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Weak convergence for semi-linear SPDEs.

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Sonja Cox
Tuesday, 31 January 2017

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Faculté des sciences - Section de mathématiques
Joint work with Arnulf Jentzen, Ryan Kurniawan, and Timo Welti.
In numerical analysis for stochastic differential equations, a general rule of thumb is that the optimal weak convergence rate of a numerical scheme is twice the optimal strong convergence rate. However, for SPDEs the optimal weak convergence rate is difficult to establish theoretically. Recently, progress was been made by Jentzen, Kurniawan and Welti for semi-linear SPDEs using the so-called mild Itô formula. We consider this approach for wave equations.
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Collection

Workshop on Multiscale methods for stochastic dynamics

1

Stochastic parameterizations of deterministic dynamical systems: Theory, applications and challenges

Georg Gottwald
Tuesday 31 January 2017
2

Ergodic Stochastic Differential Equations and Sampling: A numerical analysis perspective

Kostas Zygalakis
Tuesday 31 January 2017
3

Weak convergence for semi-linear SPDEs.

Sonja Cox
Tuesday 31 January 2017
4

On stochastic numerical methods for the approximative pricing of financial derivatives.

Arnulf Jentzen
Tuesday 31 January 2017
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Mean-square stability analysis of SPDE approximations.

Annika Lang
Wednesday 1 February 2017
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Adaptive timestepping for S(P)DEs to control growth.

Gabriel Lord
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Noise-induced transitions and mean field limits for multiscale diffusions.

Greg Pavliotis
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8

Accelerated dynamics and transition state theory.

Tony Lelièvre
Wednesday 1 February 2017
9

Long-time homogenization of the wave equation.

Antoine Gloria
Wednesday 1 February 2017