Past

When $\partial D$ is spatially homogeneous, we show that we can recover the lower and upper Minkowski dimensions of $\partial D$ from the sort time behaviour of $E(s)$. Furthermore, when the Minkowski dimension exists, finer geometric fluctuations can be recovered and $E(s)$ is controlled by $s^\alpha e^{f(\log(1/s))}$ for small $s$, for some $\alpha \in (0, \infty)$ and some regularly varying function $f$. The function $f$ is not constant is general and carries some geometric information.

When $\partial D$ is statistically self-similar, the Minkowski dimension and content of $\partial D$ typically exist and can be recovered from $E(s)$. Furthermore, $E(s)$ has an almost sure expansion $E(s) = c s^{\alpha} N_\infty + o(s^\alpha)$ for small $s$, for some $c$ and $\alpha \in (0, \infty)$ and some positive random variable $N_\infty$ with unit expectation arising as the limit of some martingale. In some cases, we can show that the fluctuations around this almost sure behaviour are governed by a central limit theorem, and conjecture that this is true more generally.

This is based on joint work with David Croydon and Ben Hambly.

We are dwelling in the Big Data age. The diversity of the uses

of Big Data unleashes limitless possibilities. Many people are talking

about ways to use Big Data to track the collective human behaviours,

monitor electoral popularity, and predict financial fluctuations in

stock markets, etc. Big Data reveals both challenges and opportunities,

which are not only related to technology but also to human itself. This

talk will cover various current topics and trends in Big Data research.

The speaker will share his relevant experiences on how to use analytics

tools to obtain key metrics on online social networks, as well as

present the challenges of Big Data analytics.

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Bio: Ning Wang (Ph.D) works as Researcher at the Oxford Internet

Institute. His research is driven by a deep interest in analysing a wide

range of sociotechnical problems by exploiting Big Data approaches, with

the hope that this work could contribute to the intersection of social

behavior and computational systems.

We consider a large class of three dimensional continuous dynamic fluctuation models, and show that they all rescale and converge to the stochastic Allen-Cahn equation, whose solution should be interpreted after a suitable renormalization procedure. The interesting feature is that, the coefficient of the limiting equation is different from one's naive guess, and the renormalization required to get the correct limit is also different from what one would naturally expect. I will also briefly explain how the recent theory of regularity structures enables one to prove such results. Joint work with Martin Hairer.

Cardinal characteristics of the continuum are (definitions for) cardinals that are provably uncountable and at most the cardinality c of the reals, but which (if the continuum hypothesis fails) may be strictly less than c.  Cichon's diagram is a standard diagram laying out all of the ZFC-provable inequalities between the most familiar cardinal characteristics of the continuum.  There is a natural analogy that can be drawn between these cardinal characteristics and highness properties of Turing oracles in computability theory, with implications taking the place of inequalities.  The diagram in this context is mostly the same with a few extra equivalences: many of the implications were trivial or already known, but there remained gaps, which in joint work with Brendle, Ng and Nies we have filled in.

Topological insulators are a type of system in condensed matter physics that exhibit a robustness that physicists like to call topological. In this talk I will give a definition of a subclass of such systems: gapped, free fermions. We will look at how such systems, as shown by Kitaev, can be classified in terms of topological K-groups by using the Clifford module model for K-theory as introduced by Atiyah, Bott and Shapiro. I will be using results from Wednesday's JTGT, where I'll give a quick introduction to topological K-theory.

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Molecular modelling has become a valuable tool and is increasingly part of the standard methodology of chemistry, physics, engineering and biology. The power of molecular modelling lies in its versatility: as potential energy functions improve, a broader range of more complex phenomena become accessible to simulation, but much of the underlying methodology can be re-used. For example, the Verlet method is still the most popular molecular dynamics scheme for constant energy molecular dynamics simulations despite it being one of the first to be proposed for the purpose.

One of the most important challenges in molecular modelling remains the computation of averages with respect to the canonical Gibbs (constant temperature) distribution, for which the Verlet method is not appropriate. Whereas constant energy molecular dynamics prescribes a set of equations (Newton's equations), there are many alternatives for canonical sampling with quite different properties. The challenge is therefore to identify formulations and numerical methods that are robust and maximally efficient in the computational setting.

One of the simplest and most effective methods for sampling is based on Langevin dynamics which mimics coupling to a heat bath by the incorporation of random forces and an associated dissipative term. Schemes for Langevin dynamics simulation may be developed based on the familiar principle of splitting. I will show that the invariant measure ('long term') approximation may be strongly affected by a simple re-ordering of the terms of the splitting. I will describe a transition in weak numerical order of accuracy that occurs (in one case) in the t->infty limit.

I will also entertain some more radical suggestions for canonical sampling, including stochastic isokinetic methods that enable the use of greatly enlarged timesteps for expensive but slowly-varying force field components.

We will define the Ran space as well as Ran space versions of some of the prestacks we've already seen, and explain what is meant by the homology of a prestack. Following Gaitsgory and possibly Drinfeld, we'll show how the Ran space machinery can be used to prove that the space of rational maps is homologically contractible.

For many questions of scientific interest, all-atom molecular simulations are still out of reach, in particular in materials engineering where large numbers of atoms, and often expensive force fields, are required. A long standing challenge has been to construct concurrent atomistic/continuum coupling schemes that use atomistic models in regions of space where high accuracy is required, with computationally efficient continuum models (e.g., FEM) of the elastic far-fields.

Many different mechanisms for achieving such atomistic/continuum couplings have been developed. To assess their relative merits, in particular accuracy/cost ratio, I will present a numerical analysis framework. I will use this framework to analyse in more detail a particularly popular scheme (the BQCE scheme), identifying key approximation parameters which can then be balanced (in a surprising way) to obtain an optimised formulation.

Finally, I will demonstrate that this analysis shows how to remove a severe bottlenecks in the BQCE scheme, leading to a new scheme with optimal convergence rate.

Algebraically closed fields, and in general varieties are among the first examples
of Zariski Geometries.
I will consider specialisations of algebraically closed fields and varieties.
In the case of an algebraically closed field K, I will show that a specialisation
is essentially a residue map, res from K to a residue field k.  
In both cases I will show universality of the specialisation is controlled by the
transcendence degree of K over k.  

In the late 70s -- early 80s Makanin came up with a very simple, but very powerful idea to approach solving equations in free groups. This simplicity makes Makanin-like procedures ubiquitous in mathematics: in dynamical systems, geometric group theory, 3-dimensional topology etc. In this talk I will explain loosely how Makanin's algorithm works.

In 1878, Jordan showed that if $G$ is a finite group of complex $n \times n$ matrices, then $G$ has a normal subgroup whose index in $G$ is bounded by a function of $n$ alone. He showed only existence, and early actual bounds on this index were far from optimal. In 1985, Weisfeiler used the classification of finite simple groups to obtain far better bounds, but his work remained incomplete when he disappeared. About eight years ago, I obtained the optimal bounds, and this work has now been extended to subgroups of all (complex) classical groups. I will discuss this topic at a “colloquium” level – i.e., only a rudimentary knowledge of finite group theory will be assumed.

Auctioneers may wish to sell related but different indivisible goods in

a single process. To develop such techniques, we study the geometry of

how an agent's demanded bundle changes as prices change. This object

is the convex-geometric object known as a `tropical hypersurface'.

Moreover, simple geometric properties translate directly to economic

properties, providing a new taxonomy for economic valuations. When

considering multiple agents, we study the unions and intersections of

the corresponding tropical hypersurfaces; in particular, properties of

the intersection are deeply related to whether competitive equilibrium

exists or fails. This leads us to new results and generalisations of

existing results on equilibrium existence. The talk will provide an

introductory tour to relevant economics to show the context of these

applications of tropical geometry. This is joint work with Paul

Klemperer.

The common convention when dealing with hyperbolic groups is that such groups are finitely

generated and equipped with the word length metric relative to a finite symmetric generating

subset. Gromov's original work on hyperbolicity already contained ideas that extend beyond the

finitely generated setting. We study the class of locally compact hyperbolic groups and elaborate

on the similarities and differences between the discrete and non-discrete setting.

Hamiltonian reduction arose as a mechanism for reducing complexity of systems in mechanics, but it also provides a tool for constructing complicated but interesting objects from simpler ones. I will illustrate how this works in representation theory and algebraic geometry via examples. I will describe a new structure theory, motivated by Hamiltonian reduction (and in particular the Morse theory that results), for some categories (of D-modules) of interest to representation theorists. I will then explain how this implies a modified form of "hyperkahler Kirwan surjectivity" for the cohomology of certain Hamiltonian reductions. The talk will not assume that members of the audience know the meaning of any of the above-mentioned terms. The talk is based on joint work with K. McGerty.

We study the behaviour of orthogonal polynomials on triangles and their coefficients in the context of spectral approximations of partial differential equations.  For spectral approximation we consider series expansions $u=\sum_{k=0}^{\infty} \hat{u}_k \phi_k$ in terms of orthogonal polynomials $\phi_k$. We show that for any function $u \in C^{\infty}$ the series expansion converges faster than with any polynomial order.  With these result we are able to employ the polynomials $\phi_k$ in the spectral difference method in order to solve hyperbolic conservation laws.

It is a well known fact that discontinuities can arise leading to oscillatory numerical solutions. We compare standard filtering and the super spectral vanishing viscosity methods, which uses exponential filters build from the differential operator of the respective orthogonal polynomials.  We will extend the spectral difference method for unstructured grids by using 
 classical orthogonal polynomials and exponential filters. Finally we consider some numerical test cases.