable commodities, but realising the full value of that data may require remixing, comparison, or computation against data held by others. Unfortunately, sharing data is one of the hardest things for companies to do, because of the perceived commercial and legal risks. Even within a single organisation, sharing data can be considered to create large security or privacy risks.
The last few years have seen the emergence of technologies which allow for the secure collection, sharing, processing, and storage of data without the downsides of reducing privacy of users, or compromising corporate security. These Privacy Enhancing Technologies (PETs) have the capacity to make data sharing both safe and effective. These technologies form the basis of various new ways of doing business, with many being highlighted in recent Gartner reports as opening up new ways of exploiting data.
Now is the time to look further at case studies, models and demonstrators that show such techniques can perform what at first sight seems impossible: to process data without seeing it. The technology is so counterintuitive, and opens up such new ways of working, that we have identified a need to facilitate a greater understanding of these technologies amongst endusers, without them necessarily needing to know exactly “how” it works.
Due to Covid19 this workshop will now run virtually in a series of five weekly one and a half hour events, starting on 19th November 2020. We still plan to run a physical one day event in 2021, possibly May. The November/December and January events will feature conversations with experts who are deploying this technology, as well as endusers who are interested in applying them.
Aims and Objectives
Developed with academic partners and in collaboration with the Digital Catapult, this events series recognises the need to help business and industry find effective ways to utilise these new privacy enhancing technologies. Therefore, these events will be of interest to anyone in business and industry who has a need to share and/or process data securely, as well as those focused on corporate CyberSecurity.
Events 13 will feature talks from experts from companies developing these technologies. The talks will highlight why PET technologies can be trusted and how they enable the value in data to be unlocked; without needing to compromise on the privacy or security of the said data. They will also highlight how users can go about exploring and running tests on them, across a range of potential application domains, from inter to intra company security.
3341000

Progress on novel mathematics and statistics for Landscape Decisions, including priorities for further research
ucs_sms_3036087
http://sms.cam.ac.uk/collection/3036087
Land is a key limiting resource in many regions of the world, including the UK. Society depends on land resources for many purposes, including urban settlement, employment and transportation, as well as a host of benefits we get from nature (ecosystem services)  food, timber, energy, recreation, and aesthetic benefits. We require these land resources to be resilient to environmental change, and to meet increasing demands for not only housing, but also renewable energy, recreation and climate change mitigation. Landuse therefore connects many of the UN Sustainable Development Goals. In the UK, EU exit will require the introduction of many new policies connected to landuse (e.g. replacing the Common Agricultural Policy, the EU Biodiversity Strategy, etc) – implying an urgent need to develop better landscape decision tools. The onemonth INI programme explores the mathematical and statistical challenges associated with making use of the latest observations to understand and project landuse changes. Questions to be addressed will include: what is the minimal useful representation of the landscape system? How do we robustly model the coupled humanenvironment system without assuming that people act as perfectly rational economic agents? Where are the nonlinearities and sensitivities of the system, and how could these be used to produce transformative changes in landuse? How do we reconcile scale disconnects between different elements of humanenvironment systems?
This threeday workshop will close the INI research programme, via a series of research roadmaps that synthesize new research frontiers and synergies identified during the INI programme. The last day of the workshop will be specifically stakeholderfocused to discuss the relevance of the new insights and research roadmaps to particular policyrelevant areas of research in this field.
Participants in the workshop will include a highly interdisciplinary mix of both academic and nonacademic researchers and policy makers working on land related research and policy questions. These will include (but not be limited to) participants interested in agriculture, forestry, water resources and biodiversity, as well as mathematicians, statisticians and computer scientists expert in system modelling, uncertainty quantification and decision making who are also interested in these wide ranging applied questions.
3036087

 Latest Videos 
ucs_sms_1077495
http://sms.cam.ac.uk/collection/1077495
Latest videos from the Isaac Newton Institute.
1077495

100% Renewables  Future Challenges in Energy Systems
ucs_sms_2907429
http://sms.cam.ac.uk/collection/2907429
100% renewable energy by 2050? This is an ambitious vision that will need significant change to our energy systems. It will require the development of an integrated power grid and continuous and steady transformation of the UK power system can only happen if fundamental interdisciplinary research and smart technology challenges are met.
The rapid advance of renewable generation, along with the move away from oil and gas to increased electrification is predicted to push electricity demands in the future to at least double current levels. Additionally, there are significant challenges for getting these energy sources to the grid – both engineering and economic and specifically for storage and demand management. Wind and solar production is both variable and uncertain, and grid system operators need to make sure they have enough reserves to balance them.
Consequently, there are significant research challenges associated with the move towards more renewables in our energy systems. The mathematical sciences can make significant contributions  for instance, in the areas of problems of control and optimisation where there is a need for better modelling, prediction and simulation.
This knowledge exchange workshop was part of the four months Research Programme at the Isaac Newton Institute (INI) on The Mathematics of Energy Systems. Participants on this programme are interdisciplinary and key aims are to develop methodology which is urgent for the next several years and to sow the seeds of a lasting mathematical research agenda.
Aims and Objectives
The energy systems area is highly multidisciplinary and requires the endeavours of mathematicians, statisticians, computational modellers, engineers and economists to address the challenges that exist. One of the most significant of these, is the management of energy flows in order to avoid billions of pounds of expenditure in network reinforcement. In this context, many of the present and emerging renewable resources pose both a challenge and an opportunity. These include, for example, generators, storage, interconnectors and demandside management (including electric vehicles), along with other opportunities for automation coming from new power electronics technology and wider deployment of relays.
The programme for the day included academic research talks, as well as enduser challenge type presentations from key players across the energy sector supply chain. There was be a particular focus on:
Control and optimisation
Prediction and simulation
Market design
Risk and investment
Modelling and planning for uncertainty
This event was of interest to academics involved in energy systems research, as well as stakeholders from across the energy sector supply chain – including transmission, network distribution, generation, retail and regulation.
2907429

20th Anniversary of the Isaac Newton Institute
ucs_sms_1183344
http://sms.cam.ac.uk/collection/1183344
During 2012 the Newton Institute is planning a number of events to celebrate the 20th anniversary. Also includes events organised for the centenary celebration of the life and work of Alan Turing.
Read more @ http://www.newton.ac.uk/20/
Alan Turing Year: http://www.mathcomp.leeds.ac.uk/turing2012/
1183344

25th Anniversary of the Isaac Newton Institute
ucs_sms_2525198
http://sms.cam.ac.uk/collection/2525198
2525198

4Dimensionalism in Large Scale Data Sharing and Integration
ucs_sms_3518756
http://sms.cam.ac.uk/collection/3518756
Thursday 22nd April 2021
Background
In foundational ontology, 4dimensionalism is shorthand for a mathematicalphilosophical basis for a rigorous global identity criterion based upon composition. It acquired this name as a vital part of the approach is treating individuals as extended in time as well as space, with two objects composed of the same spatiotemporal parts being considered identical. The opportunity this brings to data sharing and integration on a large scale (both within and across organizations) is that it introduces an increased level of rigour into the way we model the world. This in turn enables a step change in the consistency that it is possible to achieve in data which is critical to enable effective data sharing and integration.
Historically, some have claimed that 4dimensionalism does not match with how we talk about the world in everyday terms, and this has led to claims it is counterintuitive which has sometimes been a barrier to adoption.
However, recent years have seen some important advances in the 4dimensional ecosystem, in how it fits into a wider information management landscape. This enables its exploitation, in improvements to the ways of talking about 4dimensionalism to make it more approachable, to the formalisation of the foundations for 4dimensionalism, to the grounding of a 4dimensional ontology using a constructive approach. These are being brought together in the National Digital Twin Programme and the Information Management Framework at its heart.
So now is the time to take a fresh look at the 4dimensional ecosystem  to see how it works and the potential it has to help deliver large scale data sharing and integration.
Aims and Objectives
This one day workshop presents an opportunity to get uptodate on the state of the art with 4dimensionalism and its application. It is a joint collaboration between the Newton Gateway to Mathematics, GCHQ, UCL STEaPP, Southampton University, Warwick University and Brunel University.
Current and potential applications of 4D/Digital Twin data modelling are wide ranging. In recent decades it has been used in both Oil and Gas and Defence/Security environments. Potential uses include the built environment and various engineering applications including aircraft engines, wind turbines, buildings and large structures, control systems.
The Grenfell tragedy and subsequent enquiry has uncovered the failure to use information effectively by a complex ecosystem of organisations. At the same time the challenges posed by responding to Covid has resulted in the Royal Society DELVE group to state clearly that there is a lot to learn from the current shortcomings in the use of data. The integrated use of data to inform key decisions offers a lot of potential. However, integration of data turns out to be far harder than is generally assumed. This event will cover what it takes to address data integration and illustrate its grounding in both pure mathematics and philosophy.
A programme of talks will outline recent advances in the 4dimensional ecosystem, and how they are being taken up and applied within the National Digital Twin programme.
This event should be of interest to Data Architects from multiple settings including, industry, business and the public sector.
4Dimensionalism in large scale data sharing and integration will also have broad appeal to the mathematical sciences as it draws upon a surprising number of branches of pure mathematics disciplines in the construction of a formal model basis for data integration. It should be applicable to a wide range of applied mathematics fields, where the use of models and data to increasingly complex areas is vital, and supports improved and trusted humancentred decision making. Presentations will touch on set theory, topology, geometry, combinatorics and formal logic and explain why the need for consistency in data depends on harnessing them.
A Provisional Programme is available here
3518756

5th Edwards Symposium  Future Directions in Soft Matter
ucs_sms_3659499
http://sms.cam.ac.uk/collection/3659499
3659499

About the Isaac Newton Institute
ucs_sms_1150342
http://sms.cam.ac.uk/collection/1150342
We are a national and international visitor research centre and run research programmes on selected themes in mathematical sciences, with applications in a wide range of science and technology. www.newton.ac.uk
1150342

About the Newton Gateway to Mathematics
ucs_sms_2907735
http://sms.cam.ac.uk/collection/2907735
The Newton Gateway to Mathematics acts as a knowledge intermediary for the mathematical sciences. It is the impact initiative of the Isaac Newton Institute for Mathematical Sciences (INI). Supported by INI and the University of Cambridge, the Newton Gateway to Mathematics reaches out to and engages with the users of mathematics – in industry, business, public sector and other scientific disciplines. It helps to bridge the gap between those engaged in frontier mathematical research and those working in more applied areas, by stimulating the interchange of knowledge and ideas.
The Newton Gateway works as a delivery partner to facilitate the exchange, translation and dissemination of knowledge. Using effective communications and proven methodologies, it develops and runs activities such as workshops and meetings, bringing people and organisations together in order to share knowledge and stimulate further research and collaboration. With extensive access to multiple communities across the UK and globally, it can respond in an agile and flexible manner.
Mission Statement:
The Newton Gateway to Mathematics acts as a vehicle for knowledge exchange between the mathematical sciences and potential users of mathematics, including industry, government, business and other academic disciplines, both in the UK and internationally. It does this by facilitating interactions and activities such as programmes of work, research and training events, as well as bespoke projects. The Newton Gateway to Mathematics aims to widen access to mathematics generally, to shorten pathways to impacts for academic research, and to support education and training in areas where mathematical skills are needed.
Background
The Newton Gateway to Mathematics was established in March 2013, as the Turing Gateway to Mathematics (TGM), as the impact initiative of INI. It was named after Alan Turing because of his exceptionally wide influence across a broad range of areas.
The increasing scale of activity was such that the Newton Gateway to Mathematics needed to reinforce its identify as both an integral part of INI and as a national facility for knowledge exchange for mathematical sciences in the UK. The Review into Knowledge Exchange in the Mathematical Sciences reinforced the need to have impact as a central role within the mathematical sciences. There was the additional need to avoid confusion with other organisations and so it was timely to rebrand to the Newton Gateway to Mathematics in January 2019.
Launch of the Newton Gateway to Mathematics
A launch event took place on 21 January 2019, with speakers talking about their experience of working with the Gateway, explaining its history, the vision and current priorities.
Ewan Kirk, Chair of the Management Committee introduced the event. David Abrahams, who is Director of the Isaac Newton Institute, then spoke about the development of INI, the role of industrial mathematics and statistics and the creation of the Turing Gateway to Mathematics and the subsequent move to become the Newton Gateway to Mathematics.
Jane Leeks, Manager of the Gateway, provided examples of the Gateway’s engagement activity over the 6 years since its inception. Jane also spoke about some of the partners that the Gateway has collaborated with and outlined the future direction.
Peter Landrock, who is Chair of the Newton Gateway to Mathematics Advisory Board, spoke about his positive experience of engaging with the Gateway and he was followed by Richard Pinch who had previously been a member of the Advisory Board and who is VicePresident, Profession & Industry of the Institute of Mathematics and its Applications. Richard spoke about the value of knowledge exchange and gave examples working with the Gateway that had helped to facilitate some particular streams of work.
Mike Cates, Lucasian Professor of Mathematics at the University of Cambridge has worked with the Gateway to develop and deliver the Edwards Symposia. Mike spoke about targeting academia and industry engagement in Soft Matter Research and the key role that the Gateway played in developing the events and facilitating their delivery.
Philip Bond, Lead Author of the Bond Review on Knowledge Exchange in the Mathematical Sciences, spoke about why impact matters – its role in productivity and innovation. He spoke about “The Era of Mathematics” and why mathematical impact is vital to society.
Priscilla Canizares from Schlumberger was the final speaker – she reiterated that mathematics is inter disciplinary and highlighted its contribution to the UK economy.
2907735

Achieving Impact in Healthcare: From Mathematics to Clinical Support Systems and Devices
ucs_sms_2959049
http://sms.cam.ac.uk/collection/2959049
Background
With a rapidly ageing global population and challenges such as the growth of antibiotic resistance, there has been significant growth in the global incidence of chronic and infectious health conditions. Furthermore, the number of people living with two or more chronic health conditions is forecast to treble by 2030. In the light of this, EPSRC introduced a set of Grand Challenges for Healthcare Technologies and issued a strategic call in 2015 to set up a number of Centres for Mathematics in Healthcare within the UK, where the remit of the Centres is to develop and apply modern mathematical ideas to problems of potential impact to healthcare.
As a result of this call, five EPSRC Mathematics for Healthcare Centres, based at Cambridge, Exeter Glasgow, Imperial and Liverpool have been funded to a total of £10m. These Centres were established in 2016 and aim to establish an ongoing programme of research and impact activities in this area, beyond the lifetime of the initial funding period. In addition to their complementary research programmes, the Centres are nurturing a new generation of researchers able to bring advanced mathematical techniques to new areas of healthcare and medicine.
Aims and Objectives
This joint workshop of the five Centres focused on translating mathematical research into technological advances, as well as outreach and linkage with clinicians and enduser companies. It presented the opportunity to hear in detail about the project collaborations, research and outcomes from each Centre. The programme aimed not only to nurture the mathematical research associated with the Centres, but to engage endusers to ensure that best practice is spread as widely as possible.
The Programme featured talks from all five Centres. The themes of ‘Clinical Support Systems’, ‘Population Medicine ’ and ‘Mathematical Challenges” were explored. Talks covered a range of topics, including crossmethodology challenges for specific disease groups, crossdisease challenges for specific methodologies and machine learning customised for medical imaging.
This workshop also aimed to coordinate and consolidate the research agenda within the Maths for Healthcare space for the subsequent five years and scope out a proposal for a six month Research Programme on the Mathematics of Healthcare to be held at the Isaac Newton Institute.
The event was of interest to researchers, clinicians and healthcare technologists from biomedical imaging, mathematics, engineering, computer science, biology and medicine and presents the opportunity for knowledge exchange and networking between senior scientists with relevant individuals from industry and government.
2959049

Advanced Monte Carlo Methods for Complex Inference Problems
ucs_sms_1704530
http://sms.cam.ac.uk/collection/1704530
In recent years there has been an explosion of complex datasets in areas as diverse as Bioinformatics, Ecology, Epidemiology, Finance and Population genetics. In a wide variety of these applications, the stochastic models devised to realistically represent the data generating processes are very high dimensional and the only computationally feasible and accurate way to perform statistical inference is with Monte Carlo.
The focus of this programme is on recent innovations in the field of Monte Carlo methods for inference in complex and intractable statistical problems. This programme will bring together researchers from a broad base, for the first time since 2009, to promote discussion and development of this important and rapidly advancing crossdisciplinary area. It will leverage on the two very successful past programmes which were the INI Programme on Stochastic Computation in the Biological Sciences (23 October  15 December 2006) and the SAMSI programme on Sequential Monte Carlo (SMC) Methods (September 2008 to August 2009), by taking up the following research threads that have genuinely enthused the wider community of research and applied statisticians over the past couple of years: Approximate Bayesian Computation; SMC and Markov Chain Monte Carlo and their integration; and recent theoretical advancements underpinning these areas.
This programme will also hold a workshop in the first week covering the two major themes of this proposal to launch the 4week programme. The workshop will serve as a catalyst for the remaining 3 weeks of intensive research and aims to cover the following specific areas:
ABC: new applications, methodology and theory
SMC/MCMC for high dimensional computation
The workshop will also have an introductory element to it, aimed at acquainting postgraduate students and postdoctoral researchers with the subject area. Details to follow soon.
1704530

Advances in Numerical Modelling
ucs_sms_3115246
http://sms.cam.ac.uk/collection/3115246
Background
Numerical modelling is used to good effect in a number of applications and advances in geometric and structure preserving methods will progress this field further. These methods are a special class of numerical algorithms used to compute solutions to differential equations that preserve the underlying geometry and structure of the system. The key advantage of these methods is that they are not only computationally fast, but they also improve the accuracy of the computation since they are both quantitatively and qualitatively precise.
Computations of differential equations are fundamental in the mathematical models of many realworld systems, many of which are highly complex and require advanced numerical methods to solve them. This is particularly the case in areas where it is vital that model simulations are both quick and precise. In recent years there has been a shift to special classes of differential equations and purposebuilt algorithms that are tailored to preserve special features of each class. This has given rise to the new fields of geometric numerical integration and of structure preserving discretization. Due to the increased speed and accuracy of geometric and structure preserving methods over other numerical algorithms to solve differential equations they have become an important tool in weather forecasting, medical imaging, defence and space and robotics.
This knowledge exchange day is part of a six month Research Programme at the Isaac Newton Institute on Geometry, compatibility and structure preservation in computational differential equations. This research programme brings together mathematicians from different communities to develop a new generation of spacetime discretisation methods for differential equations needed for major scientific applications which call for advanced numerical techniques.
Aims and Objectives
This workshop will showcase recent applications of geometric and structure preserving methods to models of realworld systems, as well as highlight where advances in these types of numerical methods are most needed.
The programme for the day represents the breadth of application areas where geometric and structure preserving numerical methods are used and will include talks from both academic research and endused perspectives from a number of application areas. The talks will highlight recent advances in these types of numerical methods which have the potential to significantly improve simulations in areas where numerical accuracy and computational speed are vital, such as weather forecasting and medical imaging.
The three sessions will focus on the following application areas where it has been identified that geometric and structure preserving methods have potential for significant impact:
Weather forecasting
Medical imaging
Robotics
Defence and space
This event will bring together mathematicians and scientists working in various areas at the forefront of advances in geometric and structure preserving numerical methods, with end users from industry to further investigate opportunities for the use of these types of methods to improve the numerical solution of realworld problems. Academic talks will highlight state of the art research and techniques in this area and where they could be applied to improve the numerical solution of industrial driven models. Enduser talks will reflect challenges where such techniques could be used to improve the speed and accuracy of simulations.
3115246

Algebraic Lie Theory
ucs_sms_533438
http://sms.cam.ac.uk/collection/533438
Lie theory has profound connections to many areas of pure and applied mathematics and mathematical physics. In the 1950s, the original "analytic" theory was extended so that it also makes sense over arbitrary algebraically closed fields, in particular, fields of positive characteristic. Understanding fundamental objects such as Lie algebras, quantum groups, reductive groups over finite or padic fields and Hecke algebras of various kinds, as well as their representation theory, are the central themes of "Algebraic Lie Theory".
A driving force has always been the abundance of challenging, yet very basic problems, like finding explicit character formulae for representations. The introduction of geometric methods (in the 1970s) has revolutionized the field. It led to a flow of new ideas between several disciplines, and produced spectacular advances. The ideas of "geometrization" and "categorification" now play a fundamental role in the development of the subject. New structures continue to arise from connections with other areas of mathematics and mathematical physics, like the emerging theory of Walgebras.
Read more at: www.newton.ac.uk/programmes/ALT/
533438

Algorithms and Software for Quantum Computers
ucs_sms_2701531
http://sms.cam.ac.uk/collection/2701531
Next generation (Quantum) computers promise to speed up some mathematical processes by orders of magnitude, but new algorithms and software will need to be developed to exploit this power. Although generalpurpose quantum computers are some years away, work should start on the software now. As quantum machines operate in a completely different way to conventional computers, code development requires entirely new thinking.
In 2015 the UK government launched the 5year UK National Quantum Technology Programme, now worth ~£400m, the largest public investment ever made in a disruptive technology. The aim is to exploit the UK’s worldclass quantum science to create a profitable and sustainable business in the UK. Part of this is funding UK development of quantum processors, but their unique characteristics will need new ways of thinking to create the code necessary for practical application to industrial problems. It has been suggested that quantum computer software will create more wealth than the hardware, important though that is.
Aims
This workshop was a collaboration between the Knowledge Transfer Network (KTN) and the Turing Gateway to Mathematics. It aimed to initiate development of quantum computer algorithms and software by bringing together realworld problem owners (for example in drug discovery, telecoms, manufacturing and others), with mathematicians, algorithm experts, and academic quantum computer hardware experts to explain what code developers need to know to create software, without getting bogged down in the underlying physics. We aimed to do this in sufficient detail to spark immediate cooperation and collaboration.
Participants included academic researchers and individuals from business and industry. Various classes of problems were discussed and a number of relevant sectors were represented  including medicine discovery, logistics, earth observation and finance.
We also updated delegates on the anticipated capabilities of classical machines 5 or 10 years from now, when practical quantum processing may be available.
A programme of talks and discussion highlighted and explored what code developers need to know to create software capable of delivering industrial needs and ideally gain estimates of speedups which could be expected. Extra consideration was given to where classical computing architectures will be in the same timeframes we expect Quantum Computing to begin to deliver.
2701531

Analysis on Graphs and its Applications
ucs_sms_39
http://sms.cam.ac.uk/collection/39
Analysis on graphs and other discrete structures has been developing for quite some time, in particular due to applications to number theory, algebra, probability theory, spectral geometry, as well as to its usefulness in many practical problems. This area, however, has experienced recently a significant boost in terms of new important applications arising, new methods being developed, and new models introduced not studied before. This has happened due to numerous new applications arising in different areas of mathematics, sciences, and engineering. They swipe throughout a wide scientific landscape, which besides the fields already mentioned includes nanotechnology, microelectronics, quantum chemistry, superconductivity, optics, etc.
Read more at: http://www.newton.ac.uk/programmes/AGA/
39

Annual Meeting of Correspondents
ucs_sms_1723392
http://sms.cam.ac.uk/collection/1723392
1723392

Applicable resurgent asymptotics: towards a universal theory
ucs_sms_3461895
http://sms.cam.ac.uk/collection/3461895
Programme Theme
Asymptotic analysis and perturbation methods can provide approximate solutions and analytical properties to a broad range of problems where an exact solution cannot be found. They are therefore some of the most critically important tools in mathematics and theoretical physics. Nevertheless, the existing approaches to study asymptotic problems are often context specific, varying in rigour or practicality. A key challenge, which this programme will seek to address, is to unify these approaches in asymptotics into techniques of enhanced efficacy and broader applicability.
The role of previously neglected exponentially small terms in asymptotics has been formalised, understood and subsequently exploited to deliver a radical change to the centuryold, but ambiguous, approach of Poincaré asymptotic analysis. Significant mathematical breakthroughs have been achieved in a number of areas including rigorous bounds, PDEs, discrete systems and eigenvalue problems. These have wideranging applications to, amongst others, fluid dynamics, aeroacoustics, pattern formation, dynamical systems, optics and biomathematics.
Recently, remarkable progress has also been made in theoretical physics in the applications of the comprehensive theory of resurgent asymptotic analysis. This approach has revealed new and deeper insights into the nonperturbative structure and dynamics of quantum field theories, string theory, random matrix and knot theories, as well as computationally efficient techniques for path integral evaluation. Simultaneously this has opened up developments in Riemann Hilbert problems, integrable nonlinear systems and orthogonal polynomials with the potential for applications to wide classes of nonlinear multidimensional problems.
Although overlapping, these advances have developed largely in parallel. However, there is increasing realisation from those working in these distinct areas that there is significant potential for mathematical technology transfer. One ambitious goal of this programme is to bring these communities together to develop a unified set of comprehensive, yet practical, advanced asymptotic approaches, widely applicable not only in mathematics and physics, but also in rapidly emerging areas such as in engineering, data science and systems biology.
The work on unified approaches to asymptotics envisaged during this programme is broad in scope and currently includes transseries and their practical implementation; parametric resurgence and higher order Stokes phenomena for multidimensional systems; analysis of Stokes coefficients; realistic sharp error bounds for highly accurate numerics (e.g., BorelPadé); complex singularity dynamics in finite and late time phenomena; RiemannHilbert methods; exact WKB analysis; practical implementation of Lefschetz thimbles in highdimensional integrals; nonlinear uniform asymptotics; Painlevé analysis and PicardLefschetz theory for novel computational methods.
The applications of these approaches under study during the programme include resurgence and nonperturbative physics in gauge theory, matrix models, string theory, AdS/CFT, supersymmetry, and localizable QFTs; highly correlated systems and relativistic hydrodynamics; metastability, free boundary and late time behaviour of nonlinear PDEs; homogenisation and other multiple scales problems; discrete to continuum limits in biological systems; interplay between integrability and asymptotics.
The programme will bring together applied mathematicians, mathematical analysts, theoretical physicists and subject specialists working on asymptotic analysis to enable significant technology transfer and to inaugurate the next generation of interdisciplinary researchers within these fields. Given the breadth of activity, and the diverse disciplines involved, the stage is set for further major advances and for unforeseen new directions.
3461895

Approximation, sampling and compression in data science
ucs_sms_2919113
http://sms.cam.ac.uk/collection/2919113
Programme Theme
Approximation theory is the study of simulating potentially extremely complicated functions, called target functions, with simpler, more easily computable functions called approximants. The purpose of the simulation could be to approximate values of the target function with respect to a given norm, to estimate the integral of the target function, or to compute its minimum value. Approximation theory's relationship with computer science and engineering encourages solutions that are efficient with regards to computation time and space. In addition, approximation theory problems may also deal with reallife restrictions on data, which can be incomplete, expensive, or noisy. As a result, approximation theory often overlaps with sampling and compression problems.
The main aim of this programme is to understand and solve challenging problems in the highdimensional context, but this aim is dual. On one hand, we would like to use the highdimensional context to understand classical approximation problems. For example, recent developments have revealed promising new directions towards a breakthrough in a set of classical unsolved problems related to sampling in hyperbolic cross approximations. On the other hand, we want to understand why classical multivariate approximation methods fail in the modern highdimensional context and to find methods that will be better and more efficient for modern approximation in very high dimensions. This direction will focus on two conceptual steps: First, replacement of classical smoothness assumptions by structural assumptions, such as those of sparsity used by compressed sensing. Second, the use of a nonlinear method, for instance a greedy algorithm, to find an appropriate sparse approximant.
In order to achieve the goal the programme will bring together researchers from different fields to work in groups on modern problems of highdimensional approximation and related topics. It will foster exchange between different groups of researchers and practitioners.
2919113

Approximation, sampling and compression in data science
ucs_sms_2989623
http://sms.cam.ac.uk/collection/2989623
Programme Theme
Approximation theory is the study of simulating potentially extremely complicated functions, called target functions, with simpler, more easily computable functions called approximants. The purpose of the simulation could be to approximate values of the target function with respect to a given norm, to estimate the integral of the target function, or to compute its minimum value. Approximation theory's relationship with computer science and engineering encourages solutions that are efficient with regards to computation time and space. In addition, approximation theory problems may also deal with reallife restrictions on data, which can be incomplete, expensive, or noisy. As a result, approximation theory often overlaps with sampling and compression problems.
The main aim of this programme is to understand and solve challenging problems in the highdimensional context, but this aim is dual. On one hand, we would like to use the highdimensional context to understand classical approximation problems. For example, recent developments have revealed promising new directions towards a breakthrough in a set of classical unsolved problems related to sampling in hyperbolic cross approximations. On the other hand, we want to understand why classical multivariate approximation methods fail in the modern highdimensional context and to find methods that will be better and more efficient for modern approximation in very high dimensions. This direction will focus on two conceptual steps: First, replacement of classical smoothness assumptions by structural assumptions, such as those of sparsity used by compressed sensing. Second, the use of a nonlinear method, for instance a greedy algorithm, to find an appropriate sparse approximant.
In order to achieve the goal the programme will bring together researchers from different fields to work in groups on modern problems of highdimensional approximation and related topics. It will foster exchange between different groups of researchers and practitioners.
2989623

Approximation, sampling, and compression in high dimensional problems
ucs_sms_3007735
http://sms.cam.ac.uk/collection/3007735
In a number of problems, both in theory and applications, one faces a situation when the ambient dimension is extremely high. Such problems often include approximating, sampling, or compressing functions on highdimensional domains. Classical methods fail to be effective in this case due to the effect known as `curse of dimensionality'; hence new tools and algorithms need to be devised. Compressed sensing, which has gained great popularity in this century, is one example of a circle of ideas which make highdimensional problems feasible. Methods which allow one to overcome the curse of dimensionality come from a mixture of mathematical fields: approximation, probability, functional and harmonic analysis, linear algebra, combinatorics, geometry, etc. In addition to pure mathematical interest, this field has great importance in numerous applications, in particular in data science and signal processing. Despite decades of research, many important questions in this area are still open. This workshop will bring together researchers in pure and applied mathematics, who attack highdimensional problems.
3007735

Artificial Intelligence Developments in Healthcare Imaging
ucs_sms_3085631
http://sms.cam.ac.uk/collection/3085631
Background
The EPSRC Centre for Mathematical Imaging in Healthcare (CMIH) will hold an engagement event in October 2019. This will aim to showcase the research that is being carried out at the Centre and will present an opportunity to hear in detail about some of the current project collaborations, other industry challenges and explore new potential collaborations.
This event follows previous industry and academic engagement events delivered over the past three years.
CMIH is based at the University of Cambridge and aims to achieve synergies between applied mathematics and statistics through the focus on the acquisition and analysis of clinical imaging data, particularly arising from neurological, cardiovascular and oncology imaging. It is a true collaboration between mathematics, engineering, physics and biomedical scientists and clinicians.
Aims and Objectives
CMIH enables mathematicians and statisticians to work closely with relevant stakeholders involved in the areas of clinical imaging from healthcare planning, clinical provision, policy making and industrial research across the UK. A key aim of this partnership is the delivery of high quality, multidisciplinary research that will help overcome some of the big challenges facing the NHS.
This user engagement event will focus on artificial intelligence and will provide an update on some of the research projects and collaborations taking place in the CMIH. It will feature presentations from CMIH researchers and Industry Partners, as well as other academics and end users in the public sector and industry. A number of industry challenges and collaborations will be highlighted in an elevator pitch session.
The event will be of interest to researchers working in the field of acquisition and analysis of clinical imaging and also to healthcare planners, clinicians, policy makers and industry partners to discuss the research projects and challenges arising from the area. It presents the opportunity for knowledge exchange and networking between senior scientists from areas such as mathematics, statistics, engineering, physics and biomedicine and relevant individuals from industry and government.
3085631

Behaviour and Policy During Pandemics: Models and Methods
ucs_sms_3817245
http://sms.cam.ac.uk/collection/3817245
Background
Over the course of the COVID19 pandemic, modelling has taken centre stage both in forecasting, policy formulation and in informing the public, featuring prominently in the advice given to government in the UK and beyond. The pandemic has had profound influence on social and economic activity, meaning that different policy interventions such as lockdowns and furlough schemes cannot be seen as merely public health policies or as economic policies in isolation. It is therefore important to better understand how policies interact through intertwined economic and disease dynamics and how different policies must be designed to work together.
A successful integration of behaviour into epidemiological models would allow both modellers and policy makers to not only assess how different interventions will likely play out in practice, but also guide the policy making process itself, indicating which policies are likely to lead to greater health and socioeconomic wellbeing. Advancements require collective engagement across disciplines, including behavioural scientists, epidemiologists, public health modellers, economic epidemiologists and those involved in public health policy.
In November 2021, the Newton Gateway to Mathematics held a three, halfday virtual event series on ‘Modelling Behaviour to Inform Policy for Pandemics’, which consisted of three main themes:
Understanding Behaviours
Integrating Behaviours Into Models
Using Behavioural Models to Inform Policy.
This event series consisted of talks from experts at the forefront of behavioural science, mathematical modelling and economics. The desire to focus and collaborate on specific problems has led to the formation of the February event.
This event was held virtually and was guided by links with the JUNIPER Consortium and delivered by the RAMP Continuity Network, the followon to the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative. It brought together modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on COVID19.
Aims and Objectives
Following on from the November 2021 event series, this virtual workshop aimed to bring together the relevant scientific communities (epimodellers and economic epidemiologists) to work on addressing current problems in modelling behaviour and its epidemiological, economic and societal implications for the COVID19 pandemic. The following four problems were presented and potential solutions were be discussed.
3817245

Big Data and the Role of Statistical Scalability
ucs_sms_2680025
http://sms.cam.ac.uk/collection/2680025
The ability to collect and store data has increased exponentially in recent years. So too have the challenges around managing the huge volumes generated and trying to extract meaningful information from it. However, it’s universally acknowledged that such ‘Big Data’ has the potential to transform many aspects of people's lives, particularly in datarich areas – including industries, government agencies, science and technology. Examples range from the use of the Oyster card to improve London’s transport network, to the Square Kilometre Array astrophysics project that has the potential to transform understanding of the universe.
The important role of statistics within Big Data has been clear for some time. Statistical techniques, such as sampling populations, confounders, multiple testing, bias, overfitting and generally dealing with variation in the data, are essential for modelling and effective analysis. A major challenge of working with Big Data is that the volume can exceed what is feasible to compute with and traditional methods can fail to scale up. There has also been a tendency to focus purely on algorithmic scalability, e.g., developing versions of existing statistical algorithms that scale better with the amount of data. However, such approaches ignore the fact that fundamentally new issues often arise, and highly innovative solutions are required.
This workshop was part of the six month programme at the Isaac Newton Institute (INI) on Statistical Scalability. The Programme aimed to help address some of these issues by simultaneous consideration of the methodological, theoretical and computational challenges involved and the development of robust, scalable methods, crucial to unlocking the potential of Big Data. This event was also in collaboration with the EPSRC funded StatScale Network.
Aims and Objectives
This knowledge exchange event by the Turing Gateway to Mathematics sought to extend the reach of the research being undertaken as part of the INI Statistical Scalability Research Programme. It opened up the discussion to a wide audience, including those working in multiple industrial sectors, Government and the public sector.
Because interest in Big Data is so intense, the field is developing very rapidly. This event therefore facilitated the dissemination of stateoftheart statistical research and highlighted a number of key future research directions, such as:
Statistical inference after model selection
Model misspecification
Tradeoffs between statistical and computational efficiency
Sequential decision problems
New data types
There was also three enduser sessions which featured speakers from the health, energy and communications sectors. Speakers described how Big Data scaling is managed in their organisations and the challenges they face. Each session included time for discussion and feedback from the audience.
The workshop also included a poster exhibition, which ran during the lunch and the drinks/networking session and there was a short discussion and question session to finish. It was expected to bring together industrial and academic experts from a diverse set of backgrounds and areas, including healthcare, medicine, manufacturing, finance, defence, engineering, security, communications, Government and the public sector.
2680025

Big proof
ucs_sms_2520307
http://sms.cam.ac.uk/collection/2520307
Proofs as constructive demonstrations of mathematical validity have been at the heart of mathematics since antiquity. Formal proof systems capture the definitions, statements, and proofs of mathematical discourse using precisely defined formal languages and rules of inference. Formal proofs have enabled mathematicians to rigorously explore foundational issues of expressiveness, consistency, independence, completeness, computability, and decidability. The formalisation of proof facilitates the representation and manipulation of mathematical knowledge with modern digital computers. During the last sixty years, the digitisation of formal mathematics has yielded satisfiability solvers, rewriting engines, computer algebra systems, automated theorem provers, and interactive proof assistants. Proof technology can be used to perform large calculations reliably, solve systems of constraints, discover and visualise examples and counterexamples, simplify expressions, explore hypotheses, navigate large libraries of mathematical knowledge, capture abstractions and patterns of reasoning, and interactively construct proofs. The scale and sophistication of proof technology is approaching a point where it can effectively aid human mathematical creativity at all levels of expertise. Modern satisfiability solvers can efficiently solve problems with millions of Boolean constraints in hundreds of thousands of variables. Automated theorem provers have discovered proofs of open problems. Interactive proof assistants have been used to check complicated mathematical proofs such as those for the Kepler’s conjecture and the FeitThompson odd order theorem. Such systems have also been applied to the verification of practical artifacts such as central processing units (CPUs), compilers, operating system kernels, file systems, and air traffic control systems. Several highlevel programming languages employ logical inference as a basic computation step.
This programme is directed at the challenges of bringing proof technology into mainstream mathematical practice. The specific challenges addressed include
Novel pragmatic foundations for representing mathematical knowledge and vernacular inspired by set theory, category theory, and type theory.
Largescale formal mathematical libraries that capture background knowledge spanning a range of domains.
Algorithmic and engineering issues in building and integrating largescale inference engines.
The social exploration and curation of formalised mathematical and scientific knowledge.
Educational proof technology in support of collaborative learning.
This programme brings together mathematicians interested in employing proof technology in their research, logicians exploring pragmatic and foundational issues in the formalisation of mathematics, and computer scientists engaged in developing and applying proof technology. The programme includes a weeklong workshop exploring foundational, theoretical, and practical challenges in exploiting proof technology to transform mathematical practice across a range of scientific and engineering disciplines. A key expected output is a concrete, longterm research agenda for making computational inference a basic technology for formalising, creating, curating, and disseminating mathematical knowledge in digital form.
2520307

Big Proof  Challenges in Industry and Research
ucs_sms_2531518
http://sms.cam.ac.uk/collection/2531518
Wednesday 19th July 2017
The Alan Turing Institute
London
United Kingdom
Background
Formal proof systems have been used as constructive demonstrations of mathematical validity for millennia. The generally agreed criteria for formal proofs are that they should have reproducibility (easily accessible and communicable), objectivity (accurately representative) and have verifiability (It being possible to recognise that something is a proof).
They are essential in the context of hardware and software systems where formal verification is needed to prove or disprove the correctness of intended algorithms which underpin a systems specification. Formal proofs are used for the verification of systems such as cryptographic protocols, combinational circuits, digital circuits with internal memory and software expressed as source code.
This workshop, part of the Isaac Newton Institute Research Programme Big Proof, brought together mathematicians, computer scientists and logicians with those from relevant application areas. The research programme seeks to explore foundational, theoretical, and practical challenges in exploiting proof technology to transform mathematical practice across a range of scientific and engineering disciplines. A key expected output was a concrete, longterm research agenda for making computational inference a basic technology for formalising, creating, curating, and disseminating mathematical knowledge in digital form.
Aims and Objectives
The aim of the workshop was to promote discussion around the area of big proof and formal verification, and the challenges from academic and industry perspectives. For example, academic challenges are presented by the problem of scaling mathematical proof on machine, including issues such as search, representation and reasoning in ways that are more natural to working mathematicians than current systems offer. Conversely, industry challenges may be posed around the limits of automation and the efficiency of current logics and algorithms.
The Programme of talks featured both academic and industry speakers and included areas such as:
Verification for mainstream software and security
Bringing big verification proof to big finance
Big proofs from social networks of mathematics
Reasoning with big code
Reasoning at scale for cloud computing security
A key aspect of the workshop was to encourage links between academics and industry and allowed both parties to further understand the others’ needs. Therefore, as well as highlighting stateoftheart mathematics for formal proof systems, talks also covered end user challenges and experiences. Discussion and networking sessions allowed for new research directions to be discussed and areas of mutual interest were explored.
Registration and Venue
Registration for this event is now closed.
The workshop took place at the Alan Turing Institute, London. The Institute is headquartered at the British Library. Please see the link for directions to the venue.
Organisers
Professor David Aspinall (University of Edinburgh and Alan Turing Institute) and David Butler (Alan Turing Institute)
2531518

Bringing pure and applied analysis together via the WienerHopf technique, its generalisations and applications
ucs_sms_3040667
http://sms.cam.ac.uk/collection/3040667
Programme Theme
The WienerHopf technique enables us to solve numerous physical problems motivated by real world applications modelled, for example, by partial differential equations and stochastic processes. The WienerHopf technique is currently used in a wide range of disciplines including acoustics, finance, Lèvi processes, hydrodynamics, elasticity, potential theory and electromagnetism.
The theory of scalar WienerHopf equations is now very rich and well developed. In contrast, much less is known about matrix WienerHopf equations. These are a natural extension of the scalar case, and enable us to model more advanced problems. As it stands, solutions to matrix WienerHopf problems have to be constructed on a casebycase basis, or in an approximate fashion. The focus of this programme will be on matrix WienerHopf equations, constructive numerical methods and applications. The three main aims will be:
Matrix factorisation, approximate methods and their numerical implementation.
There are numerous approximate methods for WienerHopf matrix factorisation. However, there is no clear picture for deciding when a method is appropriate or numerically efficient. Consequently, approximate WienerHopf factorisation is highly specialised and a difficult subject for nonexperts. An important outcome of the programme will be to make this more routine by filling the outstanding gaps in the literature. There is also a lot of scope for the theoretical study of methods motivated by applications. This requires a close collaboration between mathematicians from the pure and applied communities. Developing existing methods into working algorithms and making them freely available in a toolbox will make the WienerHopf technique more easily accessible for applications than is currently the case.
Establishing links between different applications of the WienerHopf method.
There are several disjoint communities who rely on the WienerHopf method, and developments in one field often go unnoticed in another. There is much to be gained by generalising the developments in one area to solve open problems in other areas.
Consolidating existing knowledge and developing a set of promising new directions.
We will consider the area as a whole, pose open problems and map out promising directions. This will highlight new developments and applications, and make the area more attractive to young researchers.
The above aims will be achieved by bringing together internationally leading experts in the WienerHopf technique from diverse areas and catalyse new interactions between them. There will be an emphasis on enabling young researchers to meet and interact with established experts.
3040667

Cambridge Science Festival at the Isaac Newton Institute
ucs_sms_536912
http://sms.cam.ac.uk/collection/536912
Discover centuries of science at the Cambridge Science Festival.
Read more at: http://comms.group.cam.ac.uk/sciencefestival/
536912

Cambridge Statistics Initiative 2011
ucs_sms_1178921
http://sms.cam.ac.uk/collection/1178921
The Cambridge Statistics Initiative (CSI) will host a third Special OneDay meeting, jointly organised with the Design and Analysis of Experiments programme at the Isaac Newton Institute for Mathematical Sciences. This is part of continuing efforts to bring together statisticians from various fields within the University of Cambridge and outside, to meet as well as encourage new research collaborations within academia and industry. The previous CSI Special OneDay meeting was held in September 2009. The CSI is funded by the EPSRC Science and Innovation Award, Isaac Newton Institute, School of Physical Sciences, and Mathematics to enhance and foster innovative research into statistics, bridging applied and theoretical statistics.
Read more at: http://www.statslab.cam.ac.uk/Statistics/CSI/meeting2011.html
1178921

Cantab Capital Institute for the Mathematics of Information – Connecting with Industry
ucs_sms_2613223
http://sms.cam.ac.uk/collection/2613223
The Cantab Capital Institute for the Mathematics of Information (CCIMI) will hold an Industry engagement day in November 2017. This event aims to showcase the research that is being carried out at the Institute and will present an opportunity to hear in detail about some of the current project collaborations, other industry challenges and explore new potential collaborations.
This event follows the previous industry and academic engagement events delivered in November 2016 and May 2017.
The Cantab Capital Institute for the Mathematics of Information accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is at the highest international level, aiming to extract the relevant information from large and highdimensional data with a predictable certainty. For more detailed information on projects, please see the CCIMI website.
Aims and Objectives
The main focus of this one day conference event was as an industrial engagement day that provided an update on research and collaborations taking place at CCIMI, as well as highlighting projects being developed elsewhere.
The talks highlighted research taking place at CCIMI, with associated industrial engagements and looked to explore the big questions in data science where mathematics is most suited to help provide answers.
There was the opportunity to present at a poster exhibition, which ran during the lunch and the networking sessions and the event closed with a facilitated panel session, followed by a drinks reception.
This event was of interest to participants including economists; social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied and computational analysis; quantum computing, cryptography, communication and security and those from data processing.
2613223

Cantab Capital Institute for the Mathematics of Information – Industry Engagement
ucs_sms_3713418
http://sms.cam.ac.uk/collection/3713418
The Cantab Capital Institute for the Mathematics of Information (CCIMI) held its annual Industry engagement event on the 24th November 2021.
Launched in 2016, CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is of the highest international level, aiming to extract the relevant information from large and highdimensional data with a predictable certainty.
This event follows previous successful academic and industrial engagement events, which have focused on different aspects related to the mathematics of information.
Aims and Objectives
This conference brought together those academics working to advance data science and will aim to showcase the research that is being carried out at the Institute and enable delegates to hear more detail about some of the current project collaborations and industry challenges that CCIMI is exploring. Additionally, it will highlight other potential collaborative opportunities, as well as projects being developed elsewhere related to data analysis.
There was a session of short “elevator pitches” from next generation researchers as well as a poster session by some registered delegates.
This event was of interest to participants including economists; social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied & computational analysis; quantum computing, cryptography, communication & security and those from data processing.
3713418

Cardiac Physiome Project
ucs_sms_649452
http://sms.cam.ac.uk/collection/649452
Predicting physiological behaviour from experimental data combined with environmental influences is a compelling, but unfulfilled, goal of postgenomic biology. This undeniably ambitious goal is the aim of the Physiome Project and its subset the Cardiome Project which is an international effort to build a biophysically based multiscale mathematical model of the heart. To achieve this goal requires further development of the current generation of advanced cardiac models which span an already diverse set of mathematical representations from stochastic subcellular regulation models to wholeorganbased sets of coupled partial differential equations. The focus of this programme will be on the development and application of the mathematical techniques which underpin the ongoing extension of this approach, and specifically to:
* integrate data from disparate sources into a common quantitative framework;
* examine the complex cause and effect relationships which exist across many temporal and spatial orders of magnitude in physiology;
* determine the appropriate level of detail to capture observable phenomena and the closely related issue of parameter identifiability;
* examine issues of model inheritance and multiscale coupling for combining existing models together to create extended frameworks;
* define standards for the constituent electrical, mechanical and vascular classes of cardiac models.
Read more at: www.newton.ac.uk/programmes/CPP/
649452

Challenges in Landscape Decisionmaking
ucs_sms_3016713
http://sms.cam.ac.uk/collection/3016713
Background
The numerous processes and interactions around landscapes, present significant challenges for stakeholders who need to make better evidencebased decisions, necessary for planning and management of the various landscape domains in the UK. Landscapes are always changing too  shaped by various interactions between geographical, climatic, socioeconomic pressures and the dynamics of ecological systems. So making such decisions are often fraught with risk and complexity.
Within landscapes, numerous processes operate and interact across different spatial and temporal scales. As well as physical and biogeochemical factors, anthropogenic (human) activity also has a big impact on landscape structures and this makes it extremely challenging to try to understand causal relationships between these structures and processes. Furthermore, decisions need to be made about the future of landscapes amidst uncertainties in climate, social and economic environments, all of which can have a significant impact on landscapes.
It’s clear that better methodologies need to be developed in order to capture the complexity and uncertainty inherent in landscape decisionmaking. Mathematical and statistical modelling techniques are a powerful tool to aid decisionmaking since they provide a way to combine different spatial and temporal processes as well as incorporate future uncertainty. However, a number of statistical and mathematical challenges need to be overcome, in order to ensure the accuracy and usefulness of these approaches for decisionmakers.
This knowledge exchange workshop is part of the one month Research Programme at the Isaac Newton Institute (INI) on Mathematical and Statistical Challenges to Landscape Decision Making It forms day 1 of the three day research workshop on Current status and key questions in Landscape Decisionmaking.
Aims and Objectives
This workshop aims to set the scene on current decisionmaking approaches and help define policyrelevant areas where advances in mathematical and statistical modelling would be particularly valuable. It will be of interest to researchers from a number of areas including mathematics, statistics, environmental science, geography, ecology and biology, as well as stakeholders from government/public sector, business, and other organisations involved in urban planning, coastal/inland waters and land conservation and management.
The day will feature talks from academic researchers and stakeholders to highlight the needs for and challenges associated with landscape modelling, as well as relevant advances in mathematical and statistical modelling techniques. Session one will set the scene in terms of stakeholder needs for landscape models and the interacting components of landscapes that need to be represented in such models. This will be followed by Sessions 2, 3 and 4 which will include presentations from academics and stakeholders describing the stateoftheart in landscape modelling from the rural, urban and coastal/inland waters domains.
The focus for the day is matching the challenges faced by stakeholders involved in the management and planning of different landscape domains in the UK with advances in modelling approaches. It is intended that this will reveal key knowledge gaps and research questions that can be explored during the following onemonth INI research programme, which runs 3rd July to 2nd August 2019.
3016713

Climate Modelling and Prediction Showcase
ucs_sms_1084803
http://sms.cam.ac.uk/collection/1084803
A showcase of seminars from the Isaac Newton Institute programme 'Mathematical and Statistical Approaches to Climate Modelling and Prediction'.
For more information visit: http://www.newton.ac.uk/programmes/CLP/
1084803

Cluster algebras and representation theory
ucs_sms_3647945
http://sms.cam.ac.uk/collection/3647945
Programme theme
The theory of cluster algebras is one of the most active research areas in Mathematics over the last 18 years. Introduced by Fomin and Zelevinsky in 2002 in the context of Lie theory and total positivity, cluster algebras quickly developed deep connections to different disciplines such as representation theory, combinatorics, algebraic, hyperbolic and symplectic geometry, dynamical systems, topology and string theory. Among the major applications of cluster algebras are the construction of part of Lusztig's dual semicanonical basis in Lie theory, the discovery of generalized associahedra in combinatorics, the development of clustertilting theory in the representation theory of finite dimensional algebras, the proof of Zamolodchikov's periodicity conjecture in conformal field theory, the development of a new approach to Teichmüller theory and the discovery of a fundamental relationship with DonaldsonThomas invariants and wallcrossing in algebraic geometry. Much work on cluster algebras has centred around applications to the representation theory of finite dimensional algebras. These grew from categorical models for cluster algebras. In particular, the clustertilted algebras arising from cluster categories have given new insights into classical tilting theory. The interaction is in both directions, with the representationtheoretic models also being used to answer fundamental questions about cluster algebras. This programme will focus on interactions between cluster algebras and representation theory as well as interdisciplinary applications of cluster algebras.
3647945

Combinatorics and Statistical Mechanics
ucs_sms_87
http://sms.cam.ac.uk/collection/87
The past halfdecade has seen an increasing interaction between combinatorialists, probabilists, computer scientists and theoretical physicists concerned broadly with the study of "probability theory on graphs" or "statistical mechanics on graphs".
The programme will build on this crossfertilisation. It is particularly timely for a number of reasons:
* methods from mathematical physics are beginning to make their mark on previously intractable combinatorial problems;
* increasing computer power, together with the wide availability of symbolicalgebra packages, has brought the possibility of exploration of nontrivial examples;
* phase transitions are increasingly being investigated on a wide variety of combinatorial structures, including matroids, set partitions and constraint satisfaction problems, as well as graphs.
Read more at: www.newton.ac.uk/programmes/CSM/
87

Compressed Sensing LMS Series 2011
ucs_sms_1117766
http://sms.cam.ac.uk/collection/1117766
LMS Invited Lecturer 2011
Emmanuel Candes, Stanford
March 2125 2011
Isaac Newton Institute
The annual Invited Lecturers scheme aims to bring a distinguished overseas mathematician to the United Kingdom to present a small course of about ten lectures spread over a week. Each course of Invited Lectures is on a major field of current mathematical research, and is instructional in nature, being directed both at graduate students beginning research and at established mathematicians who wish to learn about a field outside their own research specialism.
Emmanuel Candes will give an eightlecture minicourse, at a level suitable for graduate students, on Compressed Sensing. This is a subject very much at the interface of pure and applied mathematics and the lectures should interest a wide audience. There will also be onehour lectures by:
Mike Davies (Edinburgh)
Compressed sensing in RF
Anders Hansen (Cambridge)
Generalized sampling and infinitedimensional compressed sensing
Vincent Rivoirard (ParisDauphine)
The Dantzig selector for high dimensional statistical problems
Carola Schoenlieb (Cambridge)
Minimisation of sparse higherorder energies for largescale problems in imaging
More info at: http://www.dpmms.cam.ac.uk/~bjg23/candeslectures.html
1117766

Computational Challenges in Image Processing
ucs_sms_2560293
http://sms.cam.ac.uk/collection/2560293
Background
Image processing is a dynamic and fast moving field of research. Recent advances in the area have led to an explosion in the use of images in a variety of scientific and engineering applications. New approaches are constantly being developed by mathematicians, engineers and computer scientists to be applied to image processing problems. Image processing, along with mathematical imaging and computer vision have become fundamental for gaining information on various aspects in medicine, the sciences, and technology, in the public and private sector equally. The rapid development of new imaging hardware, the advance in medical imaging, the advent of multisensor data fusion and multimodal imaging, as well as the advances in computer vision have sparked numerous research endeavours leading to highly sophisticated and rigorous mathematical models and theories.
There are many computational challenges in image processing. These include issues such as the handling of image uncertainties that cannot be otherwise eliminated, including various sorts of information that is incomplete, noisy, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. However, some computational techniques such as fuzzy logic, neural networks, and evolutionary methods have shown great potential to solve such image processing problems.
This afternoon workshop, part of the Isaac Newton Institute Research Programme Variational Methods and Effective Algorithms for Imaging and Vision, brought together mathematicians, computer scientists and engineers from both the research and industry communities. Talks from academics and endusers explored various computational challenges around areas of image processing.
Aims and Objectives
This Open for Business workshop aimed to extend the reach of the Isaac Newton Institute research programme, by fostering exchange between different groups of researchers and practitioners who are involved in imaging science. The event highlighted both some of the challenges and potential novel solutions for computational image processing. Talks and discussion highlighted possible new mathematical models which are needed to address the ever growing challenges in applications and technology, generating new demands that cannot be met by existing mathematical concepts and algorithms.
The Programme of talks featured academic stateoftheart talks, as well as enduser challenge type presentations and included areas such as:
Variational image processing
Optimisation and machine learning approaches
Development of computational methods that enable semiautomatic analysis
Algorithmic challenges of global optimisation and convex relaxation methods as well as stochastic optimisation for large and highdimensional imaging problems
Dynamic image processing challenges
Medical image processing challenges
Remote sensing: aerial and satellite image interpretations and Image processing challenges
The workshop included a poster exhibition, which ran during the lunch and the drinks/networking session. It brought together industrial and academic experts from a diverse set of backgrounds in mathematics, computer science and information engineering. Many relevant sectors included computer and software engineering, medical and biomedical, security/biometrics, environmental monitoring, industrial automation/inspection, traffic management, media and creative industries.
2560293

Controlling COVID19 in Schools: Lessons Learned and Open Questions
ucs_sms_3912751
http://sms.cam.ac.uk/collection/3912751
Background
The control of SARSCoV2 within the school setting poses a unique challenge. While policy makers must consider the impact that uncontrolled transmission within schools may have on transmission within the community at large, they must also consider the impact of restrictions to reduce withinschool transmission on pupil absences, educational attainment, and other factors.
Since the beginning of the COVID19 pandemic, a range of control measures have been introduced to control SARSCoV2 transmission in schools, from maskwearing to regular mass testing to the isolation of close contacts. Correspondingly, a range of studies and approaches have been used to understand the effectiveness and impact of different control measures, from modelling studies to randomised controlled trials.
Understanding the true impact of different measures is paramount to the design of effective control measures within the school setting. This session aimed to synthesise what we have learnt about the impact of SARSCoV2 in the school setting and to identify the gaps in knowledge that are vital to answer going forward to plan better schoollevel control policies for SARSCoV2 and for future pandemics. Guided by links with the JUNIPER Consortium, this event was delivered by the RAMP Continuity Network, the followon to the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative.
Aims and objectives
This oneday workshop aimed to reflect on the lessons learned about the study of SARSCoV2 control in schools, focusing on three broad categories:
What impact does transmission within school settings have on transmission in the community?
How effective are schoollevel control measures at reducing SARSCoV2 transmission within schools?
What are the other impacts of SARSCoV2 transmission and control measures in schools?
Moreover, the workshop outlined the questions most needing answered and studies most needing to be undertaken in order to plan optimal policies for schools for COVID19 and future pandemics. It will bring together researchers from a diverse range of disciplines, from mathematical modellers to social scientists to policy experts, to support the pandemic modelling community already working on COVID19.
3912751

Correspondents Day
ucs_sms_2657630
http://sms.cam.ac.uk/collection/2657630
2657630

Coupling Geometric PDEs with Physics for Cell Morphology, Motility and Pattern Formation
ucs_sms_1633792
http://sms.cam.ac.uk/collection/1633792
The aim of this sixmonth research programme is to create a unique forum to strengthen and develop research links between stateoftheart experimental "wet" sciences (biology, medicine, biophysics) and theoretical "dry" sciences (pure, applied and computational mathematics, theoretical physics, statistics). In this programme we will discuss and present in a handson format current experimental methodology for cell motility and pattern formation. We will emphasise interactions between experimentalists and theoreticians, with the dual goals of understanding how current mathematical techniques from physics, differential geometry, mathematical modelling and numerical analysis can help to understand current problems in the areas of cell motility and pattern formation, and what new mathematical techniques may emerge in the process.
Read more at http://www.newton.ac.uk/programmes/CGP/
1633792

Current status and key questions in Landscape Decision making
ucs_sms_3016714
http://sms.cam.ac.uk/collection/3016714
Workshop Theme
Land is a key limiting resource in many regions of the world, including the UK. Society depends on land resources for many purposes, including urban settlement, employment and transportation, as well as a host of benefits we get from nature (ecosystem services)  food, timber, energy, recreation, and aesthetic benefits. We require these land resources to be resilient to environmental change, and to meet increasing demands for not only housing, but also renewable energy, recreation and climate change mitigation. Landuse therefore connects many of the UN Sustainable Development Goals. In the UK, EU exit will require the introduction of many new policies connected to landuse (e.g. replacing the Common Agricultural Policy, the EU Biodiversity Strategy, etc) – implying an urgent need to develop better landscape decision tools. The onemonth INI programme explores the mathematical and statistical challenges associated with making use of the latest observations to understand and project landuse changes. Questions to be addressed will include: what is the minimal useful representation of the landscape system? How do we robustly model the coupled humanenvironment system without assuming that people act as perfectly rational economic agents? Where are the nonlinearities and sensitivities of the system, and how could these be used to produce transformative changes in landuse? How do we reconcile scale disconnects between different elements of humanenvironment systems?
This threeday workshop will open the INI research programme, focusing on reviewing the stateoftheart in modelling land systems and identifying key knowledge gaps where collaboration between different environmental, mathematical and social science disciplines may lead to new insights, methods and tools. The first day of the workshop will be open to stakeholders to set the scene on current decisionmaking approaches and to define policyrelevant areas where advances in the stateoftheart would be particularly valuable.
Participants in the workshop will include a highly interdisciplinary mix of both academic and nonacademic researchers and stakeholders working on landrelated research and policy questions. These will include (but not be limited to) participants interested in agriculture, forestry, water resources and biodiversity, as well as mathematicians, statisticians and computer scientists expert in system modelling, uncertainty quantification and decision making who are also interested in these wide ranging applied questions.
The workshop programme will be available soon. Days 2 and 3 of the workshop will consist of both talks and panel discussions covering the following topics:
"Decisionmaking in the face of uncertainty"
Modelling social/human processes in landscapes
Model coupling
Spatial/temporal scaling
Nonlinearities and tipping points
Benchmarking, calibration and uncertainty (including the role of model emulation)
3016714

Data Linkage and Anonymisation
ucs_sms_2276450
http://sms.cam.ac.uk/collection/2276450
Public policy decisions and much scientific research hinge on accurate and comprehensive data about people. Commercial organisations base their success similarly on data describing how people behave.
2276450

Dense Granular Flows
ucs_sms_521697
http://sms.cam.ac.uk/collection/521697
Following the 2003 INI programme Granular and ParticleLaden Flows, the Institute of Mathematics and its Applications has held two conferences on Dense Granular Flows at the Isaac Newton Institute:
5  9 January 2009 IMA Conference on Dense Granular Flows
1  4 July 2013 2nd IMA Conference on Dense Granular Flows
Flows involving solid particulates are ubiquitous in nature and industry alike. Such flows are found in pharmaceutical production, the chemical industry, the food and agricultural industries, energy production and the environment. Many unsolved problems remain, however. For example, the rejection rate by US pharmaceutical manufacturers is around 5% with the cost of losing a single batch of medication ranging from £50,000 to £500,000. In order to be able to solve such problems, granular flows need to be understood so that their behaviour can be controlled and predicted.
To date, we are able to describe rapid granular flows, where the particles are highly agitated and there has been some success describing static systems. The intermediate regime, where these two phases meet and coexist, is not as well understood and yet is the most commonly observed behaviour of granular flow. The objective of these meetings is to interface the two ends of the particulate flow spectrum – those working to understand the fundamentals of granular flows and those attempting to control particulate flows in an industrial setting  to develop solutions to the complex problems presented by dense granular flows.
http://www.ima.org.uk/conferences/conferences_calendar/dense_granular_flows.cfm
521697

Design and Analysis of Experiments
ucs_sms_125
http://sms.cam.ac.uk/collection/125
Design of experiments was born as a result of an unlikely, but true anecdote: a lady claimed before R.A. Fisher that she was able to ascertain whether milk was poured before or after tea in her cuppa. Fisher devised a study to verify her claim and, in turn, this gave birth to Experimental Design. Agricultural experiments formed the core around which the theory evolved in its origins in the 1930s. The theory of Design of Experiments has since blossomed into many different approaches, ranging from optimal designs for dynamical models in pharmacokynetic studies, and designs for industrial experimentation, to designs of simulation experiments in climate change, to name but a few. The mathematical techniques currently used in different branches of Design are vast, for example Galois theory, non linear optimization, algebraic geometry and association schemes.
This media collection contains seminars from the following INI programmes:
Design and Analysis of Experiments 2011: http://www.newton.ac.uk/programmes/DAE/
Design of Experiments 2008: http://www.newton.ac.uk/programmes/DOE/
125

Developments in Healthcare Imaging  Connecting with Academia
ucs_sms_2742941
http://sms.cam.ac.uk/collection/2742941
The EPSRC Centre for Mathematical Imaging in Healthcare (CMIH) held its second annual academic conference which was delivered in partnership with the Liverpool Centre for Mathematical Sciences in Healthcare (LCMH).
Both Centres were created following investment in five new UK Research Centres by the Engineering and Physical Sciences Research Council (EPSRC) in December 2015. A key aim of the partnerships is the delivery of high quality, multidisciplinary research that will help overcome some of the big challenges facing the NHS. Their remit is to explore how mathematics and statistics can help clinicians to tackle serious health challenges such as cancer, heart disease and antibiotic resistant bacteria. Specifically, researchers will develop new tools from predictive mathematical models to enable earlier diagnosis of chronic diseases such as epilepsy, and new systems to make clinical imaging more accurate and efficient.
CMIH is based at the University of Cambridge and aims to achieve synergies between applied mathematics and statistics through the focus on the analysis of clinical imaging, particularly that arising in neurological, cardiovascular and oncological imaging. The Centre is a collaboration between mathematics, engineering, physics and biomedical scientists and clinicians.
LCMH is based at the University of Liverpool and is carrying out multidisciplinary research to explore how mathematics and statistics can deliver a more refined and accurate set of predictive models and tools for personalised healthcare delivery. It brings together collaborating mathematicians, scientists, engineers and clinicians at the Universities of Liverpool and Lancaster with industrial partners and policy.
Aims and Objectives
This one day conference brought together those academics working on advances in imaging technology with researchers who investigate new image analysis methods, to help address current challenges. New imaging technology goes side by side with the need for mathematical models to maximise the information gain from these novel imaging techniques.
This event presented the opportunity to hear in detail about some of the current project collaborations, and focused on the academic interactions taking place in the field of medical imaging and especially across the EPSRC Centres for Mathematical Sciences in Healthcare.
The Programme featured talks that highlighted the role that deep learning can play alongside fundamental mathematical and statistical techniques used in medical imaging, including image analysis and modelling. There was a session for short “elevator pitches” where researchers presented snapshots of their work, which were further explored during a poster exhibition which ran during the lunch and the drinks/networking session.
The event was of interest to participants from the biomedical imaging, mathematics, engineering, computer science and physics, as well as biology and medicine.
2742941

Developments in Healthcare Imaging  Connecting with Industry
ucs_sms_2586412
http://sms.cam.ac.uk/collection/2586412
Background
The EPSRC Centre for Mathematical Imaging in Healthcare (CMIH) will hold its 2nd Industry engagement day in October 2017. This will aim to showcase the research that is being carried out at the Centre and will present an opportunity to hear in detail about some of the current project collaborations, other industry challenges and explore new potential collaborations.
This event follows the previous industry and academic engagement events delivered in October 2016 and April 2017.
The Centre was launched in March 2016, following the announcement in December 2015 from the Engineering and Physical Sciences Research Council (EPSRC) of a £10 million investment in five new UK Research Centres. The remit of the Centres is to explore how mathematics and statistics can help clinicians to tackle serious health challenges such as cancer, heart disease and antibiotic resistant bacteria.
CMIH is based at the University of Cambridge and aims to achieve synergies between applied mathematics and statistics through the focus on the acquisition and analysis of clinical imaging, particularly that arising in neurological, cardiovascular and oncology imaging. It is a collaboration between mathematics, engineering, physics and biomedical scientists and clinicians.
Aims and Objectives
The Cambridge Centre enables mathematicians and statisticians to work closely with relevant stakeholders involved in the areas of clinical imaging from healthcare planning, clinical provision, policy making and industrial research across the UK. A key aim of this partnership is the delivery of high quality, multidisciplinary research that will help overcome some of the big challenges facing the NHS.
This user engagement day will provide an update on some of the research being carried out and will feature presentations from CMIH Industry Partners, including GSK and Toshiba Medical Visualization Systems. A number of industry challenges and potential new collaborations will be highlighted in an elevator pitch session. A poster exhibition will also run during the lunch and the drinks/networking session.
This event will be of interest to researchers working in the field of analysis of clinical imaging and also to healthcare planners, clinicians, policy makers and industry partners to discuss the research projects and challenges arising from the area. It presents a great opportunity for knowledge exchange and networking between senior scientists from areas such as mathematics, statistics, engineering, physics and biomedicine and relevant individuals from industry and government.
2586412

Discrete Analysis
ucs_sms_1090083
http://sms.cam.ac.uk/collection/1090083
During the past decade or so there have been dramatic developments in the interaction between analysis, combinatorial number theory and theoretical computer science: specifically between harmonic analysis and combinatorial number theory and between geometric functional analysis and the theory of algorithms.
Not only have discoveries in one area been used in others but, even more strikingly, there has emerged a commonality of methods and ideas among these apparently diverse areas of mathematics. The use of harmonic analysis in number theory is at least a century old, but in the recent works of Gowers, Green and Tao and others on the existence of arithmetic progressions in subsets of the integers, and in particular the sequence of primes, it has developed into an entire area: additive combinatorics. Classical inequalities of harmonic analysis, such as the isoperimetric inequality, have discrete analogues that are often more subtle than the continuous versions and have wideranging applications: for example the discrete isoperimetric inequality of Talagrand, which inspired his work on spinglass models.
Read more at: http://www.newton.ac.uk/programmes/DAN/
1090083

Discrete Integrable Systems
ucs_sms_533691
http://sms.cam.ac.uk/collection/533691
The theory of (ordinary and partial) differential equations is wellestablished and to some extent standardised. By contrast, the theory of difference equations, while more fundamental, has until recently been in its infancy, in spite of a major effort at the beginning of the 20th Century by N"orlund and the school of G.D. Birkhoff to establish the linear theory. Discrete systems can appear in two main guises: in the first case the independent variable is discrete, taking values on a lattice (e.g. finitedifference equations, such as recurrence relations and dynamical mappings), in the second case the independent variable is continuous (e.g. analytic difference equations and even functional equations).
Very recently, however, mainly through advances in the theory of exactly integrable discrete systems and the theory of (linear and nonlinear) special functions, the study of difference equations has undergone a true revolution. For the first time good and interesting examples of nonlinear difference equations admitting exact, albeit highly nontrivial, solutions were found and this has led to the formulation of novel approaches to the classification and treatment of such equations. Thus, an area has developed where several branches of mathematics and physics, that are usually distinct, come together: complex analysis, algebraic geometry, representation theory, Galois theory, spectral analysis and the theory of special functions, graph theory, and difference geometry.
Read more at: www.newton.ac.uk/programmes/DIS/
533691

Dynamics of Discs and Planets
ucs_sms_665815
http://sms.cam.ac.uk/collection/665815
Ever since the discovery in 1995 of an object with half the mass of Jupiter in a fourday orbit around the star 51 Pegasi, it has been clear that the dynamics of extrasolar planetary systems can be quite different from that of our solar system. More than 200 extrasolar planets have now been found, including at least 20 systems with multiple planets, some in resonant configurations. Their diversity must originate in the properties of the protoplanetary disc of dusty gas out of which they form, the dynamics of the formation of the planetary core, and the subsequent interaction of the planet with the surrounding disc, with other planets, and with the central star.
Over the past decade, there has been significant progress on the theoretical aspects of the planet formation process. Two viable models of planet formation have been explored, core accretion (growth of dust into planets through mutual collisions) and gravitational instability in the disc, and several modes of angular momentum exchange between planet and disc have been identified which may explain the proximity of the 51 Peg planet to its star. However, many of the stages of planet formation remain poorly understood. In part this is because of a lack of knowledge of the physical nature of protoplanetary discs, although this has increased dramatically in recent years owing both to observations of the gaseous and dusty components of the discs of premainsequence stars and to computational modelling of their (magneto) hydrodynamics. The outcome of planet formation is also becoming more tightly constrained, through the growing number of systems known to have either extrasolar planets or planetesimal belts analogous to the asteroid and Kuiper belts. The discovery of planetesimals and dwarf planets in the Kuiper belt beyond Neptune is also leading to a revision in our understanding of the formation and evolution of the outer solar system. The wide array of phenomena seen in all systems is opening up new areas of celestial mechanics.
Read more at: http://www.newton.ac.uk/programmes/DDP/
665815

Environmental and Aerosol Transmission of COVID19
ucs_sms_3520121
http://sms.cam.ac.uk/collection/3520121
Monday 26th April 2021 to Wednesday 28th April 2021
Background
Better understanding of the transmission of COVID19 is a key factor in managing risk and designing practical interventions. The Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative brought modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on Coronavirus (COVID19), including on environmental and aerosol transmission. With the reduction of lockdown restrictions over the next few months, insights into areas such as the role of ventilation and the impact of people moving around within buildings are particularly timely.
Developed by the Newton Gateway in its key role in the RAMP Continuity Network (a UKRI funded project), this event brought together academics from multiple disciplines and key stakeholders. This project was guided by links with groups such as the JUNIPER consortium and the Isaac Newton Institute Infectious Dynamics of Pandemics research programme and ensured relevance to current UK policy, and ensured engagement with the wider mathematical modelling and epidemiology communities.
Aims and Objectives
Building on the work begun by RAMP, this threeday science meeting reviewed existing work and identified where further research is most urgently needed. The meeting included a standalone publicfacing component providing an accessible overview of the latest science, alongside scientific talks and discussion sessions targeting active researchers.
The aims of the meeting were:
i) Bring together a wide range of participants to maximise the engagement from different communities.
ii) Better inform the public on the science underlying viral transmission.
iii) Progress the most promising areas of research, and reach consensus on future research directions and research activity.
A programme of this past event is now available. Please follow the link.
On Tuesday 27th April, there were publicfacing talks by:
Professor Lidia Morawska (Queensland University of Technology) talked about “Airborne transmission of respiratory infections: beyond COVID19”.
Professor Cath Noakes OBE (University of Leeds) talked about “Understanding COVID19 transmission mechanisms and uncertainties”.
3520121

Epidemic Models: Insights from the RAMP Project
ucs_sms_3856195
http://sms.cam.ac.uk/collection/3856195
Background
Better understanding of the transmission of COVID19 is a key factor in managing risk and designing practical interventions. The Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative brought modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on Coronavirus (COVID19), including on environmental and aerosol transmission.
RAMP was designed to provide support from the UK mathematical modelling community for existing research groups; create new models or insights that could be used to inform the work of the Government’s scientific advisors, through data sciencebased approaches; apply knowledge from related epidemiology domains; and triage incoming literature to ensure effective information flows. The goal of RAMP was to enhance modelling capacity to support rapid assessment of strategies of immediate policy relevance.
Aims and Objectives
Building on the RAMP initiative, these 2 half day events included talks by those who, via the RAMP project or otherwise, realigned their research to focus on human epidemic modelling after the COVID19 pandemic had begun. Speakers presented highlights of modelling that took place, as well as updates where this continues, there was opportunity for participates to pose some questions to help push the field further forward more broadly.
Talks explained how well models performed earlier in the pandemic, providing an update on more recent progress and identifying some useful learning for modellers going forward. A number of different models were presented highlighting methodological developments and applications to various datasets.
Developed by the Newton Gateway in its key role in the RAMP Continuity Network (a UKRI funded project), this event brought together academics from multiple disciplines and key stakeholders. This project was guided by links with groups such as the JUNIPER consortium and the Isaac Newton Institute Infectious Dynamics of Pandemics research programme to ensure relevance to current UK policy, and ensured engagement with the wider mathematical modelling and epidemiology communities.
3856195

Evaluation Workshop of the first CAMI Challenge
ucs_sms_2240609
http://sms.cam.ac.uk/collection/2240609
Critical Assessment of Metagenome Interpretation (CAMI)
The interpretation of metagenomes relies on sophisticated computational approaches, such as short read assembly, binning and taxonomic classification. All subsequent analyses can only be as meaningful as the outcome of these initial data processing methods. Tremendous progress has been achieved during the last years. However, none of these approaches can completely recover the complex information encoded in metagenomes. Simplifying assumptions are needed and lead to strong limitations and potential inaccuracies in their practical use.
The accuracy of computational methods in metagenomics has so far been evaluated in publications presenting novel or improved methods. However, these snapshots are hardly comparable due to the lack of a general standard for the assessment of computational methods in metagenomics. Users are thus not well informed about general and specific limitations of computational methods. This may result in misinterpretations of computational predictions. Furthermore, method developers need to individually evaluate existing approaches in order to come up with ideas and concepts for improvements and new algorithms. This consumes substantial time and computational resources, and may introduce unintended biases.
We suggest tackling this problem by a new initiative, aiming at the “Critical Assessment of Metagenome Interpretation” (CAMI). It should evaluate methods in metagenomics independently, comprehensively and without bias. The initiative should supply users with exhaustive quantitative data about the performance of methods in all relevant scenarios. It will therefore guide users in the selection and application of methods and in their proper interpretation. Furthermore, it will provide valuable information to developers, allowing them to identify promising directions for their future work. The first CAMI challenge took part in 2015. In the evaluation workshop of the first CAMI challenge at the INI, the challenge results will be analyzed and discussed with participating developer teams. In addition, the focus of future CAMI challenges will be discussed. All talks will be streamed. Interested scientists are encouraged to join.
2240609

Evidence Based Decisions for UK Landscapes
ucs_sms_2834038
http://sms.cam.ac.uk/collection/2834038
Evidence Based Decisions for UK Landscapes  Rural and Urban Land use, Coastal and Inland Waters
Background
Stakeholders involved in the management of, and future planning for, the various landscape domains in the UK have to take into consideration numerous processes, interactions and high levels of complexity. So how can they make better evidence based decisions?
Our landscape is the product of natural resources, environmental processes, and how land is used, according to social, cultural and political drivers. Landscapes are always changing, being shaped by various interactions between geographical, climatic, socioeconomic drivers of land use and the dynamics of ecological systems. We are only now developing the capability and the capacity to provide metrics to better understand these dynamics, and thereby make informed decision making. To move towards a new, holistic decisionmaking framework requires activities that develop a new community from the diverse research base, and expose this to the models currently being used to capture these complexities in order to understand their opportunities and weaknesses, and to expose the current approaches to new mathematical approaches.
Better methodologies need to be developed in order to improve research methods and models. This is critical in helping stakeholders to increase their understanding and more effectively manage and plan for the future of landscapes. Within landscapes, numerous processes operate and interact across different spatial and temporal scales. As well as physical and biogeochemical factors, anthropogenic (human activity) also has a big impact on landscape structures and this makes it extremely challenging to try and understand causal relationships between these structures and processes. Traditional approaches to land use and ecological modelling have tended to fall into two categories – pattern based or process based. However, new modelling approaches are now integrating human behaviour with other processes. This recognises the complex interactions between human decision making and ecological and environmental processes. Additionally, further challenges exist around verification and validation of model performance, particularly for those which seek to make predictions.
New approaches are needed to develop better linkages and integration between existing models, as well as new methodologies for decision making. This two day scoping workshop forms part of a programme of work, supported by the Natural Environment Research Council (NERC) on evidence based decisions for UK landscapes, with a focus on terrestrial land use (rural and urban), coastal and freshwater. The programme of work subsequent to this event is expected to include a funding call later in the year and a one month research programme at the Isaac Newton Institute in July 2019.
Aims and Objectives
The mathematical sciences are of fundamental importance to solving many ongoing problems across numerous scientific, societal and economic areas and never more so than today, where ‘big data’ continues to increase exponentially and uncertainty and risk predominate.
This workshop aimed to investigate new mathematical and statistical modelling techniques which can enable better evidencebased decisions to be made around UK landscapes. These need to be flexible enough to incorporate other models, whilst also taking into account many other highly complex factors across different landscapes. Areas of particular interest included:
Identifying optimal use of land areas for specific purposes
Defining national and regional scenarios to achieve multiple objectives from the management of the landscape
Consideration of the complexity of landscape dynamics and land use across spatial and temporal scales within the UK
Identifying the mathematical challenges.
Current approaches do not sufficiently capture the complex and competing ways we value the benefits from using land, to inform decisions at scales from regional to local that in turn impact on the flow and quality of ecosystem services. Decision making needs to:
Inform on the tradeoffs between the environment, health, wellbeing, and the economy, and
Include social, cultural and heritage consequences of interventions in both the short and long term.
This workshop brought together experts from a number of research disciplines and other key stakeholders to highlight relevant research and approaches to modelling uncertainty. A variety of mathematical areas were explored, including probability, numerical simulations, stochastic modelling, optimisation and uncertainty quantification.
This event was of interest to a range of UK environmental stakeholders and researchers from the mathematical, environmental, geographical, ecological and biological science areas. This included government/public sector, business, as well as organisations involved in urban planning, sea/inland waters and land conservation and management.
2834038

Evolutionary Implications of the COVID19 Vaccination Programme
ucs_sms_3496972
http://sms.cam.ac.uk/collection/3496972
Background
The COVID19 vaccine is currently being rolled out in the UK and globally, but there is a limited supply available. Therefore, countries are having to prioritise which subgroups of the population will receive the vaccine first. For example, in the UK vaccination has been targeted at the older age groups, healthcare workers and those that are at greater risk of needing hospitalisation as a result of contracting COVID19. Such a strategy is focused on reducing disease rather than transmission, since currently the impacts of the vaccine on blocking transmission are still uncertain.
At the same time, the virus is evolving with a number of new more transmissible variants, for example B117 and B1351, emerging in recent months. It is commonly accepted that the use of vaccines can result in novel selective pressure on pathogen populations, often resulting in the emergence of resistant genotypes. Therefore, it is important to consider the evolutionary implications of vaccination programmes. In particular, as more vaccine doses become available it is important to consider the optimal design of vaccination programmes to not only minimise disease or transmission, but also to minimise the risk of the emergence of COVID19 variants that are resistant to the vaccine.
This event will be the first delivered by the Newton Gateway in its key role in the RAMP Continuity Network (a UKRI funded project) to deliver a series of meetings, workshops and virtual study groups that react to key priority areas in the UK’s response to the current pandemic. This event is guided by links with groups such as the JUNIPER consortium and the Isaac Newton Institute Infectious Dynamics of Pandemics research programme to ensure relevance to current UK policy, and will ensure engagement with the wider mathematical modelling and epidemiology communities.
Aims and Objectives
This workshop will focus on the use of quantitative modelling approaches to understand the evolutionary implications of vaccination programmes. Such approaches are key to developing optimal vaccination strategies and understanding which subgroups in society should be prioritised for vaccination against COVD19.
The aim of these 2 afternoon sessions will be to understand the potential implications of different vaccination strategies on the evolutionary dynamics of COVID19. A key goal of this event is to build links between epidemic modellers and the wider modelling community with interests in COVID19, such as withinhost modelling teams – including, but not limited to members of RAMPinitiated projects.
3496972

Factorisation of matrix functions: New techniques and applications
ucs_sms_3043327
http://sms.cam.ac.uk/collection/3043327
The Wiener–Hopf method has been interdisciplinary ever since its inception. It resulted from a collaboration between Norbert Wiener, who worked on stochastic processes, and Eberhard Hopf, who worked on partial differential equations. The Wiener–Hopf technique combines two powerful
ideas: the Fourier transform and complex analysis. The Wiener–Hopf method has enabled us to analytically solve previously intractable integral and partial differential equations. To date, it remains the only known method for solving a wide class of physical problems. There are a numerous new directions of approximate methods which allow to tackle previously unapproachable real life problems.
The aim of this workshop is to share
(i) new tools for the solution of matrix WienerHopf equation
(ii) the generalisations of the WienerHopf method
(iii) the diverse applications of the WienerHopf technique"
3043327

Fermat’s Last Theorem: A celebration 25 years on
ucs_sms_2837393
http://sms.cam.ac.uk/collection/2837393
"I think I'll stop here...."
The Isaac Newton Institute is delighted to announce that on the afternoon of Monday 1 October 2018 it will be hosting an event to celebrate the 25th Anniversary of Sir Andrew Wiles famously announcing at the Institute his proof of Fermat’s Last Theorem.
The afternoon will include:
Technical talks with speakers including Andrew Wiles (Oxford), John Coates (Cambridge) and Jack Thorne (Cambridge);
A presentation to Andrew Wiles;
A wine reception including the opportunity to view art at the Institute.
Timings are given on the Timetable page http://www.newton.ac.uk/event/lfnw01/timetable.
John Coates was an Organiser of the 1993 Lfunctions and arithmetic programme as well as its associated workshop on padic representations, Iwasawa theory and the Tamagawa numbers of motives at which Andrew Wiles presented his historic proof over a series of lectures. Jack Thorne did his PhD at Harvard under the supervision of Andrew Wiles' collaborator Richard Taylor. Most recently he has been interested in using automorphy lifting techniques to establish new cases of the FontaineMazur conjecture.
2837393

Foams and Minimal Surfaces
ucs_sms_1664285
http://sms.cam.ac.uk/collection/1664285
Computational methods have given fresh impetus to the mathematics of minimal surfaces and its applications. In particular the theory of liquid foams, which has its roots in the work of Plateau in the 19th century, has been greatly advanced. The Surface Evolver software developed by Ken Brakke and others has been particularly valuable. The subject remains a fertile ground for interaction between pure and applied mathematicians, physicists and engineers, using mathematical analysis and extensive simulations.
In addition to the further analysis of equilibrium foam structure, physical properties associated with coarsening, drainage, rheology and collapse are actively debated. These are of widespread industrial interest (detergents, foods and beverages, defoaming).
The programme will progress from the theory of minimal surfaces and discrete geometry to a wide range of techniques and applications, and will include related fields (emulsions, biophysics, solid foams).
1664285

Form & Deformation in Art, Toys and Games
ucs_sms_2620801
http://sms.cam.ac.uk/collection/2620801
New mathematical approaches, such as shape analysis and computational anatomy, can be applied to growth and form in a variety of complex living and inanimate systems. Mathematical tools have the capacity to revolutionise a whole range of interdisciplinary problems, from image analysis to medical diagnosis, from study of paintings to mechanical toys and games.
Indeed, mathematical approaches, including those of nonlinear dynamics, chaos theory, fractal analysis, fluid dynamics and fluidstructure interactions, have, in recent decades, been brought to bear on a whole range of cross disciplinary problems, until recently outside the scope of physics: from visual to performing arts and from children’s puzzles to physical aspects of sport.
The emergence of form in art and the properties and role of form in finished artworks includes the mathematical and physical aspects of artistic processes and techniques. These issues are at the interface between science and art. Applications of physics and mathematical analysis to art is still a novel field of research, although a growing number of physicists and applied mathematicians have been studying artmaking, particularly various painting techniques, and art objects themselves.
This knowledge exchange event was delivered by the TGM as part of the Isaac Newton Institute Research Programme on Growth Form and Selforganisation. The Programme coincided with the 100th anniversary of the book by d’Arcy Thompson, whose elegant analysis of shapes of organisms and their mechanical characteristics brought the tools of mathematics and physics to the study of living systems  effectively enlarging the scope of both fields. This workshop therefore brought together mathematicians, biologists and physicists from both the research and industrial communities.
Art Exhibition
Delegates had the opportunity to see an exhibition entitled 'Form in Art  Art of Form' which included works by leading contemporary artists who employ physics phenomena in their artistic processes, engage themes related to science, or in some manner explore form.
Aims and Objectives
Mathematicians and scientists who work on the physical aspects of art, on the artmaking processes, and on the physics of toys, often work individually or in small groups disconnected from one another. This workshop aimed to extend the reach of the Isaac Newton Institute Research Programme, by fostering exchange between different groups of researchers and practitioners and established links between researchers pursuing different diversions and began forming a community.
This event focused on form and deformation in art, toys and games. However, the mathematical approaches which were highlighted also have generic appeal and were relevant to a broader range of industry and application areas, including engineering, healthcare, chemicals, materials, security and analytics.
The Programme included two overview talks by an art historian and a mathematician, followed by a series of more focused presentations organised into two main sessions:
Form in Art
Form in Toys and Games.
These talks highlighted how mathematicians and physicists might think about art and helped to explain some of the links between art and science. The talks included end user presentations from those working in the toy making and gaming and film industries.
It was expected to bring together industrial and academic experts from a diverse set of backgrounds including mathematics, physics, and biology, with those looking at animation art, image processing, computer vision and visual art.
2620801

Fractional differential equations
ucs_sms_3779535
http://sms.cam.ac.uk/collection/3779535
Modelling based on differential equations of fractional order and related heavytailed probability distributions has recently witnessed a surge of interest due to their ability to model complex phenomena. Applications include modelling contamination of groundwater flow, the electrical dynamics of the heart and the design of new materials. Fractional differential equations capture effects going well beyond the range tractable by conventional concepts and tools, and it is increasingly recognised that this framework is on the way of becoming a new paradigm in scientific modelling. This programme sets out to investigate the multiple facets of spacetime fractional dynamics and make significant progress in the description and deep understanding of this new phenomenology.
A common feature of the problems the programme aims to address is spacetime nonlocality. In a mathematical formulation, spatial nonlocality means that the evaluation of the action of an operator on a function at a particular point in space generally depends also on its effect in faraway positions. A typical example is the fractional Laplacian, however, we will consider a whole range of possible nonlocal operators, which generally may have different qualitative behaviours. Temporal nonlocality means that the future evolution depends on its past, which is described in terms of fractional (such as Caputo) timederivatives.
A particular aspect in the attempt to mathematically capture these problems is that several complementary approaches are at hand. A natural framework is offered by integrodifferential equations featuring integral kernels in space and/or time variables, and one path to follow is then an analysis in terms of singular integrals and related objects. Another possibility is a more operatorbased analysis emphasising spectral properties of pseudodifferential operators. A third way is a probabilistic formulation in terms of FeynmanKactype representations, involving random processes with jump discontinuities. One of the main aims of the programme is to explore the interaction of these multiple approaches, and develop a common framework and new methodology.
The programme will focus on the following themes within three workshops: (1) Deterministic and Stochastic Fractional Differential Equations and Jump Processes, (2) Fractional Kinetics, Hydrodynamic Limits and Fractals, (3) Optimal Control in Fractional Dynamics. Within the final two workshops there will also be sessions addressing applications and computational aspects of fractional differential equations. These sessions will cover themes such as physics (transport phenomena, quantum optics), chemistry and biology (chemotaxis, population dynamics/foraging), environmental sciences (groundwater contamination, fractal solute transport), and technology (image reconstruction and signal analysis, financial engineering).
The programme intends to offer to scientists working broadly in the interdisciplinary area of fractional calculus, nonlocal equations, random processes with jumps, and their applications, a platform to interact and communicate their research results in a vibrant research environment. To strengthen intra and interdisciplinary crossfertilisation, these topics will be organised in a way to combine key subjects of research with a double focus, including both theoretical aspects with more applied/computational interests. Participants to the programme and the workshops are expected from six continents, including a significant proportion of early career scientists. We also encourage PhD students/postdoctoral researchers to attend some of the proceeds or outreach activities.
3779535

Free Boundary Problems and Related Topics
ucs_sms_1625716
http://sms.cam.ac.uk/collection/1625716
Free boundary problems are today considered as one of the most important directions in the mainstream of the analysis of partial differential equations (PDEs), with an abundance of applications in various sciences and real world problems. In the last two decades, various new ideas, techniques, and methods have been developed, and new important, challenging problems in physics, engineering, industry, finance, biology, and other areas have arisen.
The topics of this programme are at the forefront of current exciting developments. We realise that there have been few activities on free boundary problems in recent decades in the UK. We strongly believe that a thematic programme at the Newton Institute will have a huge impact on the development of FBPs from all points of view. The programme is directed towards theory, numerics and applications. It will further enhance the interaction between UK mathematicians and top international researchers in this field and strengthen the UK expertise in FBPs.
Read more at www.newton.ac.uk/programmes/FRB/
1625716

Frontiers in analysis of kinetic equations
ucs_sms_3759193
http://sms.cam.ac.uk/collection/3759193
This main objective of this workshop is to address, 10 years exactly after the last semester on kinetic theory organised at the Newton Institute, the state of the art in PDE analysis related to kinetic equations. In particular, the last decade has seen new bridges and fascinating new directions Landau damping and its "fluid" sibling the inviscid damping and their role in longtime stability of persistent structures, scaling limit of kinetic equations and the derivation of fractional diffusive equations at macroscopic level, new developments on the propagation of chaos for meanfield and BoltzmannGrad limits, quantum optimal transport and semiclassical approximation of meanfield transport equations…
The workshop will try to attract prominent speakers in these different directions and will encourage interactions and crosspollination.
3759193

Future Developments in Climate Sea Ice Modelling
ucs_sms_2569953
http://sms.cam.ac.uk/collection/2569953
Background
Observations, theory and numerical modelling strongly indicate a substantial alteration of the Earth’s climate with global average warming in the coming decades. Our understanding of current and future climate is substantially derived from climate models. Climate models solve systems of equations that simulate the circulation and physical evolution of the Earth’s atmosphere, ocean, land surface, and cryosphere. Sea ice, an important component of the cryosphere, provides a partial barrier to exchanges of momentum, heat, and freshwater between the atmosphere and ocean and is a complex composite of ice and brine that exhibits varying structural, thermodynamic and mechanical properties across a range of length and timescales. The last decade’s rapid and substantial reduction of the Arctic sea ice cover has been widely reported and further changes are expected in the coming years. While loss of sea ice will not alter sea level, it does alter the exchanges and feedbacks between the atmosphere and ocean and has a significant impact on the polar regions and global climate through its impact on atmospheric and oceanic circulations.
This knowledge exchange event is delivered by the TGM as part of the Isaac Newton Institute Research Programme on the Mathematics of Sea Ice Phenomena.
It specifically addresses climate model representation of sea ice and will also investigate fundamental and applied issues in mathematical modelling of sea ice. In particular, it will seek to identify future priorities for climate sea ice model development.
Aims and Objectives
To identify priorities for future climate sea ice model development, we will discuss the following questions:
What do climate models need sea ice for?
A topdown, system level view of what sea ice models should produce from the perspective of a climate modeller.
What sea ice physics is missing from models?
A bottomup view of what is missing from current sea ice models from the perspective of a sea ice scientist.
What modelling approaches can be used to address the complexity of sea ice and the needs of climate models?
This workshop will enable the presentation and discussion of different views and modelling approaches, as well as issues relevant to adequate simulation of sea ice from the perspective of the mathematical modeller. It will be of interest and relevance to those working on climate models, specifically for sea ice.
2569953

Genomic, Evolutionary and Epidemiological Approaches for Pandemics
ucs_sms_3842904
http://sms.cam.ac.uk/collection/3842904
Background
Genomics and evolutionary biology now provide major tools used in the surveillance and study of infectious diseases. However, to a large extent, the communities involved in genomic surveillance and traditional epidemiological modelling speak different languages, and this limits their interaction.
Over the course of the SARSCoV2 pandemic, tools from both fields have been applied extensively in tracking both the original virus and the multiple mutants that have arisen. Genetics and evolutionary biology have been particularly important in the latter case, as the evolution of pathogens and their hosts has been an active field of study in these disciplines for many years. Despite this long history, this pandemic has revealed that our ability to predict the evolutionary trajectories of pathogens in the sort of complex epidemiological situations observed in the real world is limited, especially when they are adapting to a novel host. However, phylogenetic tools have allowed important conclusions about the spread of specific mutants to be made retrospectively, and provided independent validation of estimates made with traditional epidemic modelling tools on a similar timescale.
The integration of phylogenetic and epidemiological modelling tools can go much further than simply allowing validation of each other's estimates. A body of work has built up explicitly merging the two approaches, allowing epidemiological and phylogenetic models to be implemented together to coestimate important parameters of epidemics. Further communication between epidemiological modellers and computational biologists would allow both the further development of these methods and the expansion of their use.
This virtual event is guided by links with the JUNIPER Consortium and is delivered by the RAMP Continuity Network, the followon to the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative. It will bring together modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on COVID19.
Aims and Objectives
This oneday virtual workshop aims to facilitate communication between epidemiological modellers and computational and evolutionary biologists. It will do this by giving an overview of important topics in pathogen evolution and adaptation, as well as discussing tools available to merge epidemiological and genomic data and providing case studies of their use in the infectious disease research.
Participants will have the opportunity to raise questions following each presentation. There will also be a facilitated Q&A Discussion at the end of the day where individuals will have the opportunity to table further questions and share thinking.
3842904

Gravity, Twistors and Amplitudes
ucs_sms_2273873
http://sms.cam.ac.uk/collection/2273873
Over the last ten years, tremendous progress has been made in understanding scattering amplitudes in YangMills and gravity theories. On the technical side, new explicit formulae for general nparticle scattering amplitudes have been discovered that exhibit remarkable new mathematical structures. On the conceptual side, a new proof of GR and YangMills uniqueness has been obtained, in which the basic cubic interaction is fixed (onshell) from simple scaling considerations, and all other amplitudes are built from the basic cubic ones by the use of recursion relations. Thus, from this perspective, gravity and YangMills theories are the simplest nontrivial quantum field theories. Furthermore, there are remarkable relations between gravity and the `square' of YangMills arising from colourkinematic duality. Unfortunately, at present we only see manifestations of this simplicity in the perturbative structure of the field equations. An open problem is to understand these structures nonperturbatively, arising from hidden structures also in fully nonlinear gravity and YangMills theories.
2273873

GrothendieckTeichmüller Groups, Deformation and Operads
ucs_sms_1387512
http://sms.cam.ac.uk/collection/1387512
GrothendieckTeichmüller theory goes back to A. Grothendieck's celebrated Esquisse d'un programme. In 1991, V. Drinfel'd formally introduced two GrothendieckTeichmüller groups, the former one related to the absolute Galois group and the latter one related to the deformation theory of a certain algebraic structure (braided quasiHopf algebra). Introduced in algebraic topology 40 years ago, the notion of operad has enjoyed a renaissance in the 90's under the work of M. Kontsevich in deformation theory. Two proofs of the deformation quantization of Poisson manifolds, one by himself as well as one by D. Tamarkin, led M. Kontsevich to conjecture an action of a GrothendieckTeichmüller group on such deformation quantizations, thereby drawing a precise relationship between the two themes.
Read more at: http://www.newton.ac.uk/programmes/GDO/
1387512

Groups, representations and applications: new perspectives
ucs_sms_3136595
http://sms.cam.ac.uk/collection/3136595
Group Theory is essentially the theory of symmetry for mathematical and physical systems, and underpins much of modern mathematics. Born more than two centuries ago in the work of Evariste Galois, it achieved a major milestone when the Classification of Finite Simple Groups was completed. Since then, important and deep connections to areas as varied as topology, algebraic geometry, Lie theory, homological algebra, and mathematical physics, have been discovered and exploited. Still, the area abounds with basic problems and conjectures, some of which have been open for decades.
Recent breakthroughs hold out the prospect of finally solving some venerable open problems. In turn, recent results in group and representation theory have led to substantial progress in a vast number of applications in Lie theory, number theory, algebraic geometry, combinatorics and semigroup theory, to name a few.
All this wealth of new results and directions will be in the focus of the programme, which includes the following themes:
 Reductive groups: Representations, subgroup structure, and cohomology
 Localglobal conjectures in representation theory of finite groups
 Fusion systems, local group theory, and revision projects
 Modern algorithmic and computational methods
 Connections with other areas of mathematics
There will be five oneweek workshops, with the first one to provide participants with an overview of the programme's themes and how they fit together. The programme will bring together the leading experts in group and representation theory, on the one hand, and from several key other parts of mathematics on the other, with the aim of solving some of the main open problems, and taking the many connections between group theory and other areas of mathematics to the next level.
3136595

Growth form and selforganisation
ucs_sms_2554151
http://sms.cam.ac.uk/collection/2554151
This programme, planned on the 100th anniversary of On Growth and Form by D’Arcy Thompson, will endeavour to bring various contemporary strands of research related to shape selection, deformations, and selforganisation into focus. The aim is to stimulate new collaborations between mathematicians, biologists, physicists, and other scholars or creators whose work concerns or employs evolution of form, broadly understood. It will thus provide opportunities for crosspollination of ideas within and across disciplines on various aspects of shape dynamics in diverse contexts and at diverse scales.
Topics include scaling laws in biology, morphogenesis and growth, collective behaviour, propulsion mechanisms, aggregation and selforganisation, folding, stretching, mixing, topological fluid dynamics, and artificial networks. New mathematical approaches, such as shape analysis and computational anatomy, will be emphasized and applied to growth and form of a variety of complex living and inanimate systems. Mathematical tools will also be brought to bear on a whole range of interdisciplinary problems: from image analysis to medical diagnosis, study of paintings, and mechanical toys.
The four principal areas of the programme are:
Form and deformation in solid and fluid mechanics
Growth, form, and selforganisation in living systems
Shape analysis and computational anatomy
Form in art, toys, and games
2554151

Gyrokinetics in Laboratory and Astrophysical Plasmas
ucs_sms_865670
http://sms.cam.ac.uk/collection/865670
Perhaps the greatest challenge in plasma science is to understand the multiscale interaction between smallscale fluctuations and largescale plasma dynamics. This is crucial both in fundamental astrophysical and space physics research (e.g., turbulence in the solar wind) and in more practical terrestrial contexts (e.g., the performance of the international fusion reactor, ITER, will be limited by the transport caused by smallscale fluctuations). Multiscale plasma dynamics also represent a formidable and fascinating mathematical challenge, as new analytical and numerical methods have to be developed in order for major breakthroughs to become possible.
Read more at: http://www.newton.ac.uk/programmes/GYP/
865670

Higher structures in homotopy theory
ucs_sms_2781281
http://sms.cam.ac.uk/collection/2781281
Workshop
2nd July 2018 to 6th July 2018
Organisers:
Stefan Schwede Rheinische FriedrichWilhelmsUniversität Bonn
Clark Barwick University of Edinburgh
Julie Bergner University of Virginia
Ieke Moerdijk Universiteit Utrecht
Workshop Theme
Homotopy theory has covered a long distance since its origins, the classification of spaces up to homotopy equivalence. Over the years, various kinds of mathematical structures have been investigated from a homotopical perspective, such as equivariant spaces, rings, C^*algebras, or varieties. Many different approaches of how to formalize what a “homotopy theory” is were proposed, the most prominent ones being the notions of model category and ∞category.
The relationship between the different ways to formalize a homotopy theory is now well understood; indeed, for comparing different concepts of homotopy theories, one often wants to consider all of them together as another homotopy theory, i.e., a ‘homotopy theory of homotopy theories’. Somewhat surprisingly, most of the concepts organize themselves into a Quillen model category, and the various approaches are Quillen equivalent. After these individual comparison results, Töen was even able to axiomatically characterize a homotopy theory of homotopy theories.
The homotopy theory of homotopy theories is only the first step in a hierarchy of interesting structures, namely the homotopy theoretic approach to higher categories. From this broader perspective, homotopy theories are just (∞, 1)categories, where the ∞ indatices a structure with higher morphisms of all levels, and the 1 refers to the fact that all 1morphisms and higher morphisms are weakly invertible. There are now ways to give rigorous meaning to the notion of (∞, n)categories i.e., where only higher morphisms in level n and above are invertible. Having a rigorous model category of (∞,n)categories is a cornerstone for the modern approach to topological field theory, thereby unifying categorical considerations with those of homotopy and manifold theory.
This workshop consists of lecture series as well as individual research talks. The introductory series will explain some of the key methods relevant to many parts of the overarching program; they are intended to invite graduate students and postdocs into the field, as well as to strengthen the common ground of the program participants. The individual talks will inform us about recent developments about higher structures in homotopy theory.
2781281

Highly Oscillatory Problems: Computation, Theory and Application
ucs_sms_34
http://sms.cam.ac.uk/collection/34
High oscillation pervades a very wide range of applications: electromagnetics, fluid dynamics, molecular modelling, quantum chemistry, computerised tomography, plasma transport, celestial mechanics, medical imaging, signal processing. It has been addressed by a wide range of mathematical techniques, inter alia from asymptotic theory, harmonic analysis, theory of dynamical systems, theory of integrable systems and differential geometry. The computation of highly oscillatory problems spawned a large number of different numerical approaches and algorithms. The purpose of this programme is to foster research into different aspects of high oscillation – the theoretical, the computational and the applied – from a united standpoint and to promote the synergy implicit in an interdisciplinary activity.
Read more at: http://www.newton.ac.uk/programmes/HOP/
34

Homology theories in low dimensional topology
ucs_sms_2409838
http://sms.cam.ac.uk/collection/2409838
The subject of homology theories in lowdimensional topology dates back to the work of Floer, and gained new breadth and vigour with the introduction of Khovanov homology fifteen years ago. Since then, these theories have had a farreaching impact both in topology and more widely with analysts, algebraists, geometers, and physicists all contributing to and benefiting from their development. This programme will follow three broad themes:
The meaning of Floer homology: The programme will pursue and uncover intimate connections of Floer homology with underlying topological data. For example: the connection of Floer homology with the fundamental group by way of orderable groups, foliations, and related structures.
The meaning of quantum knot homologies: In comparison to Floer homology, the geometrical meaning of quantum knot homologies such as Khovanov homology remains relatively obscure. One natural place to look for such meaning is in physics, which has played an important role in this field ever since Witten interpreted the Jones polynomial in terms of ChernSimons theory.
Quantum 3manifold invariants: We hope to make significant progress towards, for example, lifting the numerical ReshetikhinTuraev 3manifold invariants to homological invariants. This should then provide a quantum counterpart to analytic invariants of smooth 4manifolds.
Tying these three themes together will be a central focus of the programme. It has become apparent in recent years that one should think of quantum invariants as firstorder approximations to Floer invariants. The programme aims to make relationships such as these more precise and general.
Figure from Ken Baker's Sketches of Topology blog
2409838

ICAMP 2013 : Summer School on Liquid Crystals
ucs_sms_1512626
http://sms.cam.ac.uk/collection/1512626
The ICAMP'13 school took the form of a summit, bringing together prominent scientists as well as students and postdoctoral fellows. It provided education for young scientists working in the fields of liquid crystal materials science, optics, photonics, mathematics, biophysics, nanoscience, and related fields. The goal was to prepare the participants for research at the frontiers of science and technology by providing an interdisciplinary expert training not easily available within the traditional system of graduate education and postdoctoral apprenticeship. The meeting also explored current state and emerging new research frontiers. The focus was on recent advances at the interface between liquid crystal physics and optics that promise to open up conceptually novel directions of research. Participants working at the forefronts of materials science, nanoscience, and optics discussed the emerging uses of light for control and study of liquid crystal materials as well as the advances in the use of these materials to control light. By bringing together both prominent & junior scientists to Cambridge, ICAMP'13 school also allowed them to combine advanced education with learning about different cultures worldwide and history of science.
Read more at: http://icamp.colorado.edu/icamp2013/
1512626

Industrial and Clinical Application of Cardiac Simulations: Quantifying Uncertainty in Model Predictions
ucs_sms_2997031
http://sms.cam.ac.uk/collection/2997031
Background
The function of the heart can be simulated using multiscale computational models: ranging from representations of electrical activation and force generation in a single cell; up to anatomical models of an individual patient’s whole heart and cardiovascular system.
There are a range of industrial and clinical applications of cardiac simulations that have begun to be tested and used in the last few years including assessing the safety of new drugs and providing patientspecific guidance for clinical procedures. A major obstacle to progress is that the present generation of cardiac simulations do not account fully for all the uncertainties and variabilities that we know to be present. Our uncertainties include geometry from incomplete medical images, and properties taken from the noisy data that are typically available. These lead to uncertainties around the inputs, meshes, parameters, and even equations/structure, that we use within the models. Variability between individual cells, tissues, organs and the bodies that they lie within are also considerable and accounting for this may be crucial in predicting clinical outcomes.
Aims and Objectives
This knowledge exchange event by the Newton Gateway to Mathematics takes place as part of the INI Research Programme on the Fickle Heart – within the workshop on Uncertainty Quantification for Cardiovascular Simulations. This particular event will open up the discussion to a wider audience, including those working in biotechnology, healthcare, pharmaceuticals and the public sector.
The introductory talks will highlight the key issues raised during the Research Programme and suggest some next steps. A number of enduser talks from industry and the public sector will describe how organisations manage the uncertainty of modelling and the challenges they face.
The main aims of the day will be to:
Discuss the latest developments in considering uncertainty and variability in cardiac simulation.
Understand challenges faced by industry and the healthcare sector in their applications of cardiac modelling.
Form an interdisciplinary community of researchers interested in the mathematics of uncertainty quantification, the creation and solution of biophysical models of the heart and cardiovascular system, and their translation into industrial and clinical applications.
2997031

Industrial Applications of Complex Analysis
ucs_sms_3090450
http://sms.cam.ac.uk/collection/3090450
Background
Complex analysis is a branch of mathematics that studies analytical properties of functions of complex variables. It lies on the intersection of several areas of mathematics, both pure and applied, and has important connections to asymptotic, harmonic and numerical analysis. Techniques based on complex variables are very powerful, with a large number of applications to the solution of physical problems.
The discipline covers a wide range of different techniques including solution methods to freeboundary problems such as HeleShaw and Stokes flow, conformal mappings, Fourier and other transform methods and RiemannHilbert problems. In practice many problems that may be difficult to solve in the real domain can be more easily solved when transformed into complex variables due to a number of special properties of the complex domain.
Importantly, there has been a surge of activity in the advancement of complex analysis methods in recent years, driven by applications in engineering, biology and medicine. The application of these methods to real world problems include propagation of acoustic waves relevant for the design of jet engines, development of boundaryintegral techniques useful for solution of many problems arising in solid and fluid mechanics as well as conformal geometry in imaging, shape analysis and computer vision.
This knowledge exchange day is part of a four month research programme at the Isaac Newton Institute on Complex Analysis: techniques applications and computations. It forms day three of the week long workshop Complex analysis in mathematical physics and applications. The research programme brings together researchers from mathematics, physics and engineering communities, whose research shares a common theme of using complex analysis to attack realworld problems.
Aims and Objectives
This knowledge exchange event will showcase the state of the art application of complex analysis methods to solve industrial driven problems, as well as where mathematical advances in this area are most needed. Another key aim is to identify techniques most commonly used by endusers and where further improvements would be most beneficial. This will help focus the areas of investigation undertaken in the remainder of the research programme.
The programme for the day reflects the breadth of application areas where complex analysis methods are important and will include talks representing both academic research and enduser perspectives from a range of different industrial areas. These will also highlight recent how complex analysis methods have the potential to tackle challenging problems in a number of areas including understanding of aeroacoustics, medical imaging methods, tissue engineering approaches and radar signal processing. Furthermore, the increasing difficulty of many problems in these fields will help inform the agenda for complex analysis research.
The four sessions that will be covered are:
Acoustics
Continuum mechanics
Life sciences
Radar
This event will bring together mathematicians and scientists working at the forefront of complex variable theory and their applications, with end users from industry to further investigate opportunities for the use of complex variable methods in the solution of applied problems.
3090450

Infectious Disease Dynamics
ucs_sms_1539399
http://sms.cam.ac.uk/collection/1539399
On 1 January 2013, it will be twenty years since Epidemic Models started as a 6month programme in the first year of the Isaac Newton Institute for Mathematical Sciences. Since then, the field has grown enormously, in topics addressed, methods and data available (e.g. genetics/genomics, immunological data, social, contact, spatial, and movement data were hardly available at the time). Apart from these advances, there has also been an increase in the need for these approaches because we have seen the emergence and reemergence of infectious agents worldwide, and the complexity and nonlinearity of infection dynamics, as well as effects of prevention and control, are such that mathematical and statistical analysis is essential for insight and prediction, now more than ever before.
Read more at http://www.newton.ac.uk/programmes/IDD/.
Image from The New England Journal of Medicine, Gardy, 'WholeGenome Sequencing and SocialNetwork Analysis of a Tuberculosis Outbreak', Volume 364, pp 7309. Copyright ©2011 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.
1539399

Infectious Dynamics of Pandemics: Mathematical and statistical challenges in understanding the dynamics of infectious disease pandemics
ucs_sms_3216788
http://sms.cam.ac.uk/collection/3216788
Organisers:
Deirdre Hollingsworth University of Oxford
Julia Gog University of Cambridge
Hans Heesterbeek Universiteit Utrecht
Valerie Isham University College London, University of Warwick
Denis Mollison HeriotWatt University
Phil O'Neill University of Nottingham
Sylvia Richardson University of Cambridge
Nigel Shadbolt University of Oxford
Caroline Trotter University of Cambridge
Alan Wilson The Alan Turing Institute
Due to current events, this is a virtualised programme
Programme Description
Mathematical modelling has played an unprecedented role in informing public health policy on the control of the current COVID19 pandemic. Infectious disease modelling groups in the UK and globally have necessarily been working in ‘response’ mode to provide realtime modelling of the pandemic as it unfolds. However, this has left limited time for longerterm thinking about the challenges of understanding the dynamics of this particular pandemic. There is therefore an additional need for experts to discuss, explore and analyse surrounding issues including model assumptions, strategies for surveillance, contact tracing, use of diagnostics, and social distancing. A key aim of this programme is to address this need for longerterm thinking.
This programme will support the activities of the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) programme through additional capacity to provide rapid assessment of strategies of immediate policy relevance. Furthermore, programme participants will provide critical assessment of extant models, considering alternatives and identifying improvements. This is vital to avoid duplication of effort and the potential for analyses which misinterpret key aspects of the epidemiology or make incorrect assumptions regarding underlying data. Finally, this programme will provide the space for considered, collaborative thinking, providing new ideas and directions, forging novel interdisciplinary links as well as reflecting on lessons learned for future pandemics with regard to planning, prevention and control.
Through a range of virtual events this programme will bring together researchers from a broad range of disciplines, from applied epidemiology to fundamental mathematics. Events will include virtual study groups and webinars. It is hoped that this programme will provide a community of researchers to support the mathematical modelling work to address this current pandemic globally.
Workshops
Details of Workshops 1 and 2 are given below. Details for subsequent workshops will be posted in due course.
Workshop 1: Models for an exit strategy, 1115 May
Following the successful reduction in transmission in many countries, questions of how and when to lift interventions are being asked. In this workshop we will address the models and underlying assumptions which would be used to inform these discussion by evaluating assumptions underlying possible exit strategies. This will include measurement and modelling of contacts, immunity, surveillance, and transmission route, and will include participants from both infectious disease modelling and other fields. This workshop will branch out into a number of different work streams over the following weeks.
Models old and new, 1822 May
This workshop will examine, compare and discuss the approaches being currently used for modelling the pandemic with potential new approaches. Participants from outside the traditional epidemiological modelling field can bring experience of modelling, for example, behaviour, movement and social structure, as well as of computational optimisation and data visualisation.
3216788

Inference for ChangePoint and Related Processes
ucs_sms_1625718
http://sms.cam.ac.uk/collection/1625718
In many applications data is collected over time or can be ordered with respect to some other criteria (e.g. position along a chromosome). Often the statistical properties, such as mean or variance, of the data will change along data. This feature of data is known as nonstationarity. An important and challenging problem is to be able to model and infer how these properties change. Examples occur in environmental applications (e.g. detecting changes in ecological systems due to climatic conditions crossing some critical thresholds), signal processing (e.g. structural analysis of EEG signals), epidemiology (e.g. early detection of hospital infections from changes in patient’s antibody levels), bioinformatics (e.g. detecting changes in copy number variation), and finance (e.g. changing volatility). As technology advances, and ever larger and complex data are collected, the need to model changes in the statistical properties of the data, and the difficulty of making inference for these models increases.
Read more at www.newton.ac.uk/programmes/ICP/
1625718

INI supports the JUNIPER consortium
ucs_sms_3466314
http://sms.cam.ac.uk/collection/3466314
Background
Since the beginning of the COVID19 pandemic in early 2020, mathematical and statistical modelling have been used to provide estimates of the epidemic in the UK and to make short and longterm predictions on interventions. The teams of epidemiological modellers and statisticians in the JUNIPER consortium represent a core of committed and experienced research groups that have been generating predictions, forecasts and insights feeding into the Scientific Pandemic Influenza Group on Modelling (SPIM) and the Scientific Advisory Group for Emergencies (SAGE), both of whom advise the UK government on scientific matters relating to the UK’s response to the pandemic.
JUNIPER consortium members continue to respond to rapid requests from the UK government via SPIM and SAGE, including providing weekly forecast of the reproductive number R and growth rate in the UK and predictions of the effect on spread of given interventions. Furthermore, as the epidemic goes through distinct phases, the research teams are proactively developing novel methodology and analysis as well as horizon scan the impact of new scientific findings and how this will impact on current and future modelling.
JUNIPER consortium will embed scientific activities within an open and collaborative framework, including considerable public outreach so that scientific assumptions and findings are effectively communicated. Our consortium will be outwardfacing and inclusive, helping to add value to a range of existing and new COVID19 activities. They aim to build national capacity and also contribute to training the next generation of applied epidemiological modellers.
3466314

Interactions between Dynamics of Group Actions and Number Theory
ucs_sms_1734729
http://sms.cam.ac.uk/collection/1734729
In the last decade there have been several important breakthroughs in Number Theory and Diophantine Geometry, where progress on longstanding open problems has been achieved by utilising ideas originated in the theory of dynamical systems on homogeneous spaces. Dynamical systems techniques are applicable to a wide range of numbertheoretic objects that have many symmetries. In particular:
various question in Diophantine approximation have been studied using recurrence properties of flows on the space of unimodular lattices
diagonal flows have played an important role in recent advances on quantum chaos and in the proof of the quantum unique ergodicity conjecture for arithmetic surfaces
flows on homogeneous spaces of nilpotent groups have been used to produce new estimates on exponential sums and to study prime solutions of systems of linear equations
the distribution of periodic orbits is connected to behaviour of period integrals of automorphic forms and to the problem of establishing subconvexity bounds for Lfunctions
The aim of this programme is to bring together researchers working in Number Theory and Homogeneous Dynamics to discuss the recent developments and open problems that lie at the crossroads of these fields and to encourage more interaction among people working in these diverse areas.
1734729

International conference on computability, complexity and randomness
ucs_sms_3936839
http://sms.cam.ac.uk/collection/3936839
In 2012, the Newton Institute hosted a highprofile programme Syntax and Semantics: A Legacy of Alan Turing, which was a major component of the worldwide Alan Turing Year celebrations. The capstone workshop of the Syntax and Semantics programme was the 7th Conference on computability, Complexity and Randomness. This followup workshop serves as the 15th Conference on Computability, Complexity and Randomness.
Computability, Complexity and Randomness is a series of conferences devoted generally to the mathematics of computation and complexity, but tends to primarily focus on algorithmic randomness/algorithmic information theory and its impact on mathematics. Algorithmic randomness is the part of mathematics devoted to ascribing meaning to the randomness of individual strings and infinite sequences. For example, we give mathematical meaning to the intuition that one would more readily believe that the string 01101101001101011 was produced via the flips of a fair coin than one would of the string 00000000000000000. The core idea is that a sequence is algorithmically random if it passes all computational randomness tests, and hence if a computational observer cannot distinguish its behaviour in some process from the expected behaviour.
There are several historical approaches to algorithmic randomness, such as computable martingales, Kolmogorov complexity and MartinLoff of randomness. Algorithmic randomness is also related to classical concepts, such as entropy (in the senses of Shannon and Boltzmann). The mathematics of this area is really quite deep. The kinds of questions include: How do we calibrate levels of randomness? Can we amplify weak random sources? Is randomness a provable computational resource? What kinds of power do random sources give us? And so on. Tools from this area can be used in many areas of mathematics and computer science, including the expected behaviour of algorithms, computational biology, ergodic theory, geometric measure theory, number theory and normality. The theme of the conference is algorithmic randomness and related topics in computability, complexity and logic, such as Kolmogorov complexity, computational complexity and reverse mathematics.
3936839

Inverse Problems
ucs_sms_1158966
http://sms.cam.ac.uk/collection/1158966
Many important real world problems give rise to an Inverse problem (IP). These include medical imaging, nondestructive testing, oil and gas exploration, landmine detection and process control. For example, in the exploration for oil and gas, one needs to assess the structure of the interior of the earth from observations made at the surface. Typically, an explosion is created and the resulting shockwaves together with their reflections are used to build a model of the structure of the earth. In magnetoencephalography one needs to determine the electric current in the neurones from the measurement of the magnetic field outside the head. In the field of medical imaging IP forms an important tool in diagnostic investigations. For example, PET and SPECT are two modern imaging techniques whose success is dependent on solving IPs.
Read more at: http://www.newton.ac.uk/programmes/INV/
1158966

Inverse Problems Network Meeting 2
ucs_sms_2615579
http://sms.cam.ac.uk/collection/2615579
This is the timetable for the meeting held from Thursday, 23rd November 2017 to Friday, 24th November 2017 in Isaac Newton Institute, Cambridge.
2615579

Isaac Newton Institute  Special Events
ucs_sms_2323475
http://sms.cam.ac.uk/collection/2323475
A video collection of special events at the Isaac Newton Institute for Mathematical Sciences
2323475

JUNIPER Research Meeting
ucs_sms_3436373
http://sms.cam.ac.uk/collection/3436373
Workshop
23rd February 2021
Organisers:
Ciara Dangerfield Isaac Newton Institute
JUNIPER Research Meeting
JUNIPER (Joint UNIversities Pandemic and Epidemiological Research) is a UKRI funded consortium of epidemiology modelling groups from seven universities:Bristol, Cambridge, Exeter, Lancaster, Manchester, Oxford and Warwick. The teams of epidemiological modellers and statisticians in the JUNIPER consortium represent a core of committed and experienced research groups that have been generating predictions, forecasts and insights feeding into the Scientific Pandemic Influenza Group on Modelling (SPIM) and the Scientific Advisory Group for Emergencies (SAGE), both of whom advise the UK government on scientific matters relating to the UK’s response to the pandemic.
This meeting will provide an introduction to who JUNIPER are, the key goals of the consortium and the current COVID19 related research activities being undertaken by consortium members. The lead academics from each university will also identify research areas of immediate priority to support the scientific advice on the UK government's pandemic response. Topics covered include vaccination and transmission within structured environments.
This meeting is the first in a series of JUNIPER research meetings over the coming 18 months. A key goal of the consortium is to be outwardfacing and inclusive. These research meetings are a major part of the consortium's engagement with the wider epidemiological and mathematical research communities. There will therefore be time for discussion within this halfday meeting and it is hoped that the talks will spark lively discussions and potentially future collaborations.
Find out more about JUNIPER consortium including the current membership here.
This event will be held virtually at 09:0012:50 (GMT). Please note that while this event is free to attend, registration has now closed but you can watch the meeting online here.
3436373

Ktheory, algebraic cycles and motivic homotopy theory
ucs_sms_3140191
http://sms.cam.ac.uk/collection/3140191
The programme will focus on the areas of Algebraic Ktheory, Algebraic Cycles and Motivic Homotopy Theory. These are fields at the heart of studying algebraic varieties from a cohomological point of view, which have applications to several other fields like Arithmetic Geometry, Hodge theory and Mathematical Physics.
It was in the 1960s that Grothendieck first observed that the various cohomology theories for algebraic varieties shared common properties, which led him to explain the underlying kinship of such cohomology theories in terms of a universal motivic cohomology theory of algebraic varieties. The theory of Algebraic Cycles, Higher Algebraic Ktheory, and Motivic Homotopy Theory are modern versions of Grothendieck's legacy. In recent years it has seen some spectacular developments, on which we want to build further.
The programme will also specifically explore the connections between the following areas:
Algebraic Ktheory, Motivic Cohomology, and Motivic Homotopy Theory;
Hodge theory, Periods, Regulators, and Arithmetic Geometry;
Mathematical Physics.
For this, we shall bring together mathematicians working on different aspects of this broad area for extended periods of time, promoting exchange of ideas and stimulating further progress.
During the programme there will be four workshops. At the very beginning, there will be a workshop aimed at giving a younger generation of mathematicians an overview of and introduction to this interesting, but broad area. Later there will be a workshop for each of the three areas listed above, aimed at the latest developments and applications of that area.
3140191

Keynote Seminars
ucs_sms_1084074
http://sms.cam.ac.uk/collection/1084074
1084074

Launch Event of the Cambridge Mathematics of Information in Healthcare (CMIH)
ucs_sms_3521526
http://sms.cam.ac.uk/collection/3521526
Tuesday 4th May 2021 to Wednesday 5th May 2021
Background
The EPSRC Cambridge Mathematics of Information in Healthcare (CMIH) Hub was launched in 2020. It focuses on some of the most challenging public health problems of our time, including Cancer, Cardiovascular Disease and Dementia. There is a core mathematical component that is common to data challenges across these clinical disciplines, which the Hub will evaluate and address through its interdisciplinary collaborations. The overarching objective is to develop data analytics algorithms and provide the associated theory that is directly linked to the requirements in the clinic for healthcare decision making.
Aims and Objectives
This was the first external event of the CMIH Hub and aimed to bring together those working in mathematical healthcare data analytics across the UK, including academic, clinical, and industrial users with mathematicians working in similar areas.
The event included talks that highlighted open challenges and successes from CMIH Hub researchers and presented other potential collaborative opportunities, as well as projects being developed elsewhere related to healthcare data analytics.
Talks focused on the key theme of the CMIH Hub, which is the development of robust and clinical applicable algorithms for analysing healthcare data in an integrated fashion. In addition, there were introductory talks from partner EPSRC Hubs for Mathematical Sciences in Healthcare.
This event brought together researchers from mathematics, statistics, computer science and medicine, with clinicians and relevant industrial stakeholders.
The Programme for this past event is available here.
3521526

Living Proof  the Isaac Newton Institute podcast
ucs_sms_2936827
http://sms.cam.ac.uk/collection/2936827
The Isaac Newton Institute is the world's foremost mathematical research centre. Living Proof aims to highlight the diverse people and interconnected topics linked to its many activities. Interviewees range from visiting academics and lecturers to mathematicians, other scientists, musicians, artists, students, and prominent figures within the University of Cambridge and beyond. The podcast typically involves mathematical themes, but is specifically aimed at a general audience. The focus is on the subjects being interviewed and the social stories they have to tell, not just on the significance and details of the research they may be undertaking. We hope there is interest and inspiration here for everyone.
 The Isaac Newton Institute for Mathematical Sciences (UK) is an international research centre based in Cambridge, UK. A part of the University of Cambridge, it has been hosting research programmes on mathematical themes since July 1992.
2936827

LMS  Spitalfields Series
ucs_sms_55
http://sms.cam.ac.uk/collection/55
The Isaac Newton Institute in Cambridge, the Mathematics Research Centre in Warwick, the International Centre for Mathematical Sciences in Edinburgh, and, from time to time, other Mathematics Departments, hold longterm meetings or symposia on specialist topics, which are attended by eminent mathematicians from overseas. The London Mathematical Society thinks that it is important for recent developments in these specialist topics to be made known to the general mathematical community, and, in particular, to research students. It therefore provides funds to the organisers of these meetings so that they can provide a day of survey lectures, accessible to a general mathematical audience.
These days are called Spitalfields Days, in honour of the Spitalfields Mathematical Society, a precursor of the London Mathematical Society which flourished from 1717 to 1845.
55

LMS Invited Lectures on the Mathematics of Deep Learning
ucs_sms_3831544
http://sms.cam.ac.uk/collection/3831544
Monday 28th February 2022 to Friday 4th March 2022
Background
This workshop featured an introductory lecture series across the week, by Professor Gitta Kutyniok (LMU, Munich) on the mathematics of deep learning. Four accompanying lectures have also been given.
Neural networks were originally introduced in 1943 by McCulloch and Pitts as an approach to develop learning algorithms by mimicking the human brain. The key goal at that time was the introduction of a theory of artificial intelligence. However, the limited amount of data and the lack of highperformance computers made the training of deep neural networks, (networks with many layers), unfeasible.
Today, massive amounts of training data are available complemented by a tremendously increased computing power, allowing for the first time the application of deep learning algorithms. It is for this reason that deep neural networks have recently seen an impressive comeback. Spectacular applications of deep learning are AlphaGo, which for the first time enabled a computer to beat the top world players in the game Go  a game by far more complex than chess, or the speech recognition systems available on each smartphone these days.
We currently witness how algorithms based on deep neural networks are used in numerous aspects of the public sector such as being used for prescreening job applications or revolutionizing the healthcare industry. In fact, the U.S. Food and Drug Administration (FDA) has already approved the marketing of the first medical device for detecting diabetic retinopathy which is based on such methodologies.
Aims and Objectives
The workshop aimed to provide a mathematical foundation of deep learning by an introduction to the main mathematical questions and concepts of deep neural networks and their training within two realms:
Theoretical foundations of deep learning independent of a particular application
Theoretical analysis of the potential and the limitations of deep learning for mathematical methodologies, in particular, for inverse problems and partial differential equations.
The programme featured 2 lectures each day as well as the opportunity for discussion and networking. A poster session also took place.
3831544

LMS Women in Maths Days 2018
ucs_sms_2742320
http://sms.cam.ac.uk/collection/2742320
The LMS Women in Mathematics Day is an annual event organised by the London Mathematical Society. This year it will be replaced by a two day event on Monday 30 April and Tuesday 1 May, to be held at the Isaac Newton Institute in Cambridge.
This inclusive event is open to all mathematicians independent of gender and stage of career. Indeed the sessions on Implicit Bias and LMS Benchmarking should be particularly useful for all HoDs and senior mathematicians whilst the session on interview skills will be more suitable for early career researchers.
Sessions will include talks by women mathematicians at different career stages. There will be a number of practical sessions including a session on Implicit Bias, on the LMS Benchmarking, and on the IoP Project JUNO. In addition there we be a session on interviewing for a first academic position. The event provides an opportunity to meet and talk with women who are active and successful in their mathematical career.
Speakers include Masoumeh Dashti (Sussex); Nilanjana Datta (Cambridge); Juliet Foster (Cambridge); Val Gibson (Cambridge); Ruth Gregory (Durham); Rebecca Hoyle (Southampton); Eugenie Hunsicker (Loughborough); Catherine Powell (Manchester); Beth Romano (Cambridge); Colva RoneyDougal (St Andrews); Claudia Schillings (Mannheim); Anitha Thillaisundaram (Lincoln); Julia Wolf (Bristol); Sarah Zerbes (UCL).
2742320

Managing Next Generation Energy Systems
ucs_sms_2973198
http://sms.cam.ac.uk/collection/2973198
Background
Stakeholders working with energy systems have to make complex decisions formulated from riskbased assessments about the future. The move towards more renewables in our energy systems complicates matters even further, requiring the development of an integrated power grid and continuous and steady transformation of the UK power system. Network flows must be managed reliably under uncertain demands, uncertain supply, emerging network technologies and possible failures and, further, prices in related markets can be highly volatile.
Mathematicians working with engineers and economists, can make significant contributions to address such issues, by helping to develop fitforpurpose models for next generation energy systems. These interdisciplinary approaches are looking to address a range of associated problems, including modelling, prediction, simulation, control, market and mechanism design and optimisation.
This knowledge exchange workshop was part of the four months Research Programme at the Isaac Newton Institute (INI) on The Mathematics of Energy Systems. Participants on this programme are highly interdisciplinary and key aims are to develop methodology which is urgent for the next several years and to sow the seeds of a lasting mathematical research agenda. This event focused on disseminating the key research outputs from the programme and highlighted aspects relevant to energy sector stakeholders and the future research agenda.
Aims and Objectives
This knowledge exchange event featured a number of talks from academic researchers, as well as some from end users including transmission and distribution network operators. It provided an opportunity for those from industry and the public sector, to access stateoftheart theory and methods for energy systems modeling, as well as to help foster links between the various communities. A number of research tracks from the INI research programme were featured in the academic talks and these included:
Budgeting and scheduling of maintenance and replacement of power system components
Planning under uncertainty
Moving energy through time: storage and demand side response
Pricing and optimisation of intraday/dayahead electricity and futures contracts
Computation in markets with risk
Transmission and distribution network operators perspectives
This event was of interest to academics involved in energy systems research, as well as stakeholders from across the energy sector supply chain – including transmission, network distribution, generation, retail and regulation.
2973198

Mathematical and Statistical Approaches to Climate Modelling and Prediction
ucs_sms_870907
http://sms.cam.ac.uk/collection/870907
Our best estimates of future climate are based on the use of complex computer models that do not explicitly resolve the wide variety of spatiotemporal scales making up Earth's climate system. The nonlinearity of the governing physical processes allows energy transfer between different scales, and many aspects of this complex behaviour can be represented by stochastic models. However, the theoretical basis for so doing is far from complete. Many uncertainties remain in predictions derived from climate models, yet governments are increasingly reliant on model predictions to inform mitigation and adaptation strategies. An overarching aim of climate scientists is to reduce the uncertainty in climate predictions and produce credible assessments of model accuracy. This programme focuses on two key themes that both require the close collaboration of mathematicians, statisticians and climate scientists in order to improve climate models and the interpretation of their output.
Read more at http://www.newton.ac.uk/programmes/CLP/index.html
870907

Mathematical and statistical challenges in landscape decision making
ucs_sms_3031447
http://sms.cam.ac.uk/collection/3031447
Land is a key limiting resource in many regions of the world, including the UK. Society depends on land resources for many purposes, including urban settlement, employment and transportation, as well as a host of benefits we get from nature (ecosystem services)  food, timber, energy, recreation, and aesthetic benefits. We require these land resources to be resilient to environmental change, and to meet increasing demands for not only housing, but also renewable energy, recreation and climate change mitigation. Landuse therefore connects many of the UN Sustainable Development Goals. In the UK, EU exit will require the introduction of many new policies connected to landuse (e.g. replacing the Common Agricultural Policy, the EU Biodiversity Strategy, etc) – implying an urgent need to develop better landscape decision tools. This INI programme will explore the mathematical and statistical challenges associated with making use of the latest observations to understand and project landuse changes.
Questions to be addressed will include: what is the minimal useful representation of the landscape system? How do we robustly model the coupled humanenvironment system without assuming that people act as perfectly rational economic agents? Where are the nonlinearities and sensitivities of the system, and how could these be used to produce transformative changes in landuse? How do we reconcile scale disconnects between different elements of humanenvironment systems? The onemonth programme will be interdisciplinary by design, bringing together those interested in agriculture, forestry, water resources and biodiversity, with mathematicians, statisticians and computer scientists expert in system modelling, uncertainty quantification and decision making.
3031447

Mathematical Aspects of Quantum Integrable Models in and out of Equilibrium
ucs_sms_2163440
http://sms.cam.ac.uk/collection/2163440
Quantum Integrability is a rich and highly crossdisciplinary subject, with fascinating mathematical structures and a wide spectrum of physical applications. It is the key tool for understanding critical properties of numerous quantum systems at and out of equilibrium, such as spin chains or the deltafunction Bose gas (also known as the quantum nonlinear Schrödinger equation). Longstanding problems such as the scaling limit of the Ising model in a magnetic field have been solved thanks to recent developments of integrable techniques.
These developments in theoretical physics have been paralleled by advances in several areas of pure and applied mathematics, enhancing interactions among researchers working on combinatorics, probability theory, infinite dimensional Lie algebras, knots and braids, soliton systems, random matrices, nonlinear differential equations and computational science.
A new arena for quantum integrable systems has recently arisen as a result of the ability to realize for the first time, stable and controllable isolated quantum systems (by means of cold atom experimental setups). This has led to an immense growth of this research area and has given access to a largely unexplored territory of outequilibrium quantum dynamics.
These exciting advances call for the development of new mathematical techniques to meet the challenge of describing outofequilibrium phenomena in strongly interacting lowdimensional quantum systems.
In gathering together a core group of outstanding scientists, we aim to make substantial progress on a series of key open problems. Topics will include
Quantum Quenches
Boundary Conformal Field Theory
Driven Systems
Local and nonlocal conserved charges
Boltzmann equation and transport phenomena
Entanglement measures
Linear and nonlinear response
Nonlinear hydrodynamics
Thermalization and Equilibration in Quantum Systems
Generalized Gibbs Ensemble
Dynamics of quantum integrable systems
Open quantum systems
Techniques in atomics condensate
Activities
In the first week of the programme there will be a conference, that will gather together leading physicists and mathematicians in the area of Quantum Integrability. In each of the following weeks there will be two introductory 60 minute lectures by worldleading experts. The topics of the lectures will be chosen to mesh with Focus Week Activities planned to involve the participants on key themes of the programme. During the Focus Weeks there will also be a certain number of round table discussions that will help in exploiting new scientific directions and shaping the future research on this emerging field.
2163440

Mathematical aspects of turbulence: where do we stand?
ucs_sms_3752488
http://sms.cam.ac.uk/collection/3752488
Despite the heavy deployment of effort and resources in the study of turbulent fluid flows for well over a century, fundamental questions remain stubbornly unanswered. The associated issues range so widely across the mathematical, physical and engineering sciences that no single research programme can hope to cover all aspects of the subject. This particular programme will concentrate upon the more mathematical concerns, addressing a significant range of topics including:
Analysis of the incompressible NavierStokes and Euler equations;
Modelling and analysis of turbulent transport, mixing and scaling processes;
Inhomogeneous and anisotropic wallbounded flows and transition to turbulence;
Geophysical turbulence including atmospheric, oceanographic and planetary flows.
Recent years have witnessed many analytical and computational advances in our understanding of the structural and dynamical properties of solutions of the incompressible NavierStokes and Euler equations and associated models, but many mathematical issues require further investigation. And despite the pressing demand for practical answers, there is nevertheless a need for longerterm thinking about how the most recent developments in mathematical analysis can be leveraged into a wider understanding of physical processes. For example, the regularity and singularity results in the primitive equations of geophysical fluid dynamics can impact climate science models. The introduction of convex integration machinery that has been instrumental in completing the proof of the Onsager conjecture and establishing nonunique weak solutions for the Euler and the NavierStokes equations can bring insights into the dissipative anomaly conjecture, a.k.a. Kolmogorov's zeroth law of turbulence. Singularity results for the Euler equations and advances on the Prandtl equations and boundary layer theory relevant to wallbounded turbulence can have significant engineering applications.
Through a range of events this programme will bring researchers from a broad range of disciplines together to consider these issues. It will provide the space for the type of collaborative interdisciplinary thinking necessary for the formulation of new ideas and research directions.
3752488

Mathematical Challenges in Quantum Information
ucs_sms_1543827
http://sms.cam.ac.uk/collection/1543827
Quantum information is currently one of the most dynamic and exciting areas of science and technology. Its breadth of significance ranges from deep fundamental issues of the ultimate physical limits of information processing and foundations of quantum mechanics, to the technological exploitation of quantum physics for exponentially enhanced computing power and novel possibilities for communication and information security. It is a highly crossdisciplinary subject with essential inputs from computer science, information theory, mathematics, quantum physics, engineering and others. In view of the central role of information processing and communication in most aspects of modern society, government and daily life, the transformative potential of Quantum Information for 21st century technology is immense.
Read more at http://www.newton.ac.uk/programmes/MQI/
1543827

Mathematical Design for Solid Complex Materials
ucs_sms_2929629
http://sms.cam.ac.uk/collection/2929629
Background
Complex materials have extraordinary and unique features which are usually determined by their rich microsctructures. They are key components to many of the emerging applications we take for granted in our everyday lives – in liquid crystal displays, microsensors and actuators, miniaturised phones, light but tough metals in cars, biological implants, composites for aerospace and many more.
Mathematics plays an important role in ensuring that technological advances in complex materials continue. It is integral to the design of such materials with desirable functionalities. However, the theoretical understanding and modelling of them have so far been quite inadequate. Mathematical modelling and understanding is a key enabler for complex material development and further promotes greater potential of these materials with actual engineering applications.
Some of the mathematical areas that are directly relevant to the key scientific questions of interest include optimisation and calculus of variations, geometry and topology, continuum mechanics and partial differential equations. The study of such common principles and techniques will aid the advancement of optimal material design and its more broad application.
This knowledge exchange workshop is part of the six months Research Programme at the Isaac Newton Institute (INI) on The Mathematical design of new materials. It brings together mathematicians and scientists working in various areas of materials science and applied mathematics in order to initiate a systematic study of the optimal design of new complex materials.
Aims and Objectives
This workshop aims to highlight how mathematical modelling provides a rational way for understanding of complex materials properties and guiding the development strategy for such materials. Mathematical modelling forms the theoretical foundation for modern materials development. As well as being a descriptor for complex materials, such models are often the key to the discovery of the singular and unusual properties of the material.
A focus for the day will be the interesting classes of complex materials  shape memory alloys (SMAs) and those involving phase transformations. These materials have remarkable properties, including the ability to ‘memorise’ or retain their previous shape when subjected to certain stimulus such as thermomechanical or magnetic forces. Due to their unique and superior properties, they can be found in a broad range of commercial areas and have great potential in emerging applications and this event will focus on the following industry application areas:
Medical devices
Energy
Robotics
This workshop will feature talks from leading academic researchers, as well as end users presenting challenges from the medical devices, energy and robotics industries. It will bring together mathematicians and scientists working in various areas of materials science and applied mathematics to further investigate opportunities in the mathematical modelling to enable optimal design of complex new materials.
2929629

Mathematical Foundations of Optimisation in Data Science
ucs_sms_3345442
http://sms.cam.ac.uk/collection/3345442
A Research Conference of the Cantab Capital Institute for the Mathematics of Information.
Background
The Cantab Capital Institute for the Mathematics of Information (CCIMI) was pleased to announce its fourth annual academic conference, which focused on the academic interactions taking place related to Mathematical Foundations of Optimisation in Data Science.
Launched in 2016, CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is of the highest international level, aiming to extract the relevant information from large and highdimensional data with a predictable certainty.
This event followed previous successful academic and industrial engagement events, which focused on different aspects related to the mathematics of information.
Aims and Objectives
This event brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to data analysis.
The talks covered:
Applications of optimisation methods in engineering and science
Algorithm design, analysis and implementation for linear and nonlinear non convex smooth optimisation
Regularisation
Optimisation for machine learning.
There was a session for shorter “elevator pitches” from next generation researchers, who also had the opportunity to present more detail about their work.
This event was of interest to participants including social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied and computational analysis; quantum computing; cryptography; communication and security; and those from data processing.
3345442

Mathematical Modelling and Analysis of Complex Fluids and Active Media in Evolving Domains
ucs_sms_1478565
http://sms.cam.ac.uk/collection/1478565
This four month programme shall advance the mathematical modelling and analysis of complex fluids and active media in situations involving interface and contact line dynamics. It is focused on confined systems involving various kinds of interfaces as, for instance, moving or evaporating drops on substrates, vesicles, thin films, crawling and swimming cells, biological membranes and tissues.
Read more at: http://www.newton.ac.uk/programmes/CFM/
1478565

Mathematical, Foundational and Computational Aspects of the Higher Infinite
ucs_sms_2054111
http://sms.cam.ac.uk/collection/2054111
The goals of set theory are the analysis of the structure of the Higher Infinite, i.e. Cantor's settheoretic universe and the elucidation of the nature of infinite mathematical objects and their role in foundational issues underlying mathematics. Moreover, the current standard system of set theory, the ZermeloFraenkel axioms with the Axiom of Choice (ZFC), is the usual framework for a large part of mathematics.
Current settheoretic research on infinity focuses on the following three broad areas: large Cardinals and inner model theory, descriptive settheoretic methods and classification problems, and infinite combinatorics.
The programme HIF will connect these three main strands of settheoretic research and other fields of set theory to the wider scope of mathematics, to research in the foundations of mathematics, including some philosophical issues, and to research on computational issues of infinity, e.g. in theoretical computer science and constructive mathematics.
The following topics are a nonexclusive list of important examples of relevant fields for the research done in the programme HIF:
1.The structure of definable subsets of the continuum
2.Infinite combinatorics, forcing, and large cardinals
3.Inner models of large cardinals and aspects of determinacy
4.Applications of set theory to other areas of mathematics
5.Constructive set theory and new models of computation
6.Set theory and the foundations of mathematics
Three workshops are planned during the programme: The first one (2428 August 2015) will be the 5th European Set Theory Conference. The second workshop, entitled "New challenges in iterated forcing" will be a Satellite Meeting held at the University of East Anglia in Norwich (26 November 2015). A final workshop will take place on 1418 December 2015.
2054111

Mathematical, Statistical and Computational Aspects of the New Science of Metagenomics
ucs_sms_1655704
http://sms.cam.ac.uk/collection/1655704
Metagenomics is the study of the total genomic content of microbial communities. In metagenomic studies, DNA material is sampled collectively from the microorganisms that populate the environment of interest (e.g. agricultural soil, ocean water, or the human gut). The extracted DNA sequences are subsequently used to profile the environment and its biodiversity, its dominant microbial classes or biological functions, and whether and how this profile differs from those of other environments. This research programme will bring together leading expertise in the multiple disciplines involved in metagenomics including mathematics, computer science, probability and statistics, biomedical research and biology.
Read more at http://www.newton.ac.uk/programmes/MTG/
1655704

Mathematics and Applications of Branes in String and Mtheory
ucs_sms_1202251
http://sms.cam.ac.uk/collection/1202251
Mtheory is an 11dimensional quantum theory of gravity which, in addition to gravitons and other particlelike excitations, includes extended objects known as membranes and five branes. Though a complete definition of Mtheory is not yet known, it is proposed as a nonperturbative formulation of superstring theory and as such is a compelling candidate for a unified theory of the fundamental particles and forces in Nature. Much has been learned about Mtheory through its symmetries and its relation to supergravity and string theory and this has in turn led to important results in superstring theory and quantum gauge theory.
1202251

Mathematics and Physics of Anderson Localization: 50 Years After
ucs_sms_113
http://sms.cam.ac.uk/collection/113
In his seminal paper Absence of diffusion in certain random lattices (1958) Philip W. Anderson discovered one of the most striking quantum interference phenomena: particle localization due to disorder. Cited in 1977 for the Nobel prize in physics, that paper was fundamental for many subsequent developments in condensed matter theory. In particular, in the last 25 years the phenomenon of localization proved to be crucial for the understanding of the Quantum Hall effect, mesoscopic fluctuations in small conductors as well as some aspects of quantum chaotic behaviour.
Random Schrödinger operators are an area of very active research in mathematical physics and mathematics. Here the main effort is to clarify the nature of the underlying spectrum. In particular, it has been proved that in dimension one all states are localized, and in any dimension the random Schrödinger operator has dense point spectrum for large enough disorder. Some open mathematical problems of major importance include the longtime evolutions of a quantum particle in a weakly disordered medium and existence of absolutely continuous spectrum in three dimensions. The expected transition from localized (point spectrum) to extended eigenstates (absolutely continuous spectrum) will also be addressed.
Read more at: http://www.newton.ac.uk/programmes/MPA/
113

Mathematics and Physics of the Holographic Principle
ucs_sms_1556140
http://sms.cam.ac.uk/collection/1556140
Holographic duality (also called gauge/gravity duality or the AdS/CFT correspondence) relates a string theory — i.e. a quantum theory of gravity — to a quantum field theory without gravity. Currently it is an area of research located at the confluence of previously seemingly distant fields in physics and mathematics including superconductivity and other exotic phases of strongly coupled quantum matter, string theory, numerical general relativity and the theory of nonlinear partial differential equations. The main aim of the programme is to bring together experts in these diverse fields to tackle questions which the traditional methods within each discipline have proved inadequate to address, with special emphasis on strongly correlated condensed matter systems and nonequilibrium dynamics.
Read more at http://www.newton.ac.uk/programmes/HOL/
1556140

Mathematics and Statistics for Effective Regulation
ucs_sms_3335793
http://sms.cam.ac.uk/collection/3335793
Background
The reliability and accuracy of reporting is key to ensuring confidence in the financial sector, yet there is limited regulation on data quality and the software used, a lack of consistency and no agreed documentation of modelling. This is in contrast to medicines and medical devices, where there are auditable processes in place with the requirement to demonstrate the source of data used and the need to show documentation of the workings of the software. This is important because of issues related to the efficacy and safety of medicines, such as how to collect reliable evidence, what the longer term effects of medicines are and how to keep medical data secure.
Mathematical and, in particular, statistical techniques provide rigorous approaches to evaluating quality of data, models and software. This event explored and compared the use of standards and approaches to regulation in medicines and medical devices with those in the financial and pensions sectors and consider what improvements could be made.
Aims and Objectives
As well as providing a useful comparison of standards and approaches to regulation in the medical and financial sectors, this workshop will provide an overview of the different expectations of regulatory bodies. It will look at approaches to assessing the quality and validity of data, statistics, computing and mathematics in the financial sector which differ substantially from those in the health sector. Speakers explored these issues, with a focus on pensions, investments and fraud. The talks looked at risks in the financial sector, ethics, handling uncertainty and achieving transparency which is important for trust. The final session was be a discussion of methods to investigate how regulation could be more efficient and effective.
Some specific issues that were explored are:
Empirical basis for inputs into projection software and the transparency of the rationale for assumptions used in projection software
The choice of software
Handling of uncertainty
Sensitivity analysis
Risk and derisking.
This event was of interest to those working in finance, quantitative finance, economics, actuarial mathematics, statistics and data science.
The event was developed and delivered in collaboration with the Royal Statistical Society and its Finance and Economics Special Interest Group.
3335793

Mathematics for the Fluid Earth
ucs_sms_1580157
http://sms.cam.ac.uk/collection/1580157
The purpose of this programme is to bring together scientists from very different perspectives in models of the dynamics of the fluid components of the Earth system. This interest may be directly into the modelling, also numerical, or at a more abstract modelling level in terms of understanding the climate system as a complex dynamical system. This programme aims to prove that there is a close connection between “core” questions and problems of pure and applied mathematics and “core” questions of geophysical fluid dynamics relevant for the investigation of the climate system and of its component, and that these are closely linked to defining rigorously what is a good model for a complex system. The aim of the programme is to provide a common ground for fostering mutually stimulating and inspiring exchanges and for creating opportunities for future research.
Read more at http://www.newton.ac.uk/programmes/MFE/
1580157

Mathematics of deep learning
ucs_sms_3594492
http://sms.cam.ac.uk/collection/3594492
Programme theme
Due to the massive amounts of training data complemented by a tremendously increased computing power, deep neural networks have recently seen an impressive comeback. In fact, we currently witness how algorithms based on deep neural networks are infusing numerous aspects of the public sector such as being used for prescreening job applications or revolutionizing the healthcare industry. A similarly strong impact can be observed on science itself. Deep learning based approaches have proven very useful within certain mathematical problem settings such as solving illposed inverse problems or highdimensional partial differential equations, sometimes already leading to stateoftheart algorithms. However, most of the related research is still empirically driven and a sound theoretical foundation is largely missing. This is not only a significant problem from a scientific viewpoint, but particularly critical for sensitive applications such as in the health care sector. Thus there exists a tremendous need for mathematics of deep learning.
Aiming to derive a mathematical foundation of deep learning, this programme addresses theoretical questions in two realms:
1) Theoretical foundations of deep learning independent of a particular application.
(2) Theoretical analysis of the potential and the limitations of deep learning for mathematical methodologies, in particular, for inverse problems and partial differential equations.
Area (1) focusses on the area of expressivity asking how powerful network architecture is from an approximation viewpoint, on the area of learning aiming to rigorously mathematically analyse training algorithms, and on the area of generalization to understand the ability of neural networks to perform well on outofsample data also. Those three research directions originate from the viewpoint of statistical learning. In addition, our programme aims to study questions related to interpretability, security, and safety of deep learning.
Area (2) focusses on the application of deep neural networks to solve illposed inverse problems and partial differential equations. Key research goals in this regime are understanding how deep learning can be optimally combined with modelbased methods as well as complete mathematical error analyses for such deep learning based approximation algorithms for illposed inverse problems or highdimensional partial differential equations which reveal the success and the limitations of such algorithms when applied to such mathematical problems.
The main goal of this programme is to achieve substantial progress in developing a theoretical foundation of deep learning. For this, the programme will for the first time gather the top experts from various areas of mathematics and of the theory of machine learning, including computer scientists, physicists, and statisticians in one place, initiating collaborations across intra and interdisciplinary boundaries and thereby generating unprecedented research dynamics.
3594492

Mathematics of Planet Earth 2013
ucs_sms_1369666
http://sms.cam.ac.uk/collection/1369666
Our planet is the setting for dynamic processes of all sorts, including the geophysical processes in the mantle, the continents, and the oceans, the atmospheric processes that determine our weather and climates, the biological processes involving living species and their interactions, and the human processes of finance, agriculture, water, transportation, and energy. The challenges facing our planet and our civilization are multidisciplinary and multifaceted, and the mathematical sciences play a central role in the scientific effort to understand and to deal with these challenges.
Read more at: mpe2013.org
Or www.newton.ac.uk/events/2013/mpe/
1369666

Mathematics of sea ice phenomena
ucs_sms_2561139
http://sms.cam.ac.uk/collection/2561139
Ice is one of the most common materials on Earth, yet it is very different from all other known materials. Depending on its morphology and microstructure, it may behave as an elastic, brittle, viscoelastic or even as a quasiliquid material. Moreover, ice is present on the Earth in different forms, notably the freshwater ice that occurs in the air, in ice caps, glaciers, icebergs, frozen rivers and lakes, and the many varieties of seaice that form in the polar and subpolar oceans. Seaice consists of solid freshwater ice, liquid salty brine, gas inclusion and possibly some other components, which makes it difficult to describe.
The 'Mathematics of SeaIce Phenomena' programme will focus upon seaice mechanics and thermodynamics, and seaice interactions with fluids and solids. Modelling of seaice and its behaviour in different situations is a challenging problem that spans several areas of physics and mathematics and has massive implications in the natural sciences and engineering. The programme will advance modelling of icerelated problems giving an appropriate level of physical and mathematical rigour to such problems. This will identify problems that require the urgent attention of mathematicians and physicists and establish a scientific network on ice research with coordinated efforts to tackle existing and future problems. The programme will bring together researchers from different fields to work in groups on modern problems of ice dynamics and thermodynamics, to formulate new problems and models and to discuss strategies for their solutions. The programme also aims to bring new specialists with new ideas and nonstandard approaches and techniques to the challenging problems of sea ice modelling.
Although the programme is associated with modelling floating seaice, other forms of ice are also included where they help with phenomenological and/or methodological understanding of seaice behaviour.
2561139

Melt in the Mantle
ucs_sms_2184980
http://sms.cam.ac.uk/collection/2184980
The Earth's mantle is almost entirely solid, but on geological timescales it convects vigorously, the wellknown surface expression of this being plate tectonics. At depths up to ~100 km beneath platetectonic boundaries (midocean ridges and subduction zones), and beneath ocean islands such as Hawaii, the mantle melts, and that melt rises to the surface to feed volcanism and form new crust. Such magmatism plays a key role in the chemical evolution and dynamics of our planet. Although the basic thermodynamics of melt generation in these settings is well understood, how the melt is transported to the surface is not, despite several decades of work on the problem. Furthermore, recent observational evidence suggests that mantle melting is not restricted to the near surface (top 100 km): it may occur within the mantle transition zone (410660 km depth) and above the coremantle boundary (2900 km). For these deeper instances of melting, an understanding of the dynamical and thermochemical characteristics is currently lacking.
Understanding the formation and migration of melt in the mantle presents a formidable scientific and mathematical challenge. One key challenge is in bridging diverse length scales  melt lies along grain boundaries at micron scales, may focus into channels at metre scales, and migrates over 100 km. Sophisticated mathematical techniques, such as homogenisation theory, are needed to map an understanding of physics at the smallest scales to platetectonic scales. Seismology offers a way to image melt in the mantle, but the development of new tools in inverse theory are required to extract that information. Models of melt transport are eventually cast as a series of coupled nonlinear partial differential equations, which require advanced numerical techniques to solve. This programme will bring together a broad spectrum of mathematicians and solid Earth scientists to tackle these and other fundamental challenges of melt in the mantle.
2184980

Metric and Analytic Aspects of Moduli Spaces
ucs_sms_2037558
http://sms.cam.ac.uk/collection/2037558
The term ‘moduli space’ has its origins in the classification of conformal structures on twodimensional surfaces. Closed surfaces are classified topologically by their genus, but for fixed genus, the set of inequivalent conformal structures is essentially a smooth finite dimensional manifold, a first example of a moduli space.
In more recent times, many other instances of mathematical structures of this type have come to light, above all in gauge theory. They have had, and continue to have, a major impact in modern geometry, topology and mathematical physics.
Working with moduli spaces is subtle. First of all, they are implicitly defined (typically) as equivalence classes of solutions to some nonlinear partial differential equations. Second, they are almost invariably noncompact and/or singular, and one of the challenges is to understand them asymptotically and/or near the singularities.
The goal of the programme is to explore moduli spaces from the metric and analytical points of view. We shall survey the current state of the art with a focus on four themes: 4dimensional hyperKaehler manifolds; compactification of moduli spaces; analysis on moduli spaces; new constructions and challenges. There will be a 5day workshop during the second week of the programme.
2037558

Model theory and applications to algebra and analysis
ucs_sms_3776417
http://sms.cam.ac.uk/collection/3776417
Model theory is a branch of mathematical logic dealing with abstract structures (models), historically with connections to other areas of mathematics. In the past decade, model theory has reached a new maturity, allowing for a strengthening of these connections and striking applications to diophantine geometry, analytic geometry and Lie theory, as well as strong interactions with group theory, representation theory of finitedimensional algebras, and the study of the padics. The main objective of the semester will be to consolidate these advances by providing the required interdisciplinary collaborations.
Model theory is traditionally divided into two parts pure and applied. Pure model theory studies abstract properties of first order theories, and derives structure theorems for their models. Applied model theory on the other hand studies concrete algebraic structures from a modeltheoretic point of view, and uses results from pure model theory to get a better understanding of the structures in question, of the lattice of definable sets, and of various functorialities and uniformities of definition. By its very nature, applied model theory has strong connections to other branches of mathematics, and its results often have nonmodeltheoretic implications. A substantial knowledge of algebra, and nowadays of algebraic and analytic geometry, is required.
3776417

ModelData Integration in Physical Systems
ucs_sms_1677535
http://sms.cam.ac.uk/collection/1677535
The workshop is concerned with the subject of blending observational data with complex models, primarily in the physical sciences, with the aim of making improved predictions. The increasing complexity of phenomena that scientists and engineers wish to model, together with our increased ability to gather, store, and interrogate data, mean that the subjects of applied mathematics and statistics are increasingly required to work in conjunction in order to significantly progress understanding.
Applications are far reaching and include the atmospheric sciences, geophysics, chemistry and signal processing. The workshop will bring together experts reflecting applied, computational, methodological and theoretical aspects of the subject area.
1677535

Modelling Behaviour to Inform Policy for Pandemics
ucs_sms_3689160
http://sms.cam.ac.uk/collection/3689160
3689160

Moduli Spaces
ucs_sms_1087487
http://sms.cam.ac.uk/collection/1087487
Algebraic geometry is a key area of mathematical research of international significance. It has strong connections with many other areas of mathematics (differential geometry, topology, number theory, representation theory, etc.) and also with other disciplines (in the present context, particularly theoretical physics). Moduli theory is the study of the way in which objects in algebraic geometry (or in other areas of mathematics) vary in families and is fundamental to an understanding of the objects themselves. The theory goes back at least to Riemann in the midnineteenth century, but moduli spaces were first rigorously constructed in the 1960s by Mumford and others. The theory has continued to develop since then, perhaps most notably with the infusion of ideas from physics after 1980.
Read more at: http://www.newton.ac.uk/programmes/MOS/
1087487

Multiscale Numerics for the Atmosphere and Ocean
ucs_sms_1291503
http://sms.cam.ac.uk/collection/1291503
Numerical models of the atmosphere and ocean have proved to be immensely valuable forecasting tools for short timescale weather and longer timescale seasonal and climate prediction. As the decades pass, these models have been improving due to increased computing power, improved modelling of the dynamics, improved parametrisation of subgrid scale processes and improved use of observations. These modelling improvements may be slowing and further large increases in computing power will almost certainly emerge from heterogenous computing architectures configued in even more massively parallel machines. If we are unable to exploit these new opportunities in highperformance computing, our current models and codes risk becoming obsolete.
Read more at: www.newton.ac.uk/programmes/AMM/
1291503

New connections in number theory and physics
ucs_sms_3535007
http://sms.cam.ac.uk/collection/3535007
Workshop
24th May 2021 to 28th May 2021
Workshop theme
During the 20th century, interactions between geometers and theoretical physicists were revolutionary in both areas, leading to such unexpected developments as mirror symmetry and the impact of topological field theory on invariants of 4manifolds. Another momentum is now developing around new connections between number theory and physics, mainly but not exclusively through the theory of automorphic forms. We have reached a time when contacts between number theorists and physicists have the potential to generate another surge of developments.
The purpose of this interdisciplinary programme is to investigate connections between various fields of theoretical physics, in particular string theory and statistical models of crystals, and the theory of automorphic forms, mock modular forms and beyond. The nonperturbative structure of string theory has led to new uses of automorphic forms that have already appeared in number theory, as well as new exotic automorphic objects that have not yet been encountered.
This is an emergent research area with a lot of potential for crossdisciplinary collaborations with great benefit to both areas. Recent work has revealed, on the one hand, a profound significance of automorphic forms and automorphic representations for string scattering amplitudes and, on the other hand, an unexpected appearance of mock theta functions in answering key questions pertaining to quantum properties of black holes. In addition, solvable lattice models have recently appeared in connection with Eisenstein series on metaplectic groups, calling for some underlying structure that remains to be understood.
Speakers
Kathrin Bringmann
Miranda Cheng
Eric D’Hoker
Amanda Folsom
Jens Funke
Jeff Harvey
Greg Moore
Steve Miller
Sameer Murthy
Boris Pioline
Yiannis Sakellaridis
Nils Scheithauer
Anne Taormina
Akshay Venkatesh
Edward Witten
Don Zagier
Please find the timetable for the event here: Timetable
Given the current restrictions on movement, due to the ongoing pandemic, the INI intends to run this workshop virtually across 5 days. All talks and discussion sessions will be available virtually.
3535007

New horizons in dispersive hydrodynamics
ucs_sms_3564195
http://sms.cam.ac.uk/collection/3564195
Workshop theme
Image: soliton gas in deep water waves
This bridging workshop aims at exploring novel, crossdisciplinary connections of dispersive hydrodynamics within the four main themes of the forthcoming 6month programme “Dispersive hydrodynamics: mathematics, simulations and experiments, with applications in nonlinear waves” https://www.newton.ac.uk/event/hyd2
The workshop themes will include: new directions, mathematical techniques and applications in nonlinear waves; statistical mechanics and dispersive hydrodynamics; applications in glaciology and seaice systems; dispersive hydrodynamic phenomena in fibre optics and magnetisation dynamics. The online format will include introductory lectures from leading experts, plenary and contributed talks, focused group discussions and poster sessions. It is expected that the workshop will stimulate new crossdisciplinary collaborations and attract new audiences to the subject of dispersive hydrodynamics. Special emphasis is given to involving young researchers and to diversity among the participants.
3564195

New Models of Spatial and Social Behaviour in a Pandemic  Programme
ucs_sms_3543340
http://sms.cam.ac.uk/collection/3543340
Wednesday 26th May 2021 to Thursday 27th May 2021
Background
The Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative brought modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on Coronavirus (COVID19). The Newton Gateway is now working with the followon initiative (funded by EPSRC)  the RAMP Continuity Network – to help deliver a series of meetings, workshops and virtual study groups to take forward promising and relevant areas of research .
This two day science meeting brought together two longer term research activities – urban analytics and human dynamics in small spaces. These RAMPinitiated projects are interrelated and differ mainly in terms of geographical scale. This event helped fulfil a key aim to maintain strong communication links between them, as well as extending to other relevant communities around COVID19. It will also seek to continue to gain further insights as lockdown restrictions are loosened in the coming months in order to provide supporting evidence and assistance to the scientists advising the government on national and local policy responses using urban analytics and spatial modelling. There are important implications for extending these models to embrace key social and economic issues that result from the pandemic and will be explored through future workshops.
These RAMP groups have been modelling the transmission of the virus in urban areas and small spaces, through mobility and interactions of people and how this would respond to different policy interventions. Regional differences in infection rate are particularly of interest, as these could show that it may be safe to send people back to work or school in one area of the country but not another. The groups have been looking at which decisions have the greatest impact and where they are most likely to be felt. This event offereed an opportunity to catch up with core model development, various research strands and progress on demonstrator projects, as well as facilitating engagement with the wider mathematical modelling and epidemiology communities.
Aims and Objectives
Building on the work begun by RAMP, this twoday science meeting reviewed existing work and identified where further research is most urgently needed. The meeting included updates on model and simulator development and demonstrator projects. There were updates on the status of getting to national capability and integration with policy makers.
As well as two key note talks at the start and finish, the event included the following sessions:
• Micro modelling and simulation
• Spatial epidemic modelling
• Stakeholders perspectives
Contributions from other stakeholders included areas such as transport, retail, urban environments, local policy making and the wider societal implications such as in urban poverty and inequalities.
3543340

Newton Gateway to Mathematics
ucs_sms_1446634
http://sms.cam.ac.uk/collection/1446634
In March 2013, the Isaac Newton Institute for Mathematical Sciences (INI) launched the Turing Gateway to Mathematics (TGM). The TGM is an impact initiative of the INI and aims to stimulate the interchange of knowledge and ideas between academics of different disciplines and users of modern mathematics. Named after Alan Turing because of his exceptionally wide influence across a very broad front, the Gateway is a channel for collaboration and cooperation between academia and industry. It will help to shorten pathways to impact and increase access to modern mathematical methods for other industrial and academic areas.
1446634

Newton Institute Video Vault Archive
ucs_sms_78
http://sms.cam.ac.uk/collection/78
Videos from the Isaac Newton Institute for Mathematical Sciences Archives. Keywords: Math, Maths, Mathematics, Science.
78

Next Generation Research and Modelling for Landscape Decisions
ucs_sms_3040223
http://sms.cam.ac.uk/collection/3040223
Background
Land is a key limiting resource in many regions of the world, including the UK. Society depends on land resources for many purposes, including urban settlement, employment and transportation, as well as a host of benefits we get from nature (ecosystem services)  food, timber, energy, recreation, and aesthetic benefits. We require these land resources to be resilient to environmental change, and to meet increasing demands for not only housing, but also renewable energy, recreation, agriculture and climate change mitigation. Such complexities are hugely challenging for stakeholders and bring an urgent need for the development of better landscape decision tools.
Mathematical sciences are integral to the development of such tools and methodologies which are needed to capture the complexity and uncertainty inherent in landscape decisionmaking. For instance, advanced mathematical and statistical modelling techniques are a powerful tool providing ways to combine different spatial and temporal processes as well as incorporating future uncertainty.
This knowledge exchange workshop was part of the one month Programme at the Isaac Newton Institute (INI) on Mathematical and Statistical Challenges to Landscape Decision Making. It formed day 3 of the three day research workshop on Progress on Novel Mathematics and Statistics for Landscape Decisions, including Priorities for Further Research. The Programme aimed to explore the mathematical and statistical challenges associated with making use of the latest observations to understand and project landuse changes.
Aims and Objectives
Intended to help inform future funding programmes for landscape decisions, this event aimed to help synthesize those research areas where collaboration between the environmental, mathematical and social sciences have the potential to significantly advance modelling of landscape systems. Insights will be developed into research roadmaps that can be used to set the agenda for future funding calls of the UKRI Strategic Priority Fund on Landscape Decisions led by NERC.
This day was open to all stakeholders. It aimed to identify the novel approaches and tools developed during the one month INI Research Programme which are particularly relevant for policy and practice, and highlighted what was required to make these new methods and tools more valuable for informing landscape decisionmaking.
Some key questions which have been considered in the INI programme were covered. These included issues such as the minimal useful representation of the landscape system, how to robustly model the coupled humanenvironment system, identifying the nonlinearities and sensitivities of the system and how to reconcile scale disconnects between different elements of humanenvironment systems?
Four main sessions within the programme for the day included:
Decision making in the face of uncertainty
Spatial and temporal scaling
Nonlinearities and sensitivities to policy inputs
Stakeholder perspectives and future research roadmaps.
Participants in the workshop included a highly interdisciplinary mix of both academic and nonacademic researchers and policy makers working on land related research and policy questions. It was of interest to researchers from a number of areas including mathematics, statistics, environmental science, geography, ecology and biology, as well as stakeholders from government/public sector, business, and other organisations involved in urban planning, coastal/inland waters and land conservation and management.
3040223

NonAbelian Fundamental Groups in Arithmetic Geometry
ucs_sms_652358
http://sms.cam.ac.uk/collection/652358
In the 1980's Grothendieck formulated his anabelian conjectures that brought to an hithertounexplored depth the interaction between topology and arithmetic. This suggested that the study of nonabelian fundamental groups could lead to a new understanding of deep arithmetic phenomena, including the arithmetic theory of moduli and Diophantine finiteness on hyperbolic curves. A certain amount of work in recent years linking fundamental groups to Diophantine geometry intimates deep and mysterious connections to the theory of motives and Iwasawa theory, with their links with arithmetic problems on special values of Lfunctions such as the conjecture of Birch and SwinnertonDyer. In fact, the work thus far suggests that the stillunresolved section conjecture of Grothendieck, whereby maps from Galois groups of number fields to fundamental groups of arithmetic curves are all proposed to be of geometric origin, is exactly the sort of key problem that touches the core of all these areas of number theory and more.
Read more at: http://www.newton.ac.uk/programmes/NAG/index.html
EVENTS:
 Introductory Workshop
http://www.newton.ac.uk/programmes/NAG/nagw01.html
 Anabelian Geometry
http://www.newton.ac.uk/programmes/NAG/nagw02.html
 Spitalfields Day  Potential Modularity
http://www.newton.ac.uk/programmes/NAG/nagw05.html
 Final Workshop
http://www.newton.ac.uk/programmes/NAG/nagw04.html
652358

NonPositive Curvature Group Actions and Cohomology
ucs_sms_2398131
http://sms.cam.ac.uk/collection/2398131
The concept of curvature describes a fundamental spatial attribute and it has found a place at the core of science since its inception.
This programme is about aspects of nonpositive curvature as they occur in various research areas of contemporary mathematics, such as the geometry of manifolds, including those arising from Lie group theory; synthetic geometry (e.g. CAT(0) geometry) as used notably in modern group theory; coarse geometry, a fundamental tool of contemporary topology; noncommutative geometry; and algebra.
By combining and comparing the aspects that nonpositive curvature displays in various contexts, the programme aims to acquire new insight and find meaningful new directions to explore. Among the tools used to uncover new aspects of nonpositive curvature one numbers cohomology, originally a tool from algebra and topology and now a research field in itself, with countless applications throughout mathematics; perturbation stability  investigating when small "errors" lead to completely new structures, or when, on the contrary, structures are robust when perturbed;fixed point and proper actions  a topic at the interface of analysis and algebra  with surprising ramifications in many other areas; and CAT(0) and coarse geometry, where CAT(0) cubical and largescale techniques come into play to solve problems from topology and algebra. All these fields are on the cutting edge of current research, and have fruitful connections to other areas, e.g. theoretical computer science.
The focus of this programme is on breakthrough results and techniques stemming from this research. The general structure consists of activities held on a regular basis (e.g. weekly research seminars, series of lectures, etc.), enhanced by weeks of more intensive lecturing focusing on a topic, and workshops intended to cathalyse interchange and research progress in a specific field. These activities rely on the interaction between long term visitors, UK researchers, and the rapidly developing body of young experts working in the area.
2398131

Nonlinear Water Waves
ucs_sms_2537909
http://sms.cam.ac.uk/collection/2537909
Organisers: Adrian Constantin (Department of Mathematics, King's College London, UK, and Faculty of Mathematics, University of Vienna, Austria), Joachim Escher (Institute of Applied Mathematics, Leibniz University Hannover, Germany), Hisashi Okamoto (Gakushuin University, Japan)
The purpose of this 4week programme is to bring mathematical analysts and applied mathematicians together, along with engineers, in a venue which will focus on four very active areas of study of surface water waves of large amplitude, where considerable advances were achieved in the last few years:
wellposedness
regularity properties and the formation of singularities
the flow beneath the waves
tsunami modelling
2537909

Novel Computational Paradigms
ucs_sms_2857473
http://sms.cam.ac.uk/collection/2857473
Background
Many of today’s interesting problems stem from the ability to generate and process large volumes of data, such as for instance, intelligent power grids and smart cities that form part of the Internet of Things. But the ability to work with all this data has to match the demand and as Moore’s law stops scaling, chipmakers will no longer be able to shrink transistors small enough to continue the trend of doubling how many they can fit on their integrated circuits every 12 or 18 months. Clearly, if the speed of processing power is to continue to develop to meet such demands, new forms of computing need to be found; new algorithms need to be developed to make efficient use of these new forms of computation; and new mathematical challenges arise in the design and analysis of these new algorithms.
In addition to the development of quantum computers, a number of novel computational paradigms, or nextgeneration computing architectures are emerging and more are likely to follow. Many have been inspired by the fundamental structure and function of the human brain. New computing paradigms are needed that are not only faster, use less power and are physically smaller, as well as those that could enable data storage/processing in contexts where current paradigms would be too expensive.
Neuromorphic computing for example, has included the development of chips that use “spiking neurons” as the basic computational building block. They attempt to model in silicon the massively parallel way the brain processes information as billions of neurons and trillions of synapses respond to sensory inputs such as visual and auditory stimuli. The implementation of neuromorphic computing at the hardware level can be realized by oxidebased memristors, threshold switches and transistors. Memristors are materials based on molecular or ionic mechanisms which act as conductors, emulating biological systems.
Similarly, massivelyparallel computing structures, such as that developed as part of the UK’s Project Spinnaker, use “spiking networks” to sensibly simulate, in real time, the behaviour of a billion neurons. Additionally, advances in DNAbased data processing and storage are predicted to have a significant influence on theoretical and practical progress in the computer sciences.
So a key question is  what could you compute on new forms of computation?
Aims and Objectives
This workshop is a collaboration with GCHQ and aims to investigate potential nextgeneration advances in novel computational paradigms. A key aim is to bring together relevant stakeholders from across various UK research communities and industry. It is hoped that this activity will help to build closer links and collaborations and aid the establishment of a joined up multidisciplinary UK community for this area. Disciplines identified so far as being relevant include synthetic biology, neuroscience, metamaterials, electronics/electrical engineering, AI/Machine learning, computer science and robotics and physics.
The event will also provide a forum for identifying challenges and increasing awareness of R&D activities across the different elements of the research communities. It is hoped that this will help to gain consensus on what the future research directions should be, for novel computational technologies, stimulating further interest from endusers towards helping to develop and invest in the novel computer paradigms area.
Over the two days, this event will include presentations from researchers as well as an enduser session, where ‘problem holders’ will present on current and future challenges and reflect how new computational innovations might be of benefit and how they might be implemented. Areas covered will include a number of key current and future research directions will be highlighted including:
Neuromorphic computing  such as memristors and massively parallel computing structures
Biologically inspired paradigms – DNA based computation and storage
Materials for novel circuits
Novel architectures
Problem owner perspectives – to include security, healthcare and financial areas
2857473

Open for Business: Energy Systems Day 2012
ucs_sms_1226313
http://sms.cam.ac.uk/collection/1226313
There will be a oneday meeting on 12 March to discuss mathematical, statistical and economic challenges arising in the management and control of future energy systems. Problems of interest include the prediction and integration of variable and uncertain resources such as those arising from the use of renewables, the buffering and storage of electrical energy, demand management, the prediction of critical time scales, and problems imposed by transmission network constraints.
Read more at: www.newton.ac.uk/ofb/ofb012/
1226313

Open for Business: Industry Day
ucs_sms_1191990
http://sms.cam.ac.uk/collection/1191990
Well designed experiments are increasingly being recognised as key components in industrial competitiveness and scientific innovation in a variety of areas. In addition, challenges from industry and science continue to provide stimulus for new research directions in the field. This oneday meeting will bring together academic and industrial researchers and practitioners for the interchange of ideas on the design and analysis of experiments.
The programme will include presentations on current and future industrial applications, and both formal and informal discussions. Read more at: http://www.newton.ac.uk/ofb/ofb010/
1191990

Open for Business: Maths meets Molecular Biology
ucs_sms_1301359
http://sms.cam.ac.uk/collection/1301359
This 'Open for Business' event follows naturally on the recently completed Newton Institute Workshop "Topological Aspects of DNA Function and Protein Folding", which focussed on the topology of DNA strands and polypeptide chains, and the mechanisms by which the topology can change through the action of sitespecific recombinases and topoisomerases. Some key results from this workshop will be reported, and will be followed by keynote lectures by the Master of St John's College, Cambridge and the Masterelect of Trinity College, Cambridge
More info @ www.newton.ac.uk/ofb/ofb014/
1301359

Open for Business: Medical Imaging Day
ucs_sms_1162770
http://sms.cam.ac.uk/collection/1162770
The afternoon will include presentations by a range of distinguished speakers from academia, clinical practice and medical imaging companies. Tissue images never before seen will be shown. These have been the result of research on next generation hybrid imaging modalities and the solution of the corresponding inverse problems. New mathematical registration techniques are at the core of a comercial product aimed at colorectal cancer prevention. As well, imaging is used in novel approaches to drug development. These lectures aim to encourage exchange of information and discussion on possible collaboration between academia and industry on future challenges in medical imaging.
This event is an Open for Business event is embedded in the workshop Analytic and Geometric Methods in Medical Imaging which is part of the Inverse Problems (INV) programme. Read more at: http://www.newton.ac.uk/ofb/ofb009/
1162770

Open for Business: Pharmaceutical Day
ucs_sms_1162768
http://sms.cam.ac.uk/collection/1162768
The day will include presentations describing the current attempts to use Design of Experiment to overcome the recognised inefficiencies of traditional drug development. The new challenges in implementing Design of Experiment in clinical trials will be a basis for discussion and exchange of information among researchers from pharmaceutical companies and academia.
This Open for Business day is embedded in the Design of Experiments in Healthcare workshop which is part of the Design and Analysis of Experiments programme. Read more at: http://www.newton.ac.uk/ofb/ofb008/
1162768

Open for Business: Polynomial Optimisation
ucs_sms_1537858
http://sms.cam.ac.uk/collection/1537858
On the afternoon and evening of Thursday 8 August 2013, the Isaac Newton Institute hosted an Open for Business meeting, in collaboration with the Knowledge Transfer Network for Industrial Mathematics. The purpose of the meeting was to give businesses and other organisations an opportunity to interact with international research leaders who have expertise in the modelling and solution of hard discrete and/or nonlinear optimisation problems. It consisted of surveys from academics on the stateoftheart in optimisation, presentations from nonacademic delegates, and a panel discussion.
This event is associated with the programme Polynomial Optimisation, which took place between 15 July  9 August 2013.
1537858

Open for Business: The Future of Quantitative Finance
ucs_sms_637088
http://sms.cam.ac.uk/collection/637088
On the afternoon and evening of Tuesday 2nd June, the Newton Institute will be hosting an Open for Business meeting, in collaboration with the Cambridge Endowment for Research in Finance and the Knowledge Transfer Network for Industrial Mathematics. The day will form part of our previous research programme on "Developments in Quantitative Finance". The purpose of the meeting is to give businesses and other organizations an opportunity to interact with international research leaders on current challenges and developments, and to network with others with similar interests. It is organised around overview talks by experts in quantitative finance, followed by a panel discussion.
637088

Operator algebras: subfactors and their applications
ucs_sms_2408349
http://sms.cam.ac.uk/collection/2408349
The study of subfactors was initiated by Vaughan Jones in the early 1980's, in the theory of von Neumann algebras of operators on Hilbert spaces. Subfactor theory rapidly led to connections with link and 3manifold invariants, quantum groups and exactly solvable models in statistical mechanics reinforcing the connections with physics. Subsequently deep applications and connections have been uncovered with algebraic, topological and conformal quantum field theory, with rapid progress in recent years in these applications. Free probability and planar algebra techniques have been combined to not only construct subfactors but derive matrix model computations in loop models of statistical mechanics.
These developments have led to connections between subfactors, noncommutative geometry and conformal field theory. In particular relationships between conformal nets of factors, twisted equivariant Ktheory, Khomology, KKtheory, fusion and module categories and vertex operator algebras. The Ktheoretic aspect of the programme includes higher twists as higher DixmierDouady twists and the categorification or higher geometry fronts. The search for geometric description of elliptic cohomology has led to relations with conformal field theories and conformal nets.
The programme will focus on these wide ranging applications as well as the underlying structure theory of operator algebras and subfactors. The classification of subfactors of small index has made strides in the last few years, involving the newer planar algebra tools, including the complete classification of subfactors with index values in the interval [4,5] and significant progress between 5 to just beyond 6. However there are very few constructions of subfactors that do not rely on group or quantum group symmetries. The challenge is to understand and even construct these allegedly exotic subfactors in a natural way and realising modular tensor categories as conformal field theories with conformal nets of factors and vertex operator algebras. There is much recent evidence that the Haagerup subfactor for example yields a natural conformal field theory.
2408349

Optimal design of soft matter  including a celebration of Women in Materials Science (WMS)
ucs_sms_3002378
http://sms.cam.ac.uk/collection/3002378
Soft matter systems range from fluids, colloids, to active and biological matter. Such materials have prominent role in Nature and are key to various applications used in our daily lives, from rubbers, paints, adhesives, displays to biological elements and biopharmaceuticals. Modern soft matter is starting to get into the capacity that desired material properties can be controllably designed, with design routes including selfassembly, microfluidics, micro manipulation, genetic encoding, and other. Can such design routes be optimized? Can one design “optimal matter”, of course for some application? Are there mathematical and other tools and methodologies that can lead in such optimal design?
The goal of this workshop is to address challenges in the optimal design of soft matter, identifying the most productive directions for research and applications and discussing the development of new methodological approaches. The workshop will bring together scientists of various backgrounds –from physics, mathematics, engineering, to chemistry to discuss and work in this one week in the stimulating environment of Isaac Newton Institute in Cambridge. The program will consist of invited talks, contributed talks, and posters.
The proportion of women working in selected areas of materials science significantly exceeds the proportion of women working in mathematics more broadly and in recognition of this, we have embedded a Celebration of Women in Materials Science (WMS) programme into this workshop. Finally, the optimal design of matter in general is a topic of growing interest and this workshop aims to contribute to future spectacular advances in the world of complex materials.
3002378

Optimal Vaccination Strategies
ucs_sms_3737221
http://sms.cam.ac.uk/collection/3737221
The huge impact of the COVID19 pandemic across the globe has been met by heroic efforts from the entire scientific community— developing vaccines and delivering them in the most effective manner in order to minimise disease burden and reduce the reliance as much as possible on socially damaging nonpharmaceutical interventions. With quantity and deployment speed of vaccines initially limited, the question of optimal deployment strategy and who to target first, has and continues to be of great importance for policy makers across the globe.
Vaccination has been shown to reduce an individual’s susceptibility, disease severity, length of infectious period, and viral load. These effects correspond to giving direct protection such as by reducing the chance of severe illness, or indirect protection  benefiting the whole population by reducing the spread of infection. It is then not obvious whether to target the vulnerable, such as the elderly and those with health conditions who make up the majority of hospitalisations and deaths, or the younger and healthier population, who may be most responsible for spreading infection.
There is also the problem of disparity between levels of vaccination achieved across the world, which throws up difficult questions regarding vaccine nationalism. From an altruistic perspective there would be significant advantages to minimising health impacts from prioritising the sharing of vaccination beyond pursuing the highest possible levels of internal infection, though even from a purely selfish standpoint reducing the amount of infection worldwide may have considerable benefits for all.
This event is guided by links with the JUNIPER Consortium and is delivered by the RAMP Continuity Network, the follow on to the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative. It brings together modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on COVID19.
3737221

Partial Differential Equations in Kinetic Theories
ucs_sms_870209
http://sms.cam.ac.uk/collection/870209
Kinetic equations occur naturally in the modelling of the collective motion of large individual particle ensembles such as molecules in rarefied gases, beads in granular materials, charged particles in semiconductors and plasmas, dust in the atmosphere, cells in biology, or the behaviour of individuals in economical trading … Generally, huge interacting particle systems cannot efficiently be described by the individual dynamics of all particles due to overwhelming complexity but clearly some input from the microscopic behaviour is needed in order to bridge from microscopic dynamics to the macroscopic world, typically rendered in terms of averaged quantities. This leads to classical equations of mathematical physics: the Boltzmann equation of rarified gas dynamics, the fermionic and bosonic Boltzmann equations and the relativistic VlasovMaxwell system of particle physics, the quantistic WignerPoisson system, to name just a few.
Read more at http://www.newton.ac.uk/programmes/KIT/index.html
870209

Periodic and Ergodic Spectral Problems
ucs_sms_1887034
http://sms.cam.ac.uk/collection/1887034
The main objective of the programme is to bring together specialists in periodic, almost periodic and random problems to discuss recent developments and deep connections between the methods intrinsic for each of these research areas. In the last several years there emerged a number of methods that had originated in one of these topics (e.g. periodic or random operators) but later were successfully used to tackle problems in a parallel area (e.g. almostperiodic). This suggests that these three lines of research have more in common than previously believed, and the interaction between specialists working in each of these areas could lead to a better understanding of ergodic operators and take us closer to solving open problems.
The programme will thus have three major themes: periodic, almostperiodic, and random operators acting in Rd or Zd; operators on manifolds or graphs and more general ergodic operators will be also considered. We also intend to address problems that lie at the interface of the main topics (e.g. "sheared" periodic operators), and applications in other areas of mathematics (e.g. geometry).
At the beginning of the programme, there will be a twoweek long instructional conference with six minicourses of about ten lectures each. The courses will be designed for students and nonspecialists, and will be organised in order to make them accessible to the UK community. Further there will be three workshops evenly spread over the period of the programme to cover more advanced results, each centred around one of the main themes of the programme. However, we do not plan to make these workshops too specialised, and expect that all three themes will be prominently represented at each of them. We plan to organise the programme in such a way that at any time a mixture of experts from at least two areas will be present at the Institute.
The programme has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/20072013) / ERC Grant Agreement n. 291147.
1887034

Phylogenetics
ucs_sms_60
http://sms.cam.ac.uk/collection/60
Phylogenetics is the reconstruction and analysis of trees and networks to describe and understand the evolution of species, populations and individuals. It is widely used in molecular biology and other areas of classification (such as linguistics), and has both led to and benefited from the development of new mathematical, statistical and computational techniques. Although the foundations of phylogenetics were laid down many decades ago, it is currently experiencing an exciting renaissance due to the wealth and types of biological data that are now becoming available. This programme will bring together key researchers in phylogenetics and related areas to further develop this important area of mathematical biology.
The main themes that will be worked on during this programme are new data types in phylogenetics; modelling reticulate evolution; constructing large trees; probabilistic models of evolution; and phylogenetic combinatorics. These themes provide a rich source of mathematical problems in areas such as combinatorics, graph theory, probability theory, topology, and algebraic geometry. Solutions to these problems will provide new insights to questions that are central to contemporary evolutionary biology.
EVENTS:
 Spitalfields Day  Yggdrasil: Reconstructing the Tree of Life
http://www.newton.ac.uk/programmes/PLG/PLG_Spitalfields.html
 Current Challenges and Problems in Phylogenetics
http://www.newton.ac.uk/programmes/PLG/plgw01.html
 Future Directions in Phylogenetic Methods and Models
http://www.newton.ac.uk/programmes/PLG/plgw03.html
 Phylogenetics: New data, new Phylogenetic challenges
http://www.newton.ac.uk/programmes/PLG/plgw05.html
60

Polynomial Optimisation
ucs_sms_1520692
http://sms.cam.ac.uk/collection/1520692
Optimisation problems involving polynomials arise in a wide variety of contexts, including operational research, statistics, probability, finance, computer science, structural engineering, statistical physics, combinatorial chemistry, computational biology and algorithmic graph theory. They are however extremely challenging to solve, both in theory and practice. Existing algorithms and software are capable of solving only very small instances to proven optimality, unless they have some amenable structure, such as sparsity or convexity.
Read more at: http://www.newton.ac.uk/programmes/POP/
1520692

Probability and Statistics in Forensic Science
ucs_sms_2313931
http://sms.cam.ac.uk/collection/2313931
While there have been dramatic advances in the range and scale of forensic techniques used to help solve legal cases, the way that the probative value of forensic evidence is presented in courts is rudimentary and often flawed. In particular, where probative value is presented in probabilistic and statistical terms there have been numerous instances of misunderstanding leading to miscarriages of justice. Yet there are emerging Bayesianbased probabilistic frameworks  for evaluating forensic evidence and combining it with other types of evidence – that have the potential to improve dramatically many aspects of the criminal justice system.
The programme will develop the main research topics in this area, such as the use of Bayesian networks for combining and evaluating multiple types of evidence, and statistical methods for DNA analysis, particularly in the difficult situations that arise in actual cases of forensic detection: mixed, low template or degraded DNA samples or rare Yhaplotypes. We will also examine the role statistical databases play in other types of trace evidence such as fibre analysis, soil analysis, and drug traces on banknotes.
The programme will address the fundamental mathematical, statistical and algorithmic challenges in developing the methods to increase their reliability, and ensure their consistency and applicability to real cases. A small number of well known cases (in which probabilistic issues related to DNA and other types of evidence were critical) will be used as a common vehicle for developing and articulating the research. The programme will also address the problem of lack of consensus on methodology amongst the forensic community, and of conflicting, controversial and widely misinterpreted court authorities on the application and communication of the methods. The major barriers facing the optimal use of mathematics in the courtroom are on three levels: scientific, cultural, and communication. The programme addresses all three types of barriers in an interdisciplinary manner, and includes both research and workshops that consider the problems of introducing the latest scientific knowledge to members of the forensic and legal professions and the task of communicating these ideas to the widest possible public.
A major goal of the programme is to produce a consensual set of guidelines specifying conditions under which specific techniques can be used to provide results and reliability estimates that are sufficiently certain to be presented in court without the risk of being challenged on appeal.
2313931

Quantum Control Engineering: Mathematical Principles and Applications
ucs_sms_1764492
http://sms.cam.ac.uk/collection/1764492
We are currently entering a new technological era in which we are able to build systems whose performance is limited by quantum physical effects and in which it may be possible to exploit nonclassical phenomena in novel ways. To this end, there has been considerable recent interest in engineering quantum systems and at the heart of this is the development of a quantum control theory dedicated to extending classical control to the quantum domain. Examples already utilizing control of one sort or another include quantum electromechanical systems, quantum dots, Cooperpair boxes, superconducting interference devices, ion traps, as well as a large selection of optical devices. It is clear that a mathematical framework is essential for the future development of quantum control as an engineering discipline.
Themes
The aim of the programme is to bring together experimentalists and theoreticians working in quantum engineering to identify the core mathematical issues and challenges ahead. The challenges we wish to focus upon (both from the mathematical and experimental viewpoint) are
Quantum filtering and the application to quantum measurement and metrology
Quantum openloop schemes
Quantum feedback networks and the design of quantum controllers
Quantum statistics and estimation and the connection with filtering and control
Quantum information processing and its relevance to quantum control and error correction
Activities
The nature of this field is strongly crossdisciplinary and we aim to give introductory seminars in the underpinning concepts of quantum open systems modelling, and mathematical control theory. We plan to hold a workshop "Principles and Applications of Control in Quantum Systems 2014" during the programme which will survey the current state of development. We also wish to hold a number of round table discussions focussing on future directions and their exploitation.
1764492

Random Geometry
ucs_sms_1890070
http://sms.cam.ac.uk/collection/1890070
A new frontier has emerged at the interface between probability, geometry, and analysis, with a central target to produce a coherent theory of the geometry of random structures. The principal question is the following: within a given structure, what is the interplay between randomness and geometry? More precisely, does the geometry appear to be random at every scale (i.e. fractal), or do fluctuations "average out" at sufficiently large scales? Can the global geometry be described by taking a suitable scaling limit that allows for concrete computations?
Spectacular progress has been made over the last ten years in this domain. The goal of the programme is to gather experts from probability, geometry, analysis and other connected areas, in order to study aspects of this question in some paradigmatic situations. Topics of particular relevance include the Gaussian Free Field, random planar maps and Liouville quantum gravity, in connection with conformally invariant scaling limits; spin glass models and branching random walks; percolation and random graphs; and random walks on graphs and groups in the case where the geometry is determined by some algebraic ambient structure.
1890070

Recent advances in statistical genetics and bioinformatics
ucs_sms_3776430
http://sms.cam.ac.uk/collection/3776430
The workshop will focus on topics from bioinformatics and statistical genetics. Bioinformatics has grown up around the rapidly expanding databases of DNA sequence, molecular structure and interaction. Understanding the evolutionary and functional relationships between these biomolecules is perhaps the greatest challenge of 21st century science. Advanced statistical methods are becoming increasingly important in this endeavour. The arrival of dense genotyping arrays has provided huge amounts of SNP data which are being used in efforts to map genes associated with complex traits. Statistical methods for designing and analyzing such whole genome scans are beginning to appear, but many open problems remain. The use of SNP data to estimate recombination rates across the genome, to detect evidence of selective sweeps and to infer demographic history has also provided some statistical challenges that will be addressed in the workshop.
3776430

Recovery from the Pandemic: Transport Logistics – Virtual Study Group
ucs_sms_3856216
http://sms.cam.ac.uk/collection/3856216
This threeday virtual study group run by VKEMS aims to bring mathematical scientists and other disciplines together to solve end user defined challenges with the aim of mitigating the impact of COVID19, climate change and the change of regulations on the shipping and supply chain network.
Background
Increased border restrictions, a reduction in the availability of workers and the increased demand for home delivery over the past 2 years has meant that the freight transport network has had to drastically adapt its operations. The consequent impact on the supply chain has been substantial, and can be observed by simply looking at supermarket shelves.
Various stages of the shipping and supply chain network have had to deal with the effects of COVID19, climate change and the change of regulations. These include:
Transport from producers to importers
Importing into the UK  Ports
Transport from ports to supermarkets
Transport from supermarkets to customers
The particular issues faced by the network include:
COVID19
Staff shortages
Restricted use of port facilities
Risk of infection when moving goods/goods contamination
Increased online ordering during lockdowns
Climate
The direct effect of climate on the water ways
The impact of sea levels rising
Increase of storms etc.
Pollution issues
Change in consumer habits:
People are less keen to buy things from across the globe leading to an increase on local sourcing
Reduction in meat consumption
Reduction in fossil fuels  less oil consumption, so less oil will be transported.
Impact of change of regulations on shipping
Staff shortages
Fuel crisis
Change in boarder regulations
Aims and Objectives
The aim of this event is to bring together those working in mathematical modelling, statistics, operations research, logistics and supply chain management and other disciplines together to solve end user defined challenges in transport logistics.
The following challenges will be presented to the study group:
1. Trustworthiness at the border, presented by Mike Brookbanks – Independent Consultant & Visiting Fellow at University of Surrey
This subgroup will look at modelling trust at the UK boarders, focusing on the relationship between the importer and the government.
The reducing friction in International Trade (RFIT) project was initiated in March 2019 and is a step towards a more operationally efficient supply chain network, as it provides transparency in the data between producers, importers and the UK border.
During the study group, we plan to model the relationship between an importer and the UK government. This model is expected to incorporate attributes such a calculative trust and cognitive trust etc., as detailed in the paper: The impact of a blockchain platform on trust in established relationships: a case study of wine supply chains, while also considering uncertainties.
2. Delivering Shore Power, presented by Alex Pepper– Senior Policy Lead  ESG at UK Major Ports Group (UKMPG)
The Department of Transport currently has a call for evidence on shore power and implementing maritime commitments in the Transport Decarbonisation Plan, which can be found here.
The call for evidence looks to see how the government can support the wider implementation of shorepower in the UK andThe delivery of shorepower at ports is often quite challenging, with many ports lacking a clear demand or available electrical capacity to deliver such demand even if it was to exist. Concerns exist as to whether a mandate on shorepower would be appropriate, when the costs can vary significantly from site to site, and there may be other lower cost options that have a greater emission reduction benefit. Is shorepower good value as an emissions reduction scheme for shipping and as a contributor to the Transport Decarbonisation Plan?
A detailed outline of the problems can be found in this document:
Delegate Information
This event will be delivered virtually as part of a Programme of activity by VKEMS. Please note that the names and affiliations of registered delegates will be shared with ICMS and the KTN.
3856216

Retirement event for Prof Papaloizou
ucs_sms_1849424
http://sms.cam.ac.uk/collection/1849424
1849424

RGM follow up
ucs_sms_2784872
http://sms.cam.ac.uk/collection/2784872
The subject of random geometry has evolved considerably during the programme of the same name which took place at the Newton Institute in spring 2015, and in the intervening months. For instance, a unification of the discrete and continuous perspectives for random surface models (eg random planar maps and Liouville quantum gravity) has been greatly advanced; new methods have been introduced in the study of disordered systems and their phase transitions; and new directions of research have emerged such as a rigorous investigation of YangMills models.The goal of the twoweek workshop will be to allow researchers worldwide and from all career stages to catch up on these developments, and to plan for future research directions of the subject by capitalising on recent progress.The workshop will combine a series of minicourses with invited talks (TBA) over a period of two weeks.
2784872

Rothschild Seminars
ucs_sms_57
http://sms.cam.ac.uk/collection/57
NM Rothschild & Sons have generously granted the Isaac Newton Institute an endowment to support visits from preeminent mathematicians around the world. Rothschild Visiting Professors give keynote seminars at the Institute as part of our Rothschild Seminar series.
57

Scalable inference; statistical, algorithmic, computational aspects
ucs_sms_2519802
http://sms.cam.ac.uk/collection/2519802
The complexity and sheer size of modern data sets, of which ever increasingly demanding questions are posed, give rise to major challenges and opportunities for modern statistics. While likelihoodbased statistical methods still provide the gold standard for statistical methodology, the applicability of existing likelihood methods to the most demanding of modern problems is currently limited. Thus traditional methodologies for numerical optimisation of likelihoods, and for simulating from complicated posterior distributions, such as Markov chain Monte Carlo and Sequential Monte Carlo algorithms often scale poorly with data size and model complexity, and thus fail for the most complex of modern problems.
The area of computational statistics is currently developing extremely rapidly, motivated by the challenges of the recent big data revolution, and enriched by new ideas from machine learning, multiprocessor computing, probability and applied mathematical analysis. Motivation for this development comes from across the physical biological and social sciences, including physics, chemistry, astronomy, epidemiology, medicine, genetics, sociology, economics  in fact it is hard to find problems not enriched by big data and the resultant associated statistical challenges.
This programme will focus on methods associated with likelihood, its variants and approximations, taking advantage of, and creating new advances in statistical methodology. These advances have the potential to impact on all aspects of science and industry that rely on probabilistic models for learning from observational or experimental data.
Intractable likelihood problems are defined loosely as ones where the repeated evaluation of likelihood function (as required in standard algorithms for likelihoodbased inference) is impossible or too computationally expensive to carry out. Scalable methods for carrying out statistical inference are loosely defined to be methods whose computational cost and statistical validity scale well with both model complexity and data size.
Understanding and developing scalable methods for intractable likelihood problems requires expertise across statistics, computer science, probability and numerical analysis. Thus it is imperative that the programme be broad, covering statistical, algorithmic and computational aspects of inference. The programme will cut across the traditional boundary between frequentist and Bayesian inference, and will incorporate both statistics and machine learning approaches to inference. Central to the focus will be the close integration of algorithm optimisation with the opportunities offered, and constraints imposed by modern multicore technologies such as GPUs.
The first week of the programme will feature a broadfocused workshop, and more application specific activities will take place later.
2519802

Scaling limits, rough paths, quantum field theory
ucs_sms_2822164
http://sms.cam.ac.uk/collection/2822164
The goal of statistical mechanics is to calculate the properties, at macroscopic length scales, of a system composed of a large number of interacting microscopic subsystems. To formalise having a large ratio between largest and the smallest length scales, limits such as infinite volume limits, hydrodynamic limits and scaling limits are studied. These limits are random fields or, in cases where there is dynamics, solutions of nonlinear partial differential equations driven by white noise. Such limits can have symmetries that are not present before taking the limit; for example infinite volume limits may be translation invariant and scaling limits by construction are scale invariant. Increased symmetry leads to very special, beautiful, objects such as euclidean quantum field theories and specific partial differential equations driven by white noise. Then statistical mechanical models can be classified into universality classes characterised by these limits. We think of this as a search for far reaching extensions of the central limit theorem and the theory of large deviations. The possible limits are characterised by very few parameters. A new feature of these extensions is that limits have to be expressed in the correct variables because divergences are inherent in limits that have enhanced symmetries. This is the famous problem of renormalisation in quantum field theory. Divergences arise from the volume of noncompact symmetry groups of translations and dilations. Likewise for partial differential equations driven by white noise divergences appear in naive attempts to define the nonlinear terms in the equations. The solutions are too rough to permit ordinary pointwise multiplication. In the last few years, the theory of rough paths, existence, uniqueness and large deviations for singular partial differential equations has been making very rapid progress. Our four month program has been designed to foster a natural alliance with mathematical quantum field theory, specifically the theory of the renormalisation group, continuation in dimension, operator product expansions and conformally invariant quantum field theory. We aim for progress in global existence of solutions of stochastic pde, dynamical critical exponents, equilibrium critical exponents, bosonisation in two dimensions, better and more complete constructions of euclidean quantum fields.
2822164

Semantics and Syntax: A Legacy of Alan Turing
ucs_sms_1200622
http://sms.cam.ac.uk/collection/1200622
The year 2012 sees the 100th anniversary of the birthday of Alan Turing, who made fundamental contributions to our research areas and worked within both the semantic/computational and syntactic/symbolic paradigms, and managed to combine them in various applications using an integrated methodology.
Read more at: http://www.newton.ac.uk/programmes/SAS/
1200622

Sir Michael Atiyah: Forays into Physics
ucs_sms_3087052
http://sms.cam.ac.uk/collection/3087052
Confirmed speakers are:
Sir Roger Penrose: "Michael Atiyah's roles in the drive towards a twistor theory of physics"
Nigel Hitchin: "Gravitational instantons and cubic surfaces"
Paul Sutcliffe: "Solitons and points"
Matilde Marcolli: "Anyons, networks, and codes in geometric models of matter"
Nick Manton: "Skyrmions"
3087052

SocioEconomic Determinants of Coronavirus in the UK
ucs_sms_3856218
http://sms.cam.ac.uk/collection/3856218
Background
The transmission dynamics of infectious diseases are inevitably influenced by inequality, poverty and social determinants of health. Health disparities or inequalities will result in unequal burdens across a country’s population in terms of economic impact, morbidity and mortality. The coronavirus pandemic is no exception, arguably highlighting and perhaps widening decades of health inequalities.
Intriguingly realtime monitoring, using for example public health data, of the evolving pandemic in the United Kingdom is revealing some apparent socioeconomic anomalies that are counterintuitive. In particular, during certain epochs the most disadvantaged groups have the highest incidence of COVID19, conversely at other times the highest incidence is reported by the more privileged groups. The precise mechanisms behind this switching of the highest case incidence between the least and most disadvantaged groups remains an open question.
The synergy between infectious disease transmission and socioeconomic determinants ideally should not only be accounted for by policymakers but also by mathematical models which aim to inform policy decisions. This drives a need for the next generation of epidemiological models to reach beyond the traditional boundaries of contagion and mortality dynamics to include the socioeconomic characteristics of the underlying population.
This virtual event is guided by links with the JUNIPER Consortium and is delivered by the RAMP Continuity Network, the followon to the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative. It will bring together modelling expertise from a diverse range of disciplines to support the pandemic modelling community already working on COVID19.
Aims and Objectives
This oneday virtual workshop aims to facilitate communication between epidemiologists, social scientists, mathematical modellers and public health policy makers. It will do this by giving an overview of the emerging socioeconomic patterns seen through the lens of the UK COVID19 public health data, as well as discussing the socioeconomic factors from both a public health and social science perspective.
Participants will have the opportunity to raise questions following each presentation. There will also be a facilitated Q&A Discussion at the end of the day where individuals will have the opportunity to table further questions and share thinking.
3856218

Soft Matter Materials  Mathematical Design Innovations
ucs_sms_2987807
http://sms.cam.ac.uk/collection/2987807
Background
Mathematics is a key enabler in ensuring that technological advances in complex materials continue. It is integral to the design of various classes of materials, from solids, through to soft matter types. There is however, a need to improve theoretical understanding and modelling in this area, which to date, has so far been quite inadequate. Mathematical modelling can help to speed up complex material development, as well as promoting greater potential of actual applications.
Soft matter materials include liquids, colloids, polymers, foams, gels, granular materials, liquid crystals and a number of biological materials.They have a number of shared characteristics including their ease of deformation by external forces, the relatively large role of thermal fluctuations, and their being governed by unifying physical principles arising from the geometry, topology and qualitative behaviour of their microscopic components. Often their properties are universal, regardless of their detailed molecular or chemical character.
This knowledge exchange workshop is part of the six months Research Programme at the Isaac Newton Institute (INI) on The Mathematical design of new materials. It follows on from a similar event which featured solid complex materials in February and brings together mathematicians and scientists working in various areas of materials science and applied mathematics in order to initiate a systematic study of the optimal design of new complex materials.
Aims and Objectives
This workshop aims to highlight the importance of stateofart mathematical modelling for complex soft matter material development. Models and basic understanding is not just of theoretical interest, but indeed is a key requirement for being able to access and further develop the true potential of these materials  to optimise them, to combine them into new materials, and to use them for creating new devices, with predefined abilities and behaviours. This will be reflected in a progamme for the day which will include talks representing academic research and endusers perspectives from a number of industries and application areas. The three sessions will cover:
Photonics and electronics
Biological sciences and drug design
Novel soft matter materials
The focus for the day is on complex soft matter materials. Talks from academic and industry speakers will cover a number of interesting materials design advances and challenges in areas such as:
Development of highperforming displays, including using transistor technologies for flexible displays and thin film applications
Advanced material design  including concepts of topology and mathematics and harnessing control of the flow of light at the microscopic scale
Mathematical tools to develop novel biological drugs
How processes in the development of drug design can be optimised
There will also be a session on novel soft matter materials. Talks will highlight areas such as sensors, insulating materials, DNA based matter, selfhealing materials with exchangeable bonds solids, plamonics.
This workshop will bring together mathematicians and scientists working in various areas of soft matter/materials science, with end users from industry to further investigate opportunities in mathematical modelling to enable optimal design of complex new materials.
2987807

Spectral Theory of Relativistic Operators
ucs_sms_1280971
http://sms.cam.ac.uk/collection/1280971
Relativistic operators are used to model important physical systems which include transport properties of graphene, and relativistic quantum field theory. This meeting will focus on the following areas of current research interest in such operators applied to mathematical physics.
Read more at: www.newton.ac.uk/programmes/SRO/
1280971

Statistical Challenges Arising from Genome Resequencing
ucs_sms_864293
http://sms.cam.ac.uk/collection/864293
The current generation of highthroughput genetic and genomic platforms, has had a great impact on biomedical research, and given new impetus to studies of molecular mechanisms of genetic disease, and to systems biology. The next big technological step forward is the advent of cheap, fast, sequencing platforms that will allow nearcomplete genome sequences to be quickly and affordably obtained from individual members of any species. Individual genomes from humans, their pathogens and model organisms will have an enormous impact on population genetics and evolutionary theory, as well as on epidemiology, particularly our understanding of infectious disease.
Read more at: http://www.newton.ac.uk/programmes/CGR/index.html
864293

Statistical scalability
ucs_sms_2647052
http://sms.cam.ac.uk/collection/2647052
Programme Theme
We are living in the information age. Modern technology is transforming our ability to collect and store data on unprecedented scales. From the use of Oyster card data to improve London's transport network, to the Square Kilometre Array astrophysics project that has the potential to transform our understanding of the universe, `Big Data' can inform and enrich many aspects of our lives. Given the prospects of transformational advances to standard practice in a plethora of datarich industries, government agencies, science and technology, it is unsurprising that Big Data is currently receiving such a high level of media publicity.
Of course, the important role of statistics within Big Data has been clear for some time. However the current tendency has been to focus purely on algorithmic scalability, such as how to develop versions of existing statistical algorithms that scale better with the amount of data. Such an approach, however, ignores the fact that fundamentally new issues often arise, and highly innovative solutions are required. In particular, the thesis of this programme is that it is only by simultaneous consideration of the methodological, theoretical and computational challenges involved that we can hope to provide robust, scalable methods that are crucial to unlocking the potential of Big Data.
2647052

Statistical Scalability for Streaming Data
ucs_sms_2774952
http://sms.cam.ac.uk/collection/2774952
The profusion of sensorbased technologies in research and industrial systems is having a major influence on our ability to derive realtime insight and understanding about the world around us. However, this deluge of data streams also brings with it significant statistical challenge.
In the past, there has been a tendency to focus purely on algorithmic scalability. However, increasingly we find new statistical challenges arising, requiring novel solutions. For example, the statistical analysis of data streams can involve computational and memory constraints due to a need to process data at source on limited hardware. An alternative challenge can arise with the problem of synthesizing information across multiple related streams, such as those observed in digital networks. Research is therefore needed to find more robust and effective methods for scaling data and, in particular, streaming data.
This workshop is part of the six month programme at the Isaac Newton Institute (INI) on Statistical Scalability. It follows on from a highly successful knowledge exchange workshop in February which focused on Big Data and the role of statistical scalability..
Aims and Objectives
Challenges in streaming data arise in numerous fields – consumer products, financial transactions, computer network traffic, transport and communications networks and energy systems are just some of them. As with statistical scaling generally, this requires an integrated approach.
This knowledge exchange event by the Turing Gateway to Mathematics will harness expertise from the research being undertaken as part of the INI Statistical Scalability Research Programme. It will also highlight experience, expertise and challenges from a number of key stakeholders from the following areas:
Exploration and Geology
Energy and Environment
Communications
The problems faced can often be generic and so have relevance to numerous other sectors and end user applications. Additionally, real applications of streaming data involve specialist streaming infrastructure, hardware and software. It is therefore envisaged that this event will be of interest to a wide audience including those working in multiple business and industrial sectors, Government and the public sector.
2774952

Statistical Theory and Methods for Complex, HighDimensional Data
ucs_sms_76
http://sms.cam.ac.uk/collection/76
Most of twentiethcentury statistical theory was restricted to problems in which the number p of 'unknowns', such as parameters, is much less than n, the number of experimental units. However, the practical environment has changed dramatically over the last twenty years or so, with the spectacular evolution of computing facilities and the emergence of applications in which the number of experimental units is comparatively small but the underlying dimension is massive, leading to the desire to fit complex models for which the effective p is very large. Areas of application include image analysis, microarray analysis, finance, document classification, astronomy and atmospheric science. Some methodological advances have been made, but there is a need to provide firm consolidation in the form of a systematic and critical assessment of the new approaches as well as appropriate theoretical underpinning in this 'large p, small n' context. The existence of key applications strongly motivates the programme, but the fundamental aim is to promote core theoretical and methodological research. Both frequentist and Bayesian paradigms will be featured. The programme is directed at a broad research community, including both mainstream statisticians and the growing population of researchers in machine learning. The methodological issues likely to be covered fall roughly into four overlapping categories:
* strategies for explicit and implicit dimensionreduction, including latentstructure methods, semiparametric models and largescale multiple testing;
* classification methods for complex datasets, including machinelearning methods such as support vector machines;
* asymptotics for increasing dimension, including the application of random matrix theory to highdimensional multivariate methods;
* graphical and other visualisation methods for complex datasets.
EVENTS:
 Contemporary Frontiers in HighDimensional Statistical Data Analysis
http://www.newton.ac.uk/programmes/SCH/schw01.html
 High Dimensional Statistics in Biology
http://www.newton.ac.uk/programmes/SCH/schw02.html
 Inference and Estimation in Probabilistic TimeSeries Models
http://www.newton.ac.uk/programmes/SCH/schw05.html
 Future Directions in HighDimensional Data Analysis
http://www.newton.ac.uk/programmes/SCH/schw03.html
76

Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
ucs_sms_2163645
http://sms.cam.ac.uk/collection/2163645
In the past decades, quantitative biology has been driven by new modellingbased stochastic dynamical systems and partial differential equations. Examples from gene regulation, molecular signalling, cell division and molecular transport, as recently revealed by live cell images, have shown that many processes in cells and in molecular biology are inherently driven by stochastic events. One of the biggest challenges we propose to address in this programme is to develop methods and analysis, as well as efficient algorithms for simulations, to bridge the range of different biological scales. In support of this goal, the programme will focus on
Analysis of stochastic dynamical systems and applications in molecular and cellular biology.
Development of efficient computational methods for simulating stochastic equations over various scales.
Identifying new research areas.
In particular, three interlinked focus areas will run throughout the programme:
Analysis, computation and development of nonspatial (well mixed) models.
Analysis, computation and development of spatiotemporal reactiondiffusion models, including Brownian dynamics and compartmentbased simulations (reactiondiffusion master equation).
Multiscale methods.
The programme will feature an opening, midterm and closing workshop at the Isaac Newton Institute, as well as a Satellite Meeting.
2163645

Stochastic Partial Differential Equations
ucs_sms_722590
http://sms.cam.ac.uk/collection/722590
Stochastic Partial Differential Equations are used to model many physical systems subjected to the influence of internal, external or environmental noise. They also arise when considering deterministic models from random initial conditions, or as tractable approximations to complex deterministic systems. In many cases the presence of noise leads to new phenomena with many recent examples in the physical sciences, biology and financial modelling.
www.newton.ac.uk/programmes/SPD/
722590

Stochastic Processes in Communication Sciences
ucs_sms_726388
http://sms.cam.ac.uk/collection/726388
Probability theory and communications have developed hand in hand for about a century. The research challenges in the latter field (from telephone networks to wireless communications and the Internet) have spurred the development of the mathematical theory of stochastic processes, particularly in the theory of Markov processes, point processes, stochastic networks, stochastic geometry, stochastic calculus, information theory, and ergodic theory—to name but a few. Conversely, a large number of applications in communications would not have been possible without the development of stochastics.
www.newton.ac.uk/programmes/SCS/
726388

Strong Fields, Integrability and Strings
ucs_sms_59
http://sms.cam.ac.uk/collection/59
Two central theories in modern theoretical physics are gauge fields and strings. Quantum gauge fields form the basis of the standard model of elementary particle physics, and are also rich mathematically  indeed, a rigorous derivation of their spectrum is one of the Clay Institute's seven millennium prize problems in mathematics. String theory potentially unifies quantum physics with gravity, and has offered a rich vein of mathematical exploration for over thirty years. Right from the early days, when string theory was envisaged as a model of strongly interacting particles, and more recently exemplified in the AdS/CFT correspondence, it has been clear that there is a close and rather mysterious relationship between the two.
The programme starts with some open issues in QCD, the gauge theory of quarks and gluons. Both conceptual issues such as dynamical mass generation and color confinement, and phenomenological ones such as properties of the quarkgluon plasma studied in ultrarelativistic ion collisions and the nature of matter at high baryon density, can be tackled by a variety of nonperturbative approaches involving lattice simulations, the properties of topologically nontrivial solutions of the YangMills field equations, or random matrix models.We then consider more theoretical questions, in particular involving supersymmetry and largerank gauge groups, where pure N = 1 supersymmetric YangMills theories (SYM) are directly connected with QCD. The increased analytic control offered by such models coupled with new techniques based on duality symmetries have enabled many exciting new, exact results in recent years, including bounds on transport coefficients which may potentially inform RHIC phenomenology. The same ideas, for varying degrees of supersymmetry, naturally recur in matrix models and string theory, and lead on to the central theme of the programme, the gauge/string correspondence. A recent feature of this has been the ubiquitous appearance of 'integrability', the exact solubility of certain classical and quantum models. Integrability appears on both sides of the AdS/CFT correspondence, with spinchain techniques enabling the calculation of anomalous dimensions in the N = 4 SYM which match string states which are those of classical integrable systems, while the hidden symmetries of the full AdS string sigma models are yet to be unravelled. Another important recent development is the reformulation of weaklycoupled YangMills theory as a string theory in twistor space, leading to a resurgence in the application of stringinspired techniques to perturbative calculations in gauge theories.
The programme thus encompasses a broad sweep of interests and techniques, from stronginteraction phenomenology and lattice simulation through theoretical aspects of gauge fields and strings to integrability. In our view there has never been a more fertile time for workers from different ranges of this spectrum to interact and exchange ideas and insight. The programme will be supplemented by workshops on Deconfinement in QCD (in August) and Integrability and the gauge/string correspondence (December) and a school on Gauge fields and strings (September).
59

Supersymmetry Breaking in String Theory
ucs_sms_1671911
http://sms.cam.ac.uk/collection/1671911
Supersymmetry breaking in string theory is a crucial issue, both for formal and more applied aspects within string phenomenology, and in string theory more generally. Any string theoretic setup aiming at addressing phenomenological issues, both in particle physics and in cosmology, has to address supersymmetry breaking. On the other hand, supersymmetry is so deeply rooted in string theory that it is difficult to break it without spoiling many desirable features, or at least without losing analytical control. For instance, stability of nonsupersymmetric solutions or frameworks in string theory is often an unresolved issue.
This workshop is aimed at bringing together experts in the field, to discuss the current status of supersymmetry breaking in string theory and future directions of the field. There will be morning sessions with overview talks and a discussion session. The afternoons are reserved for individual discussions as well as shorter talks on more specialised subjects.
Supported by:
•European COST Action "The String Theory Universe"
•Science and Technology Facilities Council
•ESF Holograv Network
1671911

SwinnertonDyer Memorial
ucs_sms_3528691
http://sms.cam.ac.uk/collection/3528691
Workshop
17th May 2021 to 20th May 2021
Organisers:
JeanLouis ColliotThélène
Miles Reid
Workshop theme:
We are organising a three day meeting in honour of Professor Sir PeterSwinnertonDyer who died in December 2018 at the age of 91.
SwinnertonDyer was one of the most influential number theorists of his generation worldwide. He is probably best known for the famous conjecture of Birch and SwinnertonDyer (one of the Millenium Clay Maths Problems), which relates the arithmetic of elliptic curves to the value of its HasseWeil Lfunction. This conjecture gave rise to a huge field of research relating special values of Lfunctions to arithmetic data. SwinnertonDyer was also one of founding figures in the arithmetic of surfaces and higherdimensional varieties, such as localtoglobal principles for rational points over number fields. He obtained fundamental results for conic bundles and cubic surfaces, and started the research of rational points on surfaces fibred into elliptic curves using completely new methods.
The meeting aims to celebrate the tremendous and widereaching contributions to mathematics of the late Sir Peter SwinnertonDyer. In the early years of the Newton Institute, SwinnertonDyer served as honorary executive director under Michael Atiyah.
The workshop is part of the LondonParis Number Theory Seminar series and is supported by the London Mathematical Society.
Speakers
Bryan Birch
Martin Bright
Tim Browning
John Coates
Henri Darmon
Lillian Matthiesen
Barry Mazur
Emmanuel Peyre
Alexei Skorobogatov
Rodolfo Venerucci
Claire Voisin
Olivier Wittenberg
Sarah Zerbes
Please find the timetable for the event here: Timetable
3528691

Symplectic geometry  celebrating the work of Simon Donaldson
ucs_sms_2543280
http://sms.cam.ac.uk/collection/2543280
14th August 2017 to 18th August 2017
Organisers: Richard Thomas (Imperial), Dusa McDuff (Barnard), Dietmar Salamon (ETH Zürich), Paul Seidel (MIT), Nicholas Woodhouse (ex officio, Clay Mathematics Institute)
Workshop Theme
A weeklong meeting of the world's experts in symplectic geometry and neighbouring fields. We will be celebrating the 60th birthday of Sir Simon Donaldson FRS and his profound influence on the subject. A characteristic of both his work and this meeting will be the influence of (and on) other fields, such as low dimensional topology, algebraic geometry, geometric analysis and theoretical physics. This is a joint INI  CMI workshop.
The organisers expect that additional funding from the NSF will be available to support the participation of USbased researchers. Participants interested in being supported from that NSF grant need to fill out a separate application for that, see https://tinyurl.com/SYGW05
Speakers to include:
Mina Aganagic (Berkeley)
Sir Michael Atiyah (Edinburgh)
Denis Auroux (Berkeley)
Kenji Fukaya (Stony Brook)
Mikhail Gromov (IHES, Paris)
Nigel Hitchin (Oxford)
Eleny Ionel (Stanford)
Frances Kirwan (Oxford)
Peter Kronheimer (Harvard)
Dusa McDuff (Barnard)
Emmy Murphy (MIT)
Tom Mrowka (MIT)
Peter Ozsváth (Princeton)
John Pardon (Princeton)
Zoltán Szabó (Princeton)
Paul Seidel (MIT)
Ivan Smith (Cambridge)
Song Sun (Stony Brook)
Thomas Walpuski (MIT)
Katrin Wehrheim (Berkeley)
2543280

Systemic Risk: Mathematical Modelling and Interdisciplinary Approaches
ucs_sms_1781904
http://sms.cam.ac.uk/collection/1781904
The recent financial crisis has underlined the importance of financial stability and systemic risk in the financial sector, and the monitoring and regulation of systemic risk has become a major concern for regulators, governments and financial institutions. Insights from the crisis include the importance of interconnectedness among financial institutions and markets, the insufficiency of monitoring the stability of individual financial institutions and the necessity of adopting a systemwide view of stability and risk. Useful insights may also be gained from analogous problems related to the large scale (in)stability of systems with many interconnected components and feedback loops in other disciplines.
Read more at http://www.newton.ac.uk/event/syr
1781904

Taming Uncertainty in Mathematical Models Used in the Private and Public Sectors
ucs_sms_2660159
http://sms.cam.ac.uk/collection/2660159
Background
Understanding how uncertainty affects real decisionmaking is an essential part of developing uncertainty quantification (UQ) as a useful intellectual discipline. On the industrial and commercial side, uncertainty arising from the increasing use of computer modelling affects decisions in areas such as new technology, design, manufacturing, longterm infrastructure investment and insurance. In the public sector, there are very topical issues on health and safety.
Uncertainty quantification is a broad phrase used to describe methodologies for taking account of uncertainties when mathematical and computer models are used to describe realworld phenomena. The scientific challenges of modern life, the recent rapid growth in computing power and the demand for more accurate and precise predictions in areas affecting improved infrastructures, public safety and economic wellbeing have spawned a recent surge in UQ activity. New UQ methodologies have and are continuing to be developed by statisticians and applied mathematicians independently.
This event is part of the six month Programme at the INI on Uncertainty Quantification for Complex Systems: Theory and Methodologies and concentrated on how to handle uncertainty arising from the use of mathematical models.
Aims and Objectives
This knowledge exchange event by the Turing Gateway to Mathematics opened up the discussion to a wide audience, including those working in biotechnology, healthcare, medicine, manufacturing, finance, defence, engineering, security, Government and the public sector.
The introductory talks highlighted the key issues raised from the Programme so far and summarised the outputs from the initial workshop on key Uncertainty Quantification methodologies.
Three enduser sessions included talks from the engineering, financial and healthcare sectors. Speakers described how uncertainty is managed at present in their organisations and the challenges they face. Each session included time for discussion and feedback from the audience.
The main aims of the day were:
Describe how uncertainty is managed at present in a number of organisations.
Try to capture what is required from an operationally useful methodology of uncertainty in the future.
Explore if we can crossfertilise, for example, between engineering, finance and medicine.
Ask which current methodologies will be most relevant and can we see over the horizon?
Discussion was encouraged and the results will feed back into the development of subsequent workshops and also to serve to scope and focus a second satellite meeting that will take place later in the year.
2660159

test collection
ucs_sms_3929980
http://sms.cam.ac.uk/collection/3929980
test col
3929980

The complex analysis toolbox: new techniques and perspectives
ucs_sms_3059064
http://sms.cam.ac.uk/collection/3059064
This core workshop will focus on the complex analysis “toolbox” and showcase the many new techniques and mathematical ideas, within the area of complex analysis that have arisen over the past few years. Among key themes are the unified transform method of Fokas and coworkers, advances in the WienerHopf method, new analytical and computational methods for RiemannHilbert problems, advances in numerical conformal mapping and spectral theory.
3059064

The Flip Side of the Pandemic: Recent Advances in the Mathematics of Information
ucs_sms_3536122
http://sms.cam.ac.uk/collection/3536122
Thursday 20th May 2021
A Research Conference of the Cantab Capital Institute for the Mathematics of Information
Background
The Cantab Capital Institute for the Mathematics of Information (CCIMI) were pleased to announce its fifth annual academic conference, which focused on the academic advances in the mathematics of information.
Launched in 2016, CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is of the highest international level, aiming to extract the relevant information from large and highdimensional data with a predictable certainty.
This event followed previous successful academic and industrial engagement events, which focused on different aspects related to the mathematics of information.
Aims and Objectives
The conference brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI specifically related to understanding and modelling the Coronavirus pandemic and associated challenges. Additionally, it highlighted other potential collaborative opportunities, as well as projects being developed elsewhere related to data analysis.
There was a session of short “elevator pitches” from next generation researchers as well as a poster session by some registered delegates.A prize for the most enlightening poster by an ECR was awarded to Paolo Campodonico.
This event was of interest to participants including economists; social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied & computational analysis; quantum computing, cryptography, communication & security and those from data processing.
3536122

The Future of Distributed Ledger Technology
ucs_sms_3095163
http://sms.cam.ac.uk/collection/3095163
Background
Distributed Ledger Technology (DLT) and its numerous potential applications has gained increasing attention in recent years. The UK showed early interest in the technology and through strong research effort is now recognised as a global player. Following rapid changes in the sector worldwide in the last few years, other countries including China, Denmark, Japan, Switzerland and the USA have also made significant impacts.
Beyond cryptocurrencies (such as Bitcoin), DLT has value in applications which require chains of provenance, attestation of data and decentralised trust for IoT devices for instance. According to a report by the UK’s Digital Catapult, it is envisioned that the commercial model most likely to succeed in the short term is permissioned, rather than permissionless blockchain. This is where ledgers are hosted between known groups of participants and visibility, access and editing rights to shared data are regulated. Some key areas highlighted as being particularly promising include supply chain traceability, smart contracts (software programmes executing across distributed networks) and Govtech (Government data that must be secure but needs to be shared with and accessible by others).
The mathematical sciences have a key role to play in helping to realise the potential of DLT and move the technology forward. The mathematics that underpins distributed ledgers is not trivial: not only does the technology rely on cryptography, but robustness and security of the protocol relies on the mathematical behaviour of the system. Moreover, new functionality such as smart contracts are realised through cuttingedge advances in cryptography, and the need to develop alternatives to energyexpensive proofofwork calls on careful mathematical engineering.
Aims and Objectives
This workshop is a collaboration with GCHQ, the Digital Catapult and the Engineering and Physical Sciences Research Council ( EPSRC). In recognition of the potential and possibilities of DLT as a technology for both Government and the UK as a whole, it aims to support appropriate use cases and promote research into scalable DLT. This is set against the backdrop that DLT has sometimes been mooted as a solution to technical problems, where it isn’t appropriate and there is a need to separate the reality from the hype in order to better understand what the technology can really do. It will also serve to bring together stakeholders (research and end users) from multiple communities, to help connect people and build closer links and collaborations to strengthen the community.
There is a recognised need to explore appropriate applications beyond crypto currencies and a key feature of the day will be to highlight a number of use cases across various research areas and applications. A mixture of talks and discussion will be split across four sessions to include:
An overview – current situation, a national perspective
Research areas and applications – archives of digital public records, foundations of distributed ledgers, human centred design, DLT in central banks
Challenges and future opportunities – legal/standards framework and general data protection regulations implications, UK Government perspective, vision and framework for the future
Vision and Future Strategy
The day will finish with a Panel Discussion which will aim to explore issues around the vision and future strategy for DLT.
3095163

The mathematical design of new materials
ucs_sms_2901231
http://sms.cam.ac.uk/collection/2901231
Programme
3rd January 2019 to 28th June 2019
Organisers:
Arghir Zarnescu BCAM  Basque Center for Applied Mathematics, Institute of Mathematics of the Romanian Academy
Xian Chen Hong Kong University of Science and Technology
Miha Ravnik University of Ljubljana, Jozef Stefan Institute
Valeriy Slastikov University of Bristol
Above image: "Martensitic Material", an experiment of Tomonari Inamura's group.
Many recent and spectacular advances in the world of materials are related to complex materials having extraordinary and unique features, usually determined by their specific microstructure. Such materials are key to much technology appearing in our daily lives: they are in liquid crystal displays, in miniaturised phones, special steels in cars, plastics and composites in the construction of modern airplanes, in biological implants in human bodies, and so on.
However, despite the impressive technological applications of these materials, the theoretical understanding and modelling of them are still inadequate.The need for models and basic understanding is not just of theoretical interest, but indeed a key requirement for being able to access and further develop the true potential of these materials, to optimise them, to combine them into new materials, and to use them for creating new devices, with predefined abilities and behaviours.
The current programme aims to bring together mathematicians and scientists working in various areas of materials science and applied mathematics in order to initiate a systematic study of the optimal design of new complex materials, focusing on:
1. Topological metamaterials
2. Colloid composites
3. Composite alloys
4. Layered heterostructures
5. Woven or printed materials
6. Structural optimisation
as the distinct existing attempts from engineering, physics and chemistry. Building on the mathematical areas that are directly relevant to the scientific questions of interest, namely, optimisation and calculus of variations, geometry and topology, continuum mechanics and partial differential equations, the programme aims to identify and study the common principles and techniques of optimal material design that apply more broadly.
2901231

The Mathematics of Deep Learning and Data Science
ucs_sms_2992477
http://sms.cam.ac.uk/collection/2992477
Background
Data science is a fast growing academic discipline incorporating many interdisciplinary areas in engineering, physics and mathematics. Deep learning is now established as a main tool in large parts of modern data science. However, the understanding of deep learning, both from a mathematical and engineering point of view, is somewhat limited. A simple example is the unprecedented success of deep learning in image recognition and classification. This is one of the key problems in computer vision that has to be overcome in order to secure safe use of, for example, selfdriving vehicles.
A fascinating issue is that the performance of deep learning methods for image recognition and classification is now often referred to as super human; however, these methods also become universally unstable. In particular, an image of a cat may be classified correctly, however, a tiny change, invisible to the human eye, may cause the algorithm to change its classification label from cat to a fire engine, or another label far from the original. The big question is why does this happen, can this potentially be dangerous if implemented on a selfdriving car, and can it be fixed?
Aims and Objectives
Basic questions like the one above fuel the need for understanding the science and the mathematics behind deep learning and data science. This knowledge exchange event took place as part of the INI Research Programme on Approximation, Sampling and Compression in Data Science and aimed to highlight both the existing theory and the big unanswered questions regarding the science and mathematics of deep learning.
Inspired by the meeting organised by the National Academy of Sciences on “The Science of Deep Learning”, this one day event aimed to bring people from academia and industry together to discuss the science and mathematics behind deep learning and data science.
The Programme is available and some of the core topics and applications that were emphasised are:
Medical imaging and inverse problems
Approximation theory and properties of neural networks
Optimisation in deep learning and data science
Secure and safe use of deep learning methods.
The workshop featured talks from leading academics, as well as researchers from industry and provided a wide perspective on the many facets of modern data science.
This event was of interest to those working in pure, applied and computational analysis; mathematics; engineering; physics; computer science; big data; data processing; quantum computing; biomedical imaging and medicine; communication and security.
2992477

The mathematics of energy systems
ucs_sms_2898254
http://sms.cam.ac.uk/collection/2898254
Programme Theme
The rapid advance of renewable generation brings fundamental interdisciplinary research challenges. On shorter timescales there are increasing problems of control and optimisation, while new questions of physical and economic design are emerging on the longer investment timescales. Network flows must be managed reliably under uncertain demands, uncertain supply, emerging network technologies and possible failures and, further, prices in related markets can be highly volatile. Drawn from mathematics, economics and engineering, the interdisciplinary participants in this programme will address a range of associated problems, including modelling, prediction, simulation, control, market and mechanism design and optimisation. Our aims are both to develop methodology which is urgent for the next several years and to sow the seeds of a lasting mathematical research agenda.
Research tracks
14  25 Jan: Lookahead operational planning under uncertainty  organised by Pascal Van Hentenryck
28 Jan  8 Feb: Budgeting and scheduling of maintenance and replacement of power system components  organised by Louis Wehenkel
11  15 Feb: Future Electricity Markets – From natural evolutions to disruptive proposals  organised by Pierre Pinson
25 Feb  1st Mar: Data and analytics for shortterm operations  organised by Yannig Goude and Pierre Pinson
1115 March : Moving energy through time: storage and demand side response  organised by Golbon Zakeri and James Cruise
25 – 29 March: Equilibria and computation in markets with risk  organised by Michael Ferris
1  12 April: Pricing and optimization of intraday/dayahead electricity and futures contracts  organised by Florentina Paraschiv
15  18 April: Planning LowCarbon Electricity Systems under Uncertainty Considering Operational Flexibility and Smart Grid Technologies  organised by Pierluigi Mancarella and Rodrigo Moreno
22  26 April: Mechanism Design for the Economics of Future Energy Systems  organised by Ankur Kulkarni
Scientific Advisory Committee
Rene Aid (Paris Dauphine)
Clemence Alasseur (EDF)
Eddie Anderson (Sydney)
Sergey Foss (HeriotWatt)
Ben Godfrey (Western Power Distribution)
Frank Kelly (Cambridge)
Ruediger Kiesel (DuisburgEssen)
Thorsten Koch (Berlin)
JeanYves Le Boudec (EPFL)
David Lenaghan (National Grid)
Jan Maciejowski (Cambridge)
Henrik Madsen (DTU)
Sean Meyn (Florida)
Guy Nason (Bristol)
David Newbery (Cambridge)
Mark O’Malley (Dublin)
Shmuel Oren (Berkeley)
Patrick Panciatici (RTE)
Andrew Richards (National Grid)
Philippe Vassilopoulos (EPEX SPOT)
2898254

The Mathematics of Liquid Crystals
ucs_sms_1383776
http://sms.cam.ac.uk/collection/1383776
Liquid crystals have a multitude of applications, notably those in flat panel display technology, which has fundamentally impacted modern life. From a theoretical point of view, liquid crystals offer a unique opportunity for the study of partial order, as complex liquid crystal phases represent the most wellorganised known states of soft matter.
Read more at: http://www.newton.ac.uk/programmes/MLC/
1383776

The Mathematics of Machine Learning  A Research Conference of the Cantab Capital Institute for the Mathematics of Information
ucs_sms_2757000
http://sms.cam.ac.uk/collection/2757000
Background
The Cantab Capital Institute for the Mathematics of Information (CCIMI) was pleased to announce its second annual academic conference, which focused on the academic interactions taking place related to the mathematics of machine learning.
Launched in 2016, CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is of the highest international level, aiming to extract the relevant information from large and highdimensional data with a predictable certainty.
This event followed previous successful academic and industrial engagement events, which focused on different aspects related to the mathematics of information.
Aims and Objectives
This one day conference brought together those academics working to advance data science and provided an update on research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, it also highlighted projects being developed elsewhere related to machine learning.
The programme of talks covered some of the following areas:
Complexity theory
Signal processing
Partial differential equations
Deep neural networks.
There was a session for short “elevator pitches” from next generation researchers, who also had the opportunity to present more detail about their work in a poster exhibition, which ran during the lunch and the drinks/networking session.
This event was of interest to participants including social scientists; physicists; engineers; biomedical scientists as well as those working in statistics; pure, applied and computational analysis; quantum computing, cryptography, communication and security and those from data processing.
2757000

The Nature of High Reynolds Number Turbulence
ucs_sms_189050
http://sms.cam.ac.uk/collection/189050
Turbulence is a notoriously difficult subject. Our attempts to understand it tend to consist of an uneasy mix of plausible but uncertain hypotheses, deterministic but highly simplified cartoons, and vast, complex data sets.
For the small scales in turbulence this mixture of hypothesis, theory and experiment is given some unity by the phenomenological picture established by Richardson, Taylor and Kolmogorov. This phenomenology paints a picture of cascades of energy and information from largescale eddies down to small, and of universal features of these cascades, provided the Reynolds numbers is large enough. In some sense this vision has worked well, providing a convenient conceptual framework within which many empirical observations can be rationalised. However, it was clear from the outset that this was too simplistic a point of view and half a century later there remain many fundamental unanswered questions. For example, exactly what do we mean by an eddy or a cascade, and how should we interpret cascadelike arguments in terms of the evolving morphology of the vorticity field? Indeed, what is the spatial structure of the vorticity field and how does this relate to the observed energy spectra?
Read more at: http://www.newton.ac.uk/programmes/HRT/
189050

The Painlevé equations and monodromy problems
ucs_sms_3889630
http://sms.cam.ac.uk/collection/3889630
The study of the Painlevé equations has progressed explosively in the last thirty years. At first, the Painlevé equations were studied mainly by the inverse scattering method. Isomonodromic deformations are one of the origins of the Painlevé equations, and the isomonodromy technique is a powerful method to investigate the Painlevé transcendents. Conversely, Painlevé analysis is useful for studying monodromy problems, especially the Riemann–Hilbert problem.
More recently, various new methods have been used to study the Painlevé equations, such as WKB methods, twistor theory, algebraic geometry of initial value spaces, affine Weyl groups, differential Galois groups, symplectic geometry of the moduli space of connections and so on. Equally, the Painlevé equations have many applications, for instance to soliton equations, random matrices, quantum field theory (especially topological field theory), differential geometry of selfdual metrics, etc. Moreover, the Painlevé equations themselves have been generalised to Schlesinger systems, discrete systems and qdifference systems.
H. Poincaré said of Painlevé, "Les mathématiqués constituent un continent solidment agencé, dont tous les pays sont bien reliés les uns aux autres; l'œuvre de Paul Painlevé est une île originale et splendide dans l'océan voisin," but Painlevé's work is now part of the continent and is related to other countries. In this programme, we expect that an understanding of different approaches will bring forth new developments in many fields of pure and applied mathematics. We will gather together experts with various backgrounds, and will share common knowledge.
3889630

The Role of Uncertainty in Mathematical Modelling of Pandemics
ucs_sms_3797085
http://sms.cam.ac.uk/collection/3797085
Background
There is an urgent need to advance the reliability and reproducibility of all forms of computerbased calculations. In an experimental setting, it is often common practice to provide not only measured values themselves, but also an estimate of the uncertainty in the measurements. Yet this is not yet standard practice when presenting predictions made by computational models.
Computational methods are becoming increasingly important for decisionmaking and thus a similar approach is needed to make computational predictions actionable, since virtually all models are contaminated by several sources of uncertainty. Sources of uncertainty originate in the imperfectly known input parameters assumptions made within the mathematical form of the model, and the influence of stochastic effects. Uncertainty quantification is a challenging field that combines scientific models, statistics, highperformance computing, and increasingly machine learning methods.
The mathematical sciences have a key role to play in addressing these challenges. In this event series, the Newton Gateway is working with members of the EPSRCfunded SEAVEA project. The work of the project seeks to address such challenges through the promotion and development of an opensource software toolkit for verification, validation and uncertainty quantification (VVUQ). This is optimised for efficient execution on many platforms including those at the current petascale and the emerging exascale. These capabilities offer new opportunities for simulations in fields as diverse as fusion, weather and climate modelling, epidemiology, advanced materials, biomedicine and many other domains.
Aims and Objectives
A series of three halfday science events is planned between 8th 10th February 2022 which will highlight key aspects of the research, bringing together relevant stakeholders across academia, industry and government. It will be delivered as a RAMP Continuity Network activity.
The event series has a focus on uncertainty modelling for epidemiology and pandemics, but will also highlight new opportunities for simulations in fields as diverse as fusion, weather and climate modelling, advanced materials, biomedicine and many other domains. Sessions will be spread across the three half days as follows:
VVUQ Fundamentals with a Focus on Epidemiology and Pandemics
Wider Applications of VVUQ Methods
Challenges and Advanced Methods for Epidemiological Modelling
3797085

The unity of mathematics: A conference in honour of Sir Michael Atiyah
ucs_sms_3653200
http://sms.cam.ac.uk/collection/3653200
Workshop theme
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Event hashtag: #NewtonAtiyah2021
Sir Michael Atiyah (19292019) was the dominant figure in UK mathematics for many decades. Amongst his many distinguished positions, he was the founding Director of the Isaac Newton Institute (199096). He was also President of the London Mathematical Society (1974 76). In his Presidential Address “The Unity of Mathematics”, delivered on November 19th, 1976, he remarked: “The aspect of mathematics which fascinates me most is the rich interaction between its different branches, the unexpected links, the surprises…”. Those who knew him will know that this fascination was an ongoing theme throughout his life.
The London Mathematical Society spearheaded the idea of a meeting of the same title to celebrate Sir Michael’s immense contributions to mathematics and the mathematical life of this country. It is being organised jointly with the Isaac Newton Institute and has been made possible owing to the generosity of the LMS and the INI, in partnership with the Heilbronn Institute for Mathematical Research, the Clay Mathematical Institute and the Mathematical Institute, Oxford.
The conference will consist of a selection of talks which we trust Sir Michael would have found interesting and which reflect the interactions which he so much appreciated. The speakers cover a broad range of mathematical generations and topics, ranging from number theory to theoretical physics, and include representatives from Oxford, Cambridge, Bonn, Princeton and Edinburgh – places which played a fundamental role at various stages of Sir Michael’s long mathematical life. The presentations should be accessible to a broad audience.
Due to current COVID restrictions in the UK, it is not possible to hold a fully facetoface meeting. It is the intention of the Organisers that the event will take place as a hybrid event, with both facetoface and online participants. However, please note that if there are any further changes to the COVID restrictions in the UK in September, the event may have to be run as a fully virtual meeting. The situation will be reviewed regularly.
All speakers will be online with the exception of Nigel Hitchin, Minhyong Kim, Oscar RandalWilliams, Bernd Schroers and Ulrike Tillmann.
The following organisers and members of the Scientific Committee will be attending the conference online only: Simon Donaldson, Lisa Jeffrey, José FigueroaO’Farrill, Laura Schaposnik and Henry Wilton. In addition to the above list, over 150 further people have registered to participate in the Conference online.
3653200

Theoretical Foundations for Statistical Network Analysis
ucs_sms_2283481
http://sms.cam.ac.uk/collection/2283481
The core of this 6month programme is understanding and quantifying mathematical structure in network models. Networks are ubiquitous in modern science and society. In fact, whenever we observe entities and relationships between them, we have network data. The behaviour of almost all networks, natural or engineered, physical or informationbased, involves a strong component of randomness and is typically not fully or directly observed. Considerable open challenges remain in proving properties both of generative mechanisms for such networks, as well as of methods for inference. This motivates the development of theoretical foundations for statistical network analysis. In support of this goal, the programme aims to:
Identify core problems in the mathematical foundations of networks whose solution will yield generic tools, thus creating a body of coherent and broadly useful results
Build a dialogue between the mathematical fields that will contribute to this foundation, and build a community of researchers spanning these areas
Link these core mathematical problems to important applications, including the modelling and analysis of largescale realworld networks
To support these aims, four interlinked focus areas will run throughout the programme:
Statistical Asymptotics of Networks
Statistical Models for Networks
LargeScale Algorithms
Dynamics in Networks
The programme will feature an opening, midterm and closing workshop at the Isaac Newton Institute, as well as a Satellite Meeting and an Open for Business industry day ( Tuesday 1st November 2016).
2283481

Theory of Water Waves
ucs_sms_1759864
http://sms.cam.ac.uk/collection/1759864
Water waves are a dramatic, potentially dangerous, yet beautiful phenomena that is omnipresent and impacts every aspect of life on the planet. At smaller length scales the ripples driven by surface tension affect remote sensing. At intermediate length scales waves in the midocean affect shipping and near the shoreline they control the coastal morphology and the ability to navigate along shore. At larger length scales waves such as tsunamis and hurricanegenerated waves can cause devastation on a global scale. Across all length scales an exchange of momentum and thermal energy between ocean and atmosphere occurs affecting the global weather system and the climate.
From a mathematical viewpoint water waves pose rich challenges.The governing equations for water waves are a widely accepted model and they have been the subject of a wide range of research. However, the equations are highly nonlinear and the level of difficulty is so great that theory has yet to scratch the surface of the subject. The solutions to the equations that describe fluid motion are elusive and whether they even exist in the most general case is one of the most difficult unanswered questions in mathematics.
On the other hand, there is good reason to be buoyant about the headway that mathematics can make in tackling the great open problems posed by water waves. In light of recent developments the questions are now clearer, new methodologies are emerging, computational approaches are becoming much more sophisticated and the number of researchers at the highest international level involved is growing. All these indicators point to an opportune time to have a focused conference on water waves.
1759864

Top Ten Isaac Newton Institute media items
ucs_sms_1166177
http://sms.cam.ac.uk/collection/1166177
Isaac Newton Institute's Top Ten Videos
1166177

Topological Dynamics in the Physical and Biological Sciences
ucs_sms_1275810
http://sms.cam.ac.uk/collection/1275810
The programme is intended to stimulate interaction between applied mathematicians, biologists and physicists who frequently encounter dynamical problems that have some explicit or implicit topological content. We use the term 'topological' to convey the idea of structures, e.g. knots, links or braids in 3D, that exhibit some measure of invariance under continuous deformation. Dynamical evolution is then subject to the topological constraints that express this invariance. A basic common problem is to determine minimum energy structures (and routes towards these structures) permitted by such constraints; and to explore mechanisms, e.g.diffusive, by which such constraints may be broken.
Read more at: http://www.newton.ac.uk/programmes/TOD/
1275810

Tutorial workshop
ucs_sms_3020410
http://sms.cam.ac.uk/collection/3020410
The tutorial workshop will feature 5 series of introductory lectures, on topics of key importance to the Programme.
The topics and the Lecturers are:
** Algebraic Theory of numerical methods, Kurusch EbrahimiFard (NTNU) and Hans MuntheKaas (Bergen)
** Finite Element Exterior Calculus, Doug Arnold (Minnesota)
** Geometric Numerical Integrators, Chris Budd (Bath)
** Geometric PDE and Finite Element, Charle Elliot (Warwick)
** Differential Geometric methods; Lie groups through to Noether's Theorem, Elizabeth Mansfield (Kent)
To complement these, there will also be Survey lectures covering some of the topics of focus periods of the Programme.
Confirmed speakers are:
*Paola Antonietti (Milan),
*Christian Lubich (Tuebingen),
*Reinout Quispel (LaTrobe),
*Beth Wingate (Exeter).
All lectures will be at the level of a tutorial for postgraduate students.
Activities for participating post graduate students will include a Poster Session and a Panel Discussion on Grand Challenges.
This workshop is a registered satellite meeting of ICIAM 2019, The International Congress on Industrial and Applied Mathematics, to be held at Valencia (Spain), 15th 19th July, 2019.
3020410

Uncertainty Quantification : Recent Advances in the Mathematics of Information
ucs_sms_3926294
http://sms.cam.ac.uk/collection/3926294
3926294

Uncertainty quantification for cardiac models
ucs_sms_2997730
http://sms.cam.ac.uk/collection/2997730
The heart is an electromechanical pump, where contraction is initiated and synchronised by a propagating wave of electrical excitation. The function of the heart can be modelled by systems of coupled and nonlinear differential equations, constrained by conservation laws. These models are multiscale, ranging from representations of electrical activation and force generation in a single cell up to models solved on an anatomical mesh that represent the heart of an individual patient. There are a wide range of potential applications that include assessing the cardiac safety of new drugs, understanding the basic mechanisms of heart rhythm disorders, and providing guidance for clinical procedures on an individual patient. A major obstacle to progress is that the present generation of cardiac models do not take into account the natural variability of real cells and organs, and are difficult to calibrate from the noisy and incomplete images and data that are typically available in the clinical setting.
2997730

Uncertainty Quantification for Complex Systems – Development in Theory and Methodologies
ucs_sms_2772775
http://sms.cam.ac.uk/collection/2772775
Uncertainty quantification (UQ) is a modern interdisciplinary science that cuts across traditional research groups and combines statistics, numerical analysis and computational applied mathematics. UQ methodologies are useful for taking account of uncertainties when mathematical and computer models are used to describe realworld phenomena. This helps to better inform decisions, assess risk and formulate policies across multiple areas as diverse as climate modelling, manufacturing, energy, life sciences, finance, geosciences and more.
The scientific challenges of modern life, along with the recent rapid growth in computing power and the demand for more accurate and precise predictions in areas affecting improved infrastructures, public safety and economic wellbeing have spawned a recent surge in UQ activity. New UQ methodologies have and are continuing to be developed by statisticians and applied mathematicians independently.
The workshop is part of the six month programme at the INI on Uncertainty Quantification for Complex Systems: Theory and Methodologies and will take place towards the end of the Programme, so will focus on disseminating the key outputs and will highlight some potential outcomes that could be taken forward. It follows an earlier event within the Programme that looked at the challenges faced by some specific problem holders.
Aims and Objectives
This knowledge exchange event by the Turing Gateway to Mathematics will feature a number of talks from academia as well as end users. It will provide the opportunity for those from industry and the public sector, to access stateoftheart theory and methods, as well as learn about best practice and help to foster links between the various communities. It will help to further consolidate opportunities for collaboration between statisticians and applied mathematicians
A short introductory talk will provide an overview of the Uncertainty Quantification Research Programme. This will be followed by a number of academic talks that will review progress made over the duration of the Programme, in relation to some of the key research themes including:
Surrogate Modelling
Multilevel and Multifidelity Methods
Dimension Reduction Strategies
Inverse Problems
Design
Two enduser sessions will include talks from the environmental/climate and energy infrastructure sectors. Speakers will describe how uncertainty is managed at present in their organisations and the challenges they face.
This event will be of relevance to individuals from multiple sectors including energy infrastructure, engineering, environmental modelling, manufacturing, Government and the public sector.
2772775

Uncertainty quantification for complex systems: theory and methodologies
ucs_sms_2642478
http://sms.cam.ac.uk/collection/2642478
In areas as diverse as climate modelling, manufacturing, energy, life sciences, finance, geosciences and medicine, mathematical models and their discretisations into computer models are routinely used to inform decisions, assess risk and formulate policies. How accurate are the predictions made using such models? This crucial question lies at the heart of uncertainty quantification (UQ).
UQ is a broad phrase used to describe methodologies for taking account of uncertainties when mathematical and computer models are used to describe realworld phenomena. This includes propagating uncertainty from unknown model inputs to model outputs, the study of uncertainty in the models themselves, developing approximation schemes that result in tractable and accurate computer models, robust design, model calibration and other inverse problems, model bias and discrepancy etc. This programme focuses on UQ for complex systems which have complicated mathematical descriptions such as systems of partial differential equations for which even a single deterministic inversion of an associated computer model is very costly.
The scientific challenges of modern life, the recent rapid growth in computing power and the demand for more accurate and precise predictions in areas affecting improved infrastructures, public safety and economic wellbeing have spawned a recent surge in UQ activity. New UQ methodologies have and are continuing to be developed by statisticians and applied mathematicians independently.
The main aim of the programme is to bring applied mathematicians and statisticians together to formulate a common mathematical foundation for UQ and to establish longlasting interactions that will lead to significant advances in UQ theory and methodologies for complex systems. Participants will work together to develop theories and methodologies for reducing the cost of model inversion, increasing the level of tractable complexity in modelling, and enabling efficient risk assessment and decision making. Five core themes of common interest to statisticians and applied mathematicians will provide the focus. These are:
Surrogate models
Multilevel, multiscale, and multifidelity methods
Dimension reduction methods
Inverse UQ methods
Careful and fair comparisons
2642478

Understanding Microbial Communities; Function, Structure and Dynamics
ucs_sms_1633838
http://sms.cam.ac.uk/collection/1633838
The importance of microbial communities for health, industry and the natural environment cannot be overstated. Despite this, there is an enormous gap between the levels of our empirical knowledge of microbial communities’ composition and experimental and theoretical understanding of their function, structure, and dynamics. Developing and advancing mathematical and computational approaches for the study of microbial communities has huge potentials for this field. The aim of this programme is to build an interactive community of theoretical and empirical scientists that can provide these developments.
Find out more at http://www.newton.ac.uk/programmes/UMC/
1633838

Understanding MultiModal Data for Social and Human Behaviour
ucs_sms_2874075
http://sms.cam.ac.uk/collection/2874075
Deciphering sequential data sets using Rough Path Theory
Background
In an era of data deluge  sensors, cameras, computers and smart phones capture and store an unending torrent of data about human activity. The data is highdimensional, sequential, complex, heterogeneous and multimodal in nature; but the sample size is woefully small in comparison.
New scientific and technological methods are emerging that can sometimes reduce this surfeit of dimension to allow meaningful and useful information to be extracted from data arising from human behaviour; by allowing patterns to be predicted for the first time there are new opportunities for significant societal benefit. These torrents of multimodal streamed data carry vital information in so many areas of human existence. This presents huge opportunities and it is a central goal of statistics and modern computer science to extract meaning and insight in an actionable form from such data.
The field of Rough Paths theory (RPT) is a focus of the four month Research Programme at the Isaac Newton Institute (INI) on Scaling Limits, Rough Paths, Quantum Field Theory. RPT is emerging as a useful data science tool. It has at its core, the ability to describe complex behaviour concisely. RPT is focused on describing evolving systems, and crucially exploits the mathematician’s ability to describe continuous sequential information in terms of the order of events without introducing a parameterisation. This is in essential contrast to conventional ways of describing sequential data, and results in a massive and controlled dimension reduction. The result is a set of simplified descriptions of the stream that are of fixed dimension regardless of the complexity of the path, and often prove extremely well adapted to the application of modern data science techniques, allowing greater sensitivity and better learning.
RP theory has great potential as a mathematical tool to facilitate the use of data science to understand social and human data. It already has a recognised role (along with techniques like deep learning), in the recognition of Chinese handwriting on a mobile device, with billions of complex figure gestures being successfully translated into typographical Chinese characters. It has also been used successfully to differentiate individual diagnoses for mental health conditions such as bipolar disorder using simple noninvasive ‘mood zoom’ diaries from mobile phones and remarkable results have been obtained in several existing data science challenges, including the interpretation of human movement from landmark data extracted from video, etc.
Aims and Objectives
Real benefits to many areas of modern society arise if one can analyse, model and predict different aspects of social and human behaviours. Techniques, such as those offered by RPT, increase the range of potential successes to include recognizing human actions and understanding changing facial expressions.
This workshop aimed to increase awareness of what is possible, whether it be better mitigation of risks, management of outcomes, or supporting individuals in their daily lives, across the spectrum of social and human behaviour.
The programme for the day featured stateoftheart surveys, as well as several shorter presentations on success stories; together these were intended to help endusers to visualise and articulate their own data challenges in this area.
The day also included enduser talks from the security, safety and human health and behaviour areas. It was of interest to a wide range of stakeholders and specifically those who wished to gain greater insight from complex sequential data. The challenges presented by such data occur across the spectrum and so was relevant to multiple application areas and sectors including areas of engineering, security, communications, human health and social sciences areas.
2874075

Understanding the Generation Time for COVID19
ucs_sms_3605987
http://sms.cam.ac.uk/collection/3605987
Background
The generation time of COVID19 is the duration between the moment a person gets infected to the moment they infect another person (i.e. it’s the time between primary and secondary infection). This is very important in the context of new variants which may have different generation times, which in turn would have implications for the estimates of the R number. The generation time is also important for the evolution of new variants.
There are a number of different factors which affect the generation time: the progress of infection within an individual (withinhost modelling), the transmission of infection between individuals by droplets from aerosol or surfaces (environmental & aerosol modelling) and contact patterns between individuals (epidemiology modelling).
Typically, the generation time is estimated from household studies and for COVID19 many of the estimates have come from these studies at the very start of the epidemic. However, with the generation time depending on a number of different aspects, this means generation time is likely to vary between settings, or environmental conditions might allow for super spreading events to occur.
Aims and Objectives
This workshop will focus on understanding the different factors which affect the generation time, as well as the interaction between these, which will be important to be able to better assess what aspects of new variants may be of concern.
The aim of this event will be to hear talks related to each of the factors affecting the generation time, to try to understand current work and thinking in each area and in turn to try to identify how these may be more joined up. A key goal of this event is to build links between epidemic modellers and the wider modelling community with interests in COVID19, such as withinhost modelling teams – including, but not limited to members of RAMPinitiated projects.
This event will be delivered by the Newton Gateway in its key role in the RAMP Continuity Network (a UKRI funded project) to deliver a series of meetings, workshops and virtual study groups that react to key priority areas in the UK’s response to the current pandemic. This event is guided by links with groups such as the JUNIPER consortium and the Isaac Newton Institute Infectious Dynamics of Pandemics research programme to ensure relevance to current UK policy, and will ensure engagement with the wider mathematical modelling and epidemiology communities.
3605987

Unlocking Data Streams
ucs_sms_3459652
http://sms.cam.ac.uk/collection/3459652
Tuesday 16th March 2021
Background
Sequential streams of information are pervasive; things happen and are recorded. These streams can be regular with all channels updating at once like sound. Alternatively, channels can update one at a time and maybe not at all, as things happen. An example of this is an electronic health record – which might capture hospital admission, a blood test, or perhaps a continuing ECG measurement.
Managing this heterogeneous stream of data is a challenge. Often there is important information in the order of events that links the channel behaviour together. In this case smoothing the data out channel by channel, like binning data, is damaging. A powerful unifying approach is to regard the data to be the input, and let it control a dynamical system. Different behaviour can be distinguished via the different responses of the system. One can modify the system so that it is not affected by the aspects of the stream that are of little interest.
With five years funding from UKRI, the DataSıg Programme looked to address this key challenge of data science – to better understand multimodal data streams. It sought to do this by developing mathematical descriptions of these streams, using ‘rough path’ (RP) theory; RP theory allows for the direct capture of the order in which events happen and in many cases can better model the effects of these data streams via a top down signature description of the stream that summarises the data effectively without exposing the individual data points to direct analysis.
The one day workshop highlighted a number of exciting research activities and outlined some of the successful collaborations within the DataSıg Programme. Collaborations included:
Security and defence  action detection using signatures and computer vision to classify physical human actions from real time data
Human computer interfaces – such as translation handwriting on mobile devices
Astronomy – rough path models to aid the development of measurement instruments and processing techniques for astronomy telescopes
Mental health – development of a tool which looks in an automated way at selfreported data (such as speech and mood information). Enables positioning of individuals on spectrums and potentially better feedback for clinicians/clients.
Human disease – identifying the evolution of cancer cell lines and an early warning system for sepsis detection
Aims and Objectives
Our experience of the world is multimodal and understanding multimodal data streams (complex sequences of data from different sources), is a key challenge of rough path theory and more generally for data science. This workshop therefore aimed to increase awareness of the research and applications being undertaken by the DataSıg team. The Programme sought to further develop signaturebased mathematical tools for dealing with complex streamed data, and connect with partners who have the capability and the challenges to benefit from and achieve significant outcomes with the methodology. The meeting was of interest to endusers from multiple settings including, industry, business, public sector and clinicians who were interested in collaborating and who could:
Benefit from the development of useful open sources software tools that could be utilized in various machine learning environments
Have needs around the interaction with complex, real world evolving data, to be able to easily tackle questions where there is a variety of different data to consume.
Talks at this workshop highlighted stateoftheart research and success stories. Presentations featured various examples of rough paths in action, understanding clouds (collections) of paths and their applications, log signals and controlled differential equations, as well as applications and challenges from endusers perspectives. The day was of relevance to multiple application areas and sectors including engineering, agriculture, security, communications, human health and the social sciences.
A programme of this past event is now available. Please follow the link.
3459652

Variational methods and effective algorithms for imaging and vision
ucs_sms_2555223
http://sms.cam.ac.uk/collection/2555223
Programme
29th August 2017 to 20th December 2017
Organisers: Ke Chen (University of Liverpool), Andrew Fitzgibbon (Microsoft Research), Michael Hintermüller (HumboldtUniversität zu Berlin), CarolaBibiane Schönlieb (University of Cambridge), and XueCheng Tai (Hong Kong Baptist University)
Scientific committee: Andrea Bertozzi (UCLA, USA); Andrew Blake (Alan Turing Institute, UK); Tony Chan (HKUST, CHINA); Bill Freeman (MIT, USA); Ron Kimmel (Technion, Israel); David Mumford (Brown, USA); Mila Nikolova (E.N.S. Cachan, France); Stanley Osher (UCLA, USA); Joachim Weickert (Saarland, Germany).
Programme Theme
In our modern society, mathematical imaging, image processing and computer vision have become fundamental for gaining information on various aspects in medicine, the sciences, and technology, in the public and private sector equally. The rapid development of new imaging hardware, the advance in medical imaging, the advent of multisensor data fusion and multimodal imaging, as well as the advances in computer vision have sparked numerous research endeavours leading to highly sophisticated and rigorous mathematical models and theories.
An evidence of this trend can be found in the still increasing use of variational models, shapes and flows, differential geometry, optimization theory, numerical analysis, statistical / Bayesian graphical models, and machine learning. Still, the ever growing challenges in applications and technology constantly generate new demands that cannot be met by existing mathematical concepts and algorithms. As a consequence, new mathematical models have to be found, analyzed and realized in practice.
This fourmonth programme will foster exchange between different groups of researchers and practitioners, who are involved in mathematical imaging science, and discussions on new horizons in theory, numerical methods and applications of mathematical imaging and vision.
2555223

Verified software: from theory to practice
ucs_sms_3521858
http://sms.cam.ac.uk/collection/3521858
Workshop
10th May 2021 to 14th May 2021
Organisers:
Natarajan Shankar SRI International
Leonardo de Moura Microsoft (USA)
Azadeh Farzan University of Toronto
Philippa Gardner Imperial College London, Imperial College London
Kim Larsen Aalborg Universitet
Xavier Leroy Collège de France, INRIA
Ken McMillan Microsoft (USA)
Peter O'Hearn University College London
Peter Sewell University of Cambridge
Moshe Vardi Rice University
Workshop theme
Formal methods for the specification and verification of softwareintensive systems bridge the gap between theory and applications. Verification techniques have to be tuned to application areas such as concurrency, cyberphysical systems, distributed systems, machine learning, computer security, networks, and programming languages. The INI Virtual Workshop is a precursor event to the program on Verified Software. It will involve an intensive exchange of ideas between researchers facing the challenges of cuttingedge applications and theoreticians armed with the conceptual tools to potentially address these challenges.
Given the current restrictions on movement, due to the ongoing pandemic, the INI intends to run this workshop virtually across 5 days. All talks and discussion sessions will be available virtually.
Please find the timetable for the event here: Timetable
3521858

Verified software: tools and experiments
ucs_sms_3550331
http://sms.cam.ac.uk/collection/3550331
VSOW04 7 June 2021 to 11 June 2021
Workshop theme
The Tools and Experiments workshop is aimed at defining an integrated tool resources for automated formal methods with standardized interfaces and interchange and data/evidence formats that allow services and arguments to be composed and test cases and counterexamples to be shared across different formal models. The goal of the INI Virtual Workshop is to lay the foundation for powerful automated tools and integrated tool suites that can be deployed in a range of largescale experiments and case studies.
The workshop will include a special event marking the 60th anniversary of Tony Hoare's invention of Quicksort.
Given the current restrictions on movement, due to the ongoing pandemic, the INI intends to run this workshop virtually across 5 days. All talks and discussion sessions will be available virtually.
Deadline for applications: 20th May 2021
Timetable
3550331

Video Interviews
ucs_sms_2766088
http://sms.cam.ac.uk/collection/2766088
Since August 2017, INI has filmed video interviews with the Organisers of each programme held at the Institute. The aim of these videos is to provide an introduction to the subject of each programme, the challenges inherent within it, and the likely outcomes from the research undertaken.
2766088

Women in Mathematics
ucs_sms_756316
http://sms.cam.ac.uk/collection/756316
With women significantly underrepresented amongst the lecturers in UK university mathematics departments, the London Mathematical Society (LMS) and the Isaac Newton Institute for Mathematical Sciences (INI) are showing how positive action can encourage the next generation of women mathematicians.
The Women in Mathematics Day is an annual event organised by the London Mathematical Society. Sessions at the day include talks and posters by women mathematicians in a variety of appointments and at different career stages.
Topics have included advice on how to get funding for your first postdoc and beyond and discussion groups on subjects such as combining family and career, working overseas and making the next step in your career, and good practice for universities.
Read more at:
http://www.lms.ac.uk/content/womenmathematicsday
http://www.newton.ac.uk/women/
756316
INIMS