Tue, 04 Nov 2008

15:45 - 16:45
L3

Higher-Genus Gromov-Witten Invariants and Crepant Resolutions

Tom Coates
(Imperial College London)
Abstract

Let X be a Gorenstein orbifold and Y a crepant resolution of

X. Suppose that the quantum cohomology algebra of Y is semisimple. We describe joint work with Iritani which shows that in this situation the genus-zero crepant resolution conjecture implies a higher-genus version of the crepant resolution conjecture. We expect that the higher-genus version in fact holds without the semisimplicity hypothesis.

Mon, 27 Oct 2008
14:15
Oxford-Man Institute

"Decay to equilibrium for linear and nonlinear semigroups"

Prof. Boguslaw Zegarlinski
(Imperial College London)
Abstract

In this talk I will present recent results on ergodicity of Markov semigroups in large dimensional spaces including interacting Levy type systems as well as some R-D models.

Mon, 15 Jan 2007
15:45
DH 3rd floor SR

The Global Error in Weak Approximations of Stochastic Differential Equations

Dr Saadia Ghazali
(Imperial College London)
Abstract

In this talk, the convergence analysis of a class of weak approximations of

solutions of stochastic differential equations is presented. This class includes

recent approximations such as Kusuoka's moment similar families method and the

Lyons-Victoir cubature on Wiener Space approach. It will be shown that the rate

of convergence depends intrinsically on the smoothness of the chosen test

function. For smooth functions (the required degree of smoothness depends on the

order of the approximation), an equidistant partition of the time interval on

which the approximation is sought is optimal. For functions that are less smooth

(for example Lipschitz functions), the rate of convergence decays and the

optimal partition is no longer equidistant. An asymptotic rate of convergence

will also be presented for the Lyons-Victoir method. The analysis rests upon

Kusuoka-Stroock's results on the smoothness of the distribution of the solution

of a stochastic differential equation. Finally, the results will be applied to

the numerical solution of the filtering problem.

 

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