Lecture

Brownian Motion: Fundamentals and Applications

Description

This lecture covers the fundamentals of Brownian motion, starting with Paul Langevin's 1908 paper and the contributions of Einstein and Markov processes. It delves into the mathematical description of Brownian motion, including symmetric dimensions, particle positions, and distribution functions. The lecture also explores the equation of motion for particles, probability functions, and Taylor expansions, providing insights into diffusion processes and their applications.

In MOOCs (2)

Official source

https://mediaspace.epfl.ch/media/0_uqybqdnk

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

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