Quenched asymptotics for Brownian motion in generalized Gaussian potential.

Speaker: 

Professor Xia Chen

Institution: 

University of Tennessee

Time: 

Tuesday, February 7, 2012 - 11:00am

Location: 

RH 306

Recall that the notion of
generalized function is introduced for the functions
that can not be defined pointwise, and
is given as a linear functional over the test functions.
The same idea applies to random fields. In this talk,
we study the quenched asymptotics for Brownian motion
in a generalized Gaussian field. The major ingredient
includes: Solution to
an open problem posted by Carmona and Molchanov (1995) with
an answer different from what was conjectured; the quenched
laws for Brownian motions in Newtonian-type potentials, and in the potentials
driven by white noise or by fractional white noise.

On diffusions interacting through their ranks

Speaker: 

Mikhaylo Shkolnikov

Institution: 

UC Berkeley

Time: 

Thursday, December 1, 2011 - 4:00pm

Location: 

RH 306

We will discuss systems of diffusion processes on the real line, in which the dynamics of every single process is determined by its rank in the entire particle system. Such systems arise in mathematical finance and statistical physics, and are related to heavy-traffic approximations of queueing networks. Motivated by the applications, we address questions about invariant distributions, convergence to equilibrium and concentration of measure for certain statistics, as well as hydrodynamic limits and large deviations for these particle systems. Parts of the talk are joint work with Amir Dembo, Tomoyuki Ichiba, Soumik Pal and Ofer Zeitouni

Effective Dynamics of Stochastic Partial Differential Equations

Speaker: 

Professor Jinqiao Duan

Institution: 

IPAM

Time: 

Tuesday, February 14, 2012 - 11:00am

Location: 

RH 306

The need to take stochastic effects into account for modeling complex systems has now become
widely recognized. Stochastic partial differential equations arise naturally as mathematical
models for multiscale systems under random influences. We consider macroscopic dynamics of
microscopic systems described by stochastic partial differential equations. The microscopic
systems are characterized by small scale heterogeneities (spatial domain with small holes or
oscillating coefficients), or fast scale boundary impact (random dynamic boundary condition),
among others.

Effective macroscopic model for such stochastic microscopic systems are derived. The effective
model s are still stochastic partial differential equations, but defined on a unified spatial domain
and the random impact is represented by extra components in the effective models. The
solutions of the microscopic models are shown to converge to those of the effective macroscopic
models in probability distribution, as the size of holes or the scale separation parameter
diminishes to zero. Moreover, the long time effectivity of the macroscopic system in the sense of
convergence in probability distribution, and in the sense of convergence in energy are also
proved.

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