Past

The observations of the first traces of cosmic structure in the

Cosmic Microwave Background are in excellent agreement with the

predictions of Inflation. However as we shall see, that account

is not fully satisfactory, as it does not address the transition

from an homogeneous and isotropic early stage to a latter one

lacking those symmetries. We will argue that new physics along the

lines of the dynamical quantum state reduction theories is needed

to account for such transition and, motivated by Penrose's ideas

suggest that quantum gravity might be the place from where

this new physics emerges. Moreover we will show that observations

can be used to constrain the various phenomenological proposals

made in this regard.

Microbial biofilms grow on most rock and stone surfaces and may play critical roles in weathering. With climate change and improving air quality in many cities in Europe biofilms are growing rapidly on many historic stone buildings and posing practical problems for heritage conservation. With many new field and lab techniques available it is now possible to identify the microbes present and start to clarify their roles. We now need help modelling microbial biofilm growth and impacts in order to provide better advice for conservators.

The question of how to derive useful bounds on

arbitrage-free prices of exotic options given only prices of liquidly

traded products like European call und put options has received much

interest in recent years. It also led to new insights about classic

problems in probability theory like the Skorokhod embedding problem. I

will take this as a starting point and show how this progress can be

used to give new results on general Monte-Carlo schemes.

This topic was the subject of an OCIAM workshop on 8th March 2013

given by Nick Hall Taylor . The presentation will start with a review

of the physical problem and experimental evidence. A mathematical

model leading to a hydrodynamic free boundary problem has been derived

and some mathematical and computational results will be described.

Finally we will assess the results so far and list a number of

interesting open problems.

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After the workshop and during coffee at 11:30, we will also give a preview of the

upcoming problems at the Malaysian Study Group (Mar. 17-21). Problem

descriptions can be found here:

www.maths.ox.ac.uk/~trinh/2014_studygroup_problems.pdf.

Several number theorists have stressed that the proofs of FLT focus on small concrete arithmetically defined groups rings and modules, so the steps can be checked by direct calculation in any given case. The talk looks at this in relation both to Hilbert's idea of contentual (inhaltlich) mathematics, and to formal provability in Peano arithmetic and other stronger and weaker axioms.

We study lower- and dual upper-bounds for Bermudan options in a MonteCarlo/MC setting and provide four contributions. 1) We introduce a local least-squares MC method, based on maximizing the Bermudan price and which provides a lower-bound, which "also" minimizes (not the dual upper-bound itself, but) the gap between these two bounds; where both bounds are specified recursively. 2) We confirm that this method is near optimal, for both lower- and upper-bounds, by pricing Bermudan max-call options subject to an up-and-out barrier; state-of-the-art methods including Longstaff-Schwartz produce a large gap of 100--200 basis points/bps (Desai et al. (2012)), which we reduce to just 5--15 bps (using the same linear basis of functions). 3) For dual upper-bounds based on continuation values (more biased but less time intensive), it works best to reestimate the continuation value in the continuation region only. And 4) the difference between the Bermudan option Delta and the intrinsic value slope at the exercise boundary gives the sensitivity to suboptimal exercise (up to a 2nd-order Taylor approximation). The up-and-out feature flattens the Bermudan price, lowering the Bermudan Delta well below one when the call-payoff slope is equal to one, which implies that optimal exercise "really" matters.

I plan to give a non technical introduction (i.e. no prerequisites required apart basic differential geometry) to some analytic aspects of the theory of harmonic maps between Riemannian manifolds, motivate it by briefly discussing some relations to other areas of geometry (like minimal submanifolds, string topology, symplectic geometry, stochastic geometry...), and finish by talking about the heat flow approach to the existence theory of harmonic maps with some open problems related to my research.

I will discuss a novel approach to estimating communication costs of an algorithm (also known as its I/O complexity), which is based on small-set expansion for computational graphs. Various applications and implications will be discussed as well, mostly having to do with linear algebra algorithms. This includes, in particular, first known (and tight) bounds on communication complexity of fast matrix multiplication.

Joint work with Grey Ballard, James Demmel, Benjamin Lipshitz and Oded Schwartz.

We investigate certain (hopefully new) arithmetic aspects of abelian varieties defined over function fields of curves over finitely generated fields. One of the key ingredients in our investigation is a new specialisation theorem a la N\'eron for the first Galois cohomology group with values in the Tate module, which generalises N\'eron specialisation theorem for rational points. Also, among other things, we introduce a discrete version of Selmer groups, which are finitely generated abelian groups. We also discuss an application of our investigation to anabelian geometry (joint work with Akio Tamagawa).

Familiar species; humans, mammals, fish, reptiles and plants represent only a razor’s edge of the Earth’s immense biodiversity. Most of the Earth’s multicellular species lie buried in soil, inside of plants, and in the undergrowth, and include millions of unknown species, almost half of which are thought to be fungi. Part of the amazing success of fungi may be the elegant solutions that they have evolved to the problems of dispersing, growing and adapting to changing environments. I will describe how we using both math modeling and experiments to discover some of these solutions. I will focus on (i) how cytoplasmic mixing enables some species to tolerate internal genetic diversity, making them better pathogens and more adaptable, and (ii) how self-organization of these flows into phases of transport and stasis enables cells to function both as transport conduits, and to perform other functions like growth and secretion.

Adaptive finite element methods (AFEMs) with Dörflers marking strategy are known to converge with

optimal asymptotical rates. Practical experiences show that AFEMs with a maximum marking strategy

produces optimal results thereby being less sensitive to choices of the marking parameter.

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In this talk, we prove that an AFEM with a modified maximum strategy is even instance optimal for the

total error, i.e., for the sum of the error and the oscillation. This is a non-asymptotical optimality result.

Our approach uses new techniques based on the minimisation of the Dirichlet energy and a newly

developed tree structure of the nodes of admissible triangulations.

I will discuss free-by-cyclic groups and cases where they can and cannot act on CAT(0) spaces. I will specifically go into a construction building CAT(0) 2-complexes on which free of rank 2-by-cyclic act. This is joint work with Martin Bridson and Martin Lustig.

I will discuss some very well studied cohomology groups that turn out to be captured by the machinery of critical CoHAs, for example the compactly supported cohomology of singular quiver varieties and untwisted character varieties. I will explain the usefulness of this extra CoHA structure on these groups, starting with a new proof of the Kac conjecture, and discuss a conjectural form for the CoHA associated to untwisted character varieties that provides a new way to think about the conjectures of Hausel and Rodriguez-Villegas. Finally I will discuss an approach to purity for the compactly supported cohomology of quiver varieties and a related approach to a conjecture of Shiffmann and Vasserot, analogous to Kirwan surjectivity for the stack of commuting matrices.

Nature and the world of human technology are full of
networks. People like to draw diagrams of networks: flow charts,
electrical circuit diagrams, signal flow diagrams, Bayesian networks,
Feynman diagrams and the like. Mathematically-minded people know that
in principle these diagrams fit into a common framework: category
theory. But we are still far from a unified theory of networks.

The cohomological Hall algebra of vanishing cycles associated to a quiver with potential is a categorification of the refined DT invariants associated to the same data, and also a very powerful tool for calculating them and proving positivity and integrality conjectures. This becomes especially true if the quiver with potential is "self dual" in a sense to be defined in the talk. After defining and giving a general introduction to the relevant background, I will discuss the main theorem regarding such CoHAs: they are free supercommutative.

State-space models are a very popular class of time series models which have found thousands of applications in engineering, robotics, tracking, vision,  econometrics etc. Except for linear and Gaussian models where the Kalman filter can be used, inference in non-linear non-Gaussian models is analytically intractable.  Particle methods are a class of flexible and easily parallelizable simulation-based algorithms which provide consistent approximations to these inference problems. The aim of this talk is to introduce particle methods and to present the most recent developments in this area.

Pluripotency is a key feature of embryonic stem cells (ESCs), and is defined as the ability to give rise to all cell lineages in the adult body. Currently, there is a good understanding of the signals required to maintain ESCs in the pluripotent state and the transcription factors that comprise their gene regulatory network. However, little is known about how ESCs exit the pluripotent state and begin the process of differentiation. We aim to understand the molecular events associated with this process via an experiment-model cycle.

The revolution in molecular biology within the last few decades has led to the identification of multiple, diverse inputs into the mechanisms governing the measurement and regulation of organ size. In general, organ size is controlled by both intrinsic, genetic mechanisms as well as extrinsic, physiological factors. Examples of the former include the spatiotemporal regulation of organ size by morphogen gradients, and instances of the latter include the regulation of organ size by endocrine hormones, oxygen availability and nutritional status. However, integrated model platforms, either of in vitro experimental systems amenable to high-resolution imaging or in silico computational models that incorporate both extrinsic and intrinsic mechanisms are lacking. Here, I will discuss collaborative efforts to bridge the gap between traditional assays employed in developmental biology and computational models through quantitative approaches. In particular, we have developed quantitative image analysis techniques for confocal microscopy data to inform computational models – a critical task in efforts to better understand conserved mechanisms of crosstalk between growth regulatory pathways. Currently, these quantitative approaches are being applied to develop integrated models of epithelial growth in the embryonic Drosophila epidermis and the adolescent wing imaginal disc, due to the wealth of previous genetic knowledge for the system. An integrated model of intrinsic and extrinsic growth control is expected to inspire new approaches in tissue engineering and regenerative medicine.

We study liquid crystal point defects in 2D domains. We employ Landau-de

Gennes theory and provide a simplified description of global minimizers

of Landau- de Gennes energy under homeothropic boundary conditions. We

also provide explicit solutions describing defects of various strength

under Lyuksutov's constraint.

Open 2d TCFTs correspond to cyclic A-infinity algebras, and Costello showed

that any open theory has a universal extension to an open-closed theory in

which the closed state space (the value of the functor on a circle) is the

Hochschild homology of the open algebra.  We will give a G-equivariant

generalization of this theorem, meaning that the surfaces are now equipped

with principal G-bundles.  Equivariant Hochschild homology and a new ribbon

graph decomposition of the moduli space of surfaces with G-bundles are the

principal ingredients.  This is joint work with Ramses Fernandez-Valencia.

Abstract: Polynomial preserving processes are defined as time-homogeneous Markov jump-diffusions whose generator leaves the space of polynomials of any fixed degree invariant. The moments of their transition distributions are polynomials in the initial state. The coefficients defining this relationship are given as solutions of a system of nested linear ordinary differential equations. Polynomial processes include affine processes, whose transition functions admit an exponential-affine characteristic function. These processes are attractive for financial modeling because of their tractability and robustness. In this work we study approximations of polynomial preserving processes with finite-state Markov processes via a moment-matching methodology. This approximation aims to exploit the defining property of polynomial preserving processes in order to reduce the complexity of the implementation of such models. More precisely, we study sufficient conditions for the existence of finite-state Markov processes that match the moments of a given polynomial preserving process. We first construct discrete time finite-state Markov processes that match moments of arbitrary order. This discrete time construction relies on the existence of long-run moments for the polynomial process and cubature methods over these moments. In the second part we give a characterization theorem for the existence of a continuous time finite-state Markov process that matches the moments of a given polynomial preserving process. This theorem illustrates the complexity of the problem in continuous time by combining algebraic and geometric considerations. We show the impossibility of constructing in general such a process for polynomial preserving diffusions, for high order moments and for sufficiently many points in the state space. We provide however a positive result by showing that the construction is possible when one considers finite-state Markov chains on lifted versions of the state space. This is joint work with Damir Filipovic and Martin Larsson.

Recent experimental work has determined the atomic structure of a quasicrystalline Cd-Yb alloy. It highlights the elegant role of polyhedra with icosahedral symmetry. Other work suggests that while chunks of periodic crystals and disordered glass predominate in the solid state, there are many hints of icosahedral clusters. This talk is based on a recent Mathematical Intelligencer article on quasicrystals with Marjorie Senechal.

The seminar will be followed by a drinks reception and forms part of a longer PDE and CoV related Workshop.

To register for the seminar and drinks reception go to http://doodle.com/acw6bbsp9dt5bcwb

This talk is intended to explain the link between some relatively straightforward mathematical concepts, in terms of linear programming and optimisation over a convex set of feasible solutions, and questions for the organisation of the power sector and hence for energy policy.

Both markets and centralised control systems should in theory optimise the use of the current stock of generation assets and ensure electricity is generated at least cost, by ranking plant in ascending order of short run marginal cost (SRMC), sometimes known as merit order operation. Wholesale markets, in principle at least, replicate exactly what would happen in a perfect but centrally calculated optimal dispatch of plant. This happens because the SRMC of each individual plant is “discovered” through the market and results in a price equal to “system marginal cost” (SMC), which is just high enough to incentivise the most costly plant required to meet the actual load.

More generally, defining the conditions for this to work - “decentralised prices replicate perfect central planning” - is of great interest to economists. Quite apart from any ideological implications, it also helps to define possible sources of market failure. There is an extensive literature on this, but we can explain why it has appeared to work so well, and so obviously, for merit order operation, and then consider whether the conditions underpinning its success will continue to apply in the future.

The big simplifying assumptions, regarded as an adequate approximation to reality, behind most current power markets are the following:

• Each optimisation period can be considered independent of all past and future periods.

• The only relevant costs are well defined short term operating costs, essentially fuel.

• (Fossil) plant is (infinitely) flexible, and costs vary continuously and linearly with output.

• Non-fossil plant has hitherto been intra-marginal, and hence has little impact

The merit order is essentially very simple linear programming, with the dual value of the main constraint equating to the “correct” market price. Unfortunately the simplifying assumptions cease to apply as we move towards types of plant (and consumer demand) with much more complex constraints and cost structures. These include major inflexibilities, stochastic elements, and storage, and many non-linearities. Possible consequences include:

• Single period optimisation, as a concept underlying the market or central control, will need to be abandoned. Multi period optimisation will be required.

• Algorithms much more complicated than simple merit order will be needed, embracing non-linearities and complex constraints.

• Mathematically there is no longer a “dual” price, and the conditions for decentralisation are broken. There is no obvious means of calculating what the price “ought” to be, or even knowing that a meaningful price exists.

The remaining questions are clear. The theory suggests that current market structures may be broken, but how do we assess or show when and how much this might matter?

Following last week's talk on Beilinson-Bernstein localisation theorem, we give basic notions in deformation quantisation explaining how this theorem can be interpreted as a quantised version of the Springer resolution. Having attended last week's talk will be useful but not necessary.

For Logic Seminar: Note change of time and place.

In this talk, I will discuss the effect of boundary conditions on the solvability of PDEs that have formally an integrable structure, in the

sense of possessing a Lax pair. Many of these PDEs arise in wave propagation phenomena, and boundary value problems for these models are very important in applications. I will discuss the extent to which general approaches that are successful for solving the initial value problem extend to the solution of boundary value problem.

I will survey the solution of specific examples of integrable PDE, linear and nonlinear. The linear theory is joint work with David Smith. For the nonlinear case, I will discuss boundary conditions that yield boundary value problems that are fully integrable, in particular recent joint results with Thanasis Fokas and Jonatan Lenells on the solution of boundary value problems for the elliptic sine-Gordon equation.

We propose a model where an algorithmic trader takes a view on the distribution of prices at a future date and then decides how to trade in the direction of her predictions using the optimal mix of market and limit orders. As time goes by, the trader learns from changes in prices and updates her predictions to tweak her strategy. Compared to a trader that cannot learn from market dynamics or form a view of the market, the algorithmic trader's profits are higher and more certain. Even though the trader executes a strategy based on a directional view, the sources of profits are both from making the spread as well as capital appreciation of inventories. Higher volatility of prices considerably impairs the trader's ability to learn from price innovations, but this adverse effect can be circumvented by learning from a collection of assets that co-move.

Many problems in the physical sciences

require the determination of an unknown

function from a finite set of indirect measurements.

Examples include oceanography, oil recovery,

water resource management and weather forecasting.

The Bayesian approach to these problems

is natural for many reasons, including the

under-determined and ill-posed nature of the inversion,

the noise in the data and the uncertainty in

the differential equation models used to describe

complex mutiscale physics. The object of interest

in the Bayesian approach is the posterior

probability distribution on the unknown field [1].

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However the Bayesian approach presents a

computationally formidable task as it

results in the need to probe a probability

measure on separable Banach space. Monte

Carlo Markov Chain methods (MCMC) may be

used to achieve this [2], but can be

prohibitively expensive. In this talk I

will discuss approximation of probability measures

by a Gaussian measure, looking for the closest

approximation with respect to the Kullback-Leibler

divergence. This methodology is widely

used in machine-learning [3]. In the context of

target measures on separable Banach space

which themselves have density with respect to

a Gaussian, I will show how to make sense of the

resulting problem in the calculus of variations [4].

Furthermore I will show how the approximate

Gaussians can be used to speed-up MCMC

sampling of the posterior distribution [5].

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[1] A.M. Stuart. "Inverse problems: a Bayesian

perspective." Acta Numerica 19(2010) and

http://arxiv.org/abs/1302.6989

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[2] S.L.Cotter, G.O.Roberts, A.M. Stuart and D. White,

"MCMC methods for functions: modifying old algorithms

to make them faster". Statistical Science 28(2013).

http://arxiv.org/abs/1202.0709

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[3] C.M. Bishop, "Pattern recognition and machine learning".

Springer, 2006.

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[4] F.J. Pinski G. Simpson A.M. Stuart H. Weber, "Kullback-Leibler

Approximations for measures on infinite dimensional spaces."

http://arxiv.org/abs/1310.7845

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[5] F.J. Pinski G. Simpson A.M. Stuart H. Weber, "Algorithms

for Kullback-Leibler approximation of probability measures in

infinite dimensions." In preparation.

(Joint work with Jochen Koenigsmann) Admitting a p-henselian
valuation is a weaker assumption on a field than admitting a henselian
valuation. Unlike henselianity, p-henselianity is an elementary property
in the language of rings. We are interested in the question when a field
admits a non-trivial 0-definable p-henselian valuation (in the language
of rings). They often then give rise to 0-definable henselian
valuations. In this talk, we will give a classification of elementary
classes of fields in which the canonical p-henselian valuation is
uniformly 0-definable. This leads to the new phenomenon of p-adically
(pre-)Euclidean fields.