17:00
Classifying crystal structures: geometric and arithmetic approach
Abstract
While the classification of crystals made up by just one atom per cell is well-known and understood (Bravais lattices), that for more complex structures is not. We present a geometric way classifying these crystals and an arithmetic one, the latter introduced in solid mechanics only recently. The two approaches are then compared. Our main result states that they are actually equivalent; this way a geometric interpretation of the arithmetic criterion in given. These results are useful for the kinematic description of solid-solid phase transitions. Finally we will reformulate the arithmetic point of view in terms of group cohomology, giving an intrinsic view and showing interesting features.
15:45
The Stability of Linear Stochastic Differential Equations with Jump
Abstract
Under the nondegenerate condition as in the diffusion case, we show
that the linear stochastic jump diffusion process projected on the
unite sphere has an uni que invariant probabolity measure. The
Lyapunov exponentcan be represented as an integral over the
sphere. These results were extended to the degenerated and Levy jump
cases.
14:15
Anderson localisation for multi-particle systems
Abstract
Anderson localisation is an important phenomenon describing a
transition between insulation and conductivity. The problem is to analyse
the spectrum of a Schroedinger operator with a random potential in the
Euclidean space or on a lattice. We say that the system exhibits
(exponential) localisation if with probability one the spectrum is pure
point and the corresponding eigen-functions decay exponentially fast.
So far in the literature one considered a single-particle model where the
potential at different sites is IID or has a controlled decay of
correlations. The present talk aims at $N$-particle systems (bosons or
fermions) where the potential sums over different sites, and the traditional
approach needs serious modifications. The main result is that if the
`randomness' is strong enough, the $N$-particle system exhibits
localisation.
The proof exploits the muli-scale analysis scheme going back to Froehlich,
Martinelli, Scoppola and Spencer and refined by von Drefus and Klein. No
preliminary knowledge of the related material will be assumed from the
audience, apart from basic facts.
This is a joint work with V Chulaevsky (University of Reims, France)
15:15
14:00
Reduction methods for biochemical and population biology models based on invariant manifold theory
16:30
Analysis of the sparse grid combination technique and high dimensional applications in option pricing
Abstract
Sparse grids yield numerical solutions to PDEs with a
significantly reduced number of degrees of freedom. The relative
benefit increases with the dimensionality of the problem, which makes
multi-factor models for financial derivatives computationally tractable.
An outline of a convergence proof for the so called combination
technique will be given for a finite difference discretisation of the
heat equation, for which sharp error bounds can be shown.
Numerical examples demonstrate that by an adaptive (heuristic)
choice of the subspaces European and American options with up to thirty
(and most likely many more) independent variables can be priced with
high accuracy.
12:00
Speciation in Salmonella: Models vs. Data
Abstract
/notices/events/abstracts/Workshop/Falush.shtml
17:00
17:00
15:45
Conditional Cameron-Martin's formula for diffusions
Abstract
I will present a new formula for diffusion processes which involving
Ito integral for the transition probability functions. The nature of
the formula I discovered is very close to the Kac formula, but its
form is similar to the Cameron-Martin formula. In some sense it is the
Cameron-Martin formula for pinned diffusions.
14:30
14:15
14:15
Endogeny and Dynamics for processes indexed by trees
Abstract
I will consider a stochastic process ( \xi_u; u \in
\Gamma_\infty ) where \Gamma_\infty is the set of vertices of an
infinite binary tree which satisfies some recursion relation
\xi_u= \phi(\xi_{u0},\xi_{u1}, \epsilon_u) \text { for each } u \in \Gamma_\infty.
Here u0 and u1 denote the two immediate daughters of the vertex u.
The random variables ( \epsilon_u; u\in \Gamma_\infty), which
are to be thought of as innovations, are supposed independent and
identically distributed. This type of structure is ubiquitous in models
coming from applied proability. A recent paper of Aldous and Bandyopadhyay
has drawn attention to the issue of endogeny: that is whether the process
( \xi_u; u \in \Gamma_\infty) is measurable with respect to the
innovations process. I will explain how this question is related to the
existence of certain dynamics and use this idea to develop a necessary and
sufficient condition [ at least if S is finite!] for endogeny in terms of
the coupling rate for a Markov chain on S^2 for which the diagonal is
absorbing.
16:30
15:15
Asymptotics and oscillation
Abstract
Much is now known about exp-log series, and their connections with o-
minimality and Hardy fields. However applied mathematicians who work with
differential equations, almost invariably want series involving
trigonometric functions which those theories exclude. The seminar looks at
one idea for incorporating oscillating functions into the framework of
Hardy fields.