These lecture notes provide an introduction to the applications
of Brownian motion to analysis and more generally, connections
between Brownian motion and analysis. Brownian motion is a
well-suited model for a wide range of real random phenomena, from
chaotic oscillations of microscopic objects, such as flower pollen
in water, to stock market fluctuations. It is also a purely
abstract mathematical tool which can be used to prove theorems in
"deterministic" fields of mathematics.
The notes include a brief review of Brownian motion and a
section on probabilistic proofs of classical theorems in analysis.
The bulk of the notes are devoted to recent (post-1990)
applications of stochastic analysis to Neumann eigenfunctions,
Neumann heat kernel and the heat equation in time-dependent
domains.
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