Lecture

Markov Chain: Configuration Sampling

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In course

CH-351: Molecular dynamics and Monte-Carlo simulation

Introduction to molecular dynamics and Monte-Carlo simulation methods. ...

Description

This lecture explains the concept of a Markov process and Markov chain in the context of the Metropolis algorithm for generating random configurations in configurational space with correct relative Boltzmann weights. The instructor discusses the importance of starting with a suitable initial configuration, making random changes to the system, and accepting or rejecting new configurations based on their relative Boltzmann weights.

Instructor

Ursula Röthlisberger

U. Röthlisberger was born in Solothurn (Switzerland). In 1988 she made her diploma in Physical Chemistry in the group of Prof. Ernst Schumacher at the University of Berne (Switzerland). Her Ph.D. thesis was done in collaboration with Dr. Wanda Andreoni at the IBM Zurich Research Laboratory in Rüschlikon. After finishing her Ph.D in 1991 she spent some time as a postdoctoral research assistant at the IBM Research Lab. From 1992-1995 she was a postdoctoral research assistant in the group of Prof. Michael L. Klein at the University of Pennsylvania in Philadelphia (USA). In 1994 she was awarded an advanced researcher fellowship (Profil 2) from the Swiss National Science Foundation. Before starting her Profile 2-fellowship she spent another year as postdoctoral research assistant in the group of Prof. Michele Parrinello at the Max-Planck-Institute for Solid State Physics in Stuttgart, Germany. In 1996 she moved as Profile 2-fellow to the ETH in Zurich, hosted by the group of Prof. Wilfred F. van Gunsteren. In 1997 she became Assistant Professor of Computer-Aided Inorganic Chemistry at the ETH Zurich.

Official source

Ontological neighbourhood

Physics

Thermodynamics: Statistical mechanics

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