Past

It is well known that electrical resistance arguments provide (usually) the best method for determining whether a graph is transient or recurrent. In this talk I will discuss a similar characterization of 'sub-diffusive behaviour' -- this occurs in spaces with many obstacles or traps.

The characterization is in terms of the energy of functions in annuli.

A simple formula is given for the $n$-field tree-level MHV gravitational

amplitude, based on soft limit factors. It expresses the full $S_n$ symmetry

naturally, as a determinant of elements of a symmetric ($n \times n$) matrix.

Shapiro's Conjecture says that two classical exponential polynomials over the complexes can have infinitely many common zeros only for algebraic reasons. I will explain the history of this, the connection to Schanuel's Conjecture, and sketch a proof for the complexes using Schanuel, as well as an unconditional proof for Zilber's fields.

In a variety of problems in engineering and applied science, the goal is to design or control a network of dynamical agents so as to achieve some desired asymptotic behaviour. Examples include consensus and rendez-vous problems in robotics, synchronization of generator angles in power grids or coordination of oscillations in bacterial populations. A pressing challenge in all of these problems is to derive appropriate analytical tools to prove convergence towards the target behaviour. Such tools are not only invaluable to guarantee the desired performance, but can also provide important guidelines for the design of decentralized control strategies to steer the collective behaviour of the network of interest in a desired manner. During this talk, a methodology for analysis and design of convergence in networks will be presented which is based on the use of a classical, yet not fully exploited, tool for convergence analysis: contraction theory. As opposed to classical methods for stability analysis, the idea is to look at convergence between trajectories of a system of interest rather that at their asymptotic convergence towards some solution of interest. After introducing the problem, a methodology will be derived based on the use of matrix measures induced by non-Euclidean norms that will be exploited to design strategies to control the collective behaviour of networks of dynamical agents. Representative examples will be used to illustrate the theoretical results.

We study exponential sums of Weyl type taken over roots of quadratic congruences. We are particularly interested in the situation where the range of summation is small compared to the discriminant of the polynomial. We are then able to give a number of arithmetic applications.

This is work which is joint with W. Duke and H. Iwaniec.

The advent of multicore processors represents a disruptive event in the history of computer science as conventional parallel programming paradigms are proving incapable of fully exploiting their potential for concurrent computations. The need for different or new programming models clearly arises from recent studies which identify fine-granularity and dynamic execution as the keys to achieve high efficiency on multicore systems. This talk shows how these models can be effectively applied to the multifrontal method for the QR factorization of sparse matrices providing a very high efficiency achieved through a fine-grained partitioning of data and a dynamic scheduling of computational tasks relying on a dataflow parallel programming model. Moreover, preliminary results will be discussed showing how the multifrontal QR factorization can be accelerated by using low-rank approximation techniques.

Complex structures on a closed surface of genus at least 2 are in

one-to-one correspondence with hyperbolic metrics, so that there is a

single space, Teichmüller space, parametrising all possible complex

and hyperbolic structures on a given surface (up to isotopy). We will

explore how complex and hyperbolic geometry interact in Teichmüller

space.

A construction by McCool gives rise to a finite presentation for the stabiliser of a finite set of conjugacy classes in a free group under the action of Aut(F_n) or Out(F_n). An important concept of my talk are rigid elements, which will allow to simplify these huge presentations. Finally I will sketch applications to centralisers in Aut(F_n).

In this talk, I will introduce stochastic models to describe the state of the chemical networks using continuous-time Markov chains.
First, I will talk about the multiscale approximation method developed by Ball, Kurtz, Popovic, and Rempala (2006). Extending their method, we construct a general multiscale approximation in chemical reaction networks. We embed a stochastic model for a chemical reaction network into a family of models parameterized by a large parameter N. If reaction rate constants and species numbers vary over a wide range, we scale these numbers by powers of the parameter N. We develop a systematic approach to choose an appropriate set of scaling exponents. When the scaling suggests subnetworks have di erent time-scales, the subnetwork in each time scale is approximated by a limiting model involving a subset of reactions and species.

After that, I will briefly introduce Gaussian approximation using a central limit theorem, which gives a model with more detailed uctuations which may be not captured by the limiting models in multiscale approximations.

Next, we consider modeling of a chemical network with both reaction and diffusion.
We discretize the spatial domain into several computational cells and model diffusion as a reaction where the molecule of species in one computational cell moves to the neighboring one. In this case, the important question is how many computational cells we need to use for discretization to get balance between e ective diffusion rates and reaction rates both of which depend on the computational cell size. We derive a condition under which concentration of species converges to its uniform solution exponentially. Replacing a system domain size in this condition by computational cell size in our stochastic model, we derive an upper bound
for the computational cell size.

Finally, I will talk about stochastic reaction-diffusion models of pattern formation. Spatially distributed signals called morphogens influence gene expression that determines phenotype identity of cells. Generally, different cell types are segregated by boundary between
them determined by a threshold value of some state variables. Our question is how sensitive the location of the boundary to variation in parameters. We suggest a stochastic model for boundary determination using signaling schemes for patterning and investigate their effects on the variability of the boundary determination between cells.

It is very well known that every graph on $n$ vertices and $m$ edges admits a bipartition of size at least $m/2$. This bound can be improved to $m/2 + (n-1)/4$ for connected graphs, and $m/2 + n/6$ for graphs without isolated vertices, as proved by Edwards, and Erd\"os, Gy\'arf\'as, and Kohayakawa, respectively. A bisection of a graph is a bipartition in which the size of the two parts differ by at most 1. We prove that graphs with maximum degree $o(n)$ in fact admit a bisection which asymptotically achieves the above bounds.These results follow from a more general theorem, which can also be used to answer several questions and conjectures of Bollob\'as and Scott on judicious bisections of graphs.
Joint work with Po-Shen Loh and Benny Sudakov

In 1932 Signorini formulated the first variational inequality as a model of an elastic body laying on a rigid surface. In this talk we will revisit this problem from the point of view of regularity theory.

We will sketch a proof of optimal regularity and regularity of the contact set. Similar result are known for scalar equations. The proofs for scalar equations are however based on maximum principles and thus not applicable to Signorini's problem which is modelled by a system of equations.

Let G be a finitely generated group generated by g_1,..., g_n. Consider the alphabet A(G) consisting of the symbols g_1,..., g_n and the symbols '+' and '-'. The words in this alphabet represent elements of the integral group ring Z[G]. In the talk we will investigate the computational problem of deciding whether a word in the alphabet A(G) determines a zero-divisor in Z[G]. We will see that a version of the Atiyah conjecture (together with some natural assumptions) imply decidability of the zero-divisor problem; however, we'll also see that in the group (Z/2 \wr Z)^4 the zero-divisor problem is not decidable. The technique which allows one to see the last statement involves "embedding" a Turing machine into a group ring.

We consider the approximation of the marginal distribution of solutions of stochastic partial differential equations by splitting schemes. We introduce a functional analytic framework based on weighted spaces where the Feller condition generalises. This allows us to apply the theory of strongly continuous semigroups. The possibility of achieving higher orders of convergence through cubature approximations is discussed.

Applications of these results to problems from mathematical finance (the Heath-Jarrow-Morton equation of interest rate theory) and fluid dynamics (the stochastic Navier-Stokes equations) are considered. Numerical experiments using Quasi-Monte Carlo simulation confirm the practicality of our algorithms.

Parts of this work are joint with J. Teichmann and D. Veluscek.

I will discuss properties of stochastic differential equations and numerical algorithms for sampling Gibbs (i.e smooth) measures. Methods such as Langevin dynamics are reliable and well-studied performers for molecular sampling.   I will show that, when the objective of simulation is sampling of the configurational distribution, it is possible to obtain a superconvergence result (an unexpected increase in order of accuracy) for the invariant distribution.   I will also describe an application of thermostats to the Hamiltonian vortex method in which the energetic interactions with a bath of weak vortices are treated as thermal fluctuations

I will discuss some recent progress connecting different quiver gauge theories and some applications of these results.

• Thomas März - Calculus on surfaces with general closest point functions
• Jay Newby - Modeling rare events in biology
• Hugh McNamara - Stochastic parameterisation and variational multiscale

Sorry, this has been cancelled at short notice!