MSE-639 / 2 credits

Teacher: Ceriotti Michele

Language: English


Frequency

Every 2 years

Summary

The course gives an overview of atomistic simulation methods, combining theoretical lectures and hands-on sessions. It covers the basics (molecular dynamics and monte carlo sampling) and also more advanced topics (accelerated sampling of rare events, and non-linear dimensionality reduction).

Content

Keywords

Introductory knowledge of statistical mechanics and probability, basic programming skills preferably in FORTRAN.  Some familiarity with working in a Linux environment is preferable.  

Learning Prerequisites

Recommended courses

Introductory knowledge of statistical mechanics and probability, basic programming skills,
preferably in FORTRAN or Python

Assessment methods

Project report

Resources

Websites

In the programs

  • Exam form: Project report (session free)
  • Subject examined: Statistical methods in atomistic computer simulations
  • Lecture: 14 Hour(s)
  • Practical work: 14 Hour(s)

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22