Non-equilibrium Statistical Physics

3 EC

Semester 1, period 3

5354NESP3Y

Owner Master Physics and Astronomy (joint degree)
Coordinator Edan Lerner
Part of Master Physics and Astronomy, track Advanced Matter and Energy Physics, Master Physics and Astronomy, track Theoretical Physics, Master Computational Science (Joint Degree), Master Physics and Astronomy (joint degree), track Biophysics and Biophotonics, Master Physics and Astronomy (joint degree), track General Physics and Astronomy, Master Quantum Computer Science,

Course manual 2024/2025

Course content

Course Description 

In this course students will become familiar with fundamental classes of statistical processes often encountered in many fields of physics. Starting from the most basic Brownian motion, we will derive/review/analyze the Fokker-Planck equation and formalism, linear response theory, fluctuation-dissipation relations, and several exotic classes of random walks that produce super- and sub- diffusive behavior. A particular focus will be devoted to scaling arguments, their construction and utility, and to concepts of universality. Examples from various fields of physics will be presented and discussed.  

Study materials

Literature

  • Pavel L. Krapivsky, Sidney Redner, and Eli Ben–Naim, 'A Kinetic View of Statistical Physics'. 

  • Chaikin and Lubensky, 'Principles of condensed matter physics' 

  • M. E. Tuckerman, 'Statistical Mechanics - Theory and Molecular Simulation'

  • J.-P. Bouchaud and A. Georges, Anomalous diffusion in disordered media, Phys. Rep. 195, 127 (1990).

Syllabus

  • see canvas

Software

  • python

Objectives

  • Students will become familiar with a the most commonly encountered classes of statistical problems.
  • Students will know how to construct and motivate scaling arguments.
  • Students will be able to set up simple numerical simulations.
  • Students will know how to perform data analysis on simulational data.
  • Students will be able to apply mathematical tools to study statistical problems.

Teaching methods

  • Laptop seminar
  • Lecture
  • Self-study
  • homework assignments

The homework assignments provide students with an opportunity to conduct "computer experiments" and by such acquire much better intuition about the meaning of different classes of statistical behavior. 

Learning activities

Activity

Hours

Hoorcollege

14

Tentamen

3

Werkcollege

14

Self study

53

Total

84

(3 EC x 28 uur)

Attendance

Requirements concerning attendance (OER-B).

  • In addition to, or instead of, classes in the form of lectures, the elements of the master’s examination programme often include a practical component as defined in article A-1.2 of part A. The course catalogue contains information on the types of classes in each part of the programme. Attendance during practical components is mandatory.

    • Additional requirements for this course:

    Students are strongly recommended to attend all lectures and exercise sessions.

    Assessment

    Item and weight Details

    Final grade

    0.4 (40%)

    Tentamen

    		Mandatory

    0.25 (25%)

    in-class quiz

    		Mandatory

    0.35 (35%)

    homework assignments

    		Mandatory

    Assignments

    There will be 2 homework assignments  (17.5% x 2 = 35%) that involve both analytical and numerical exercises.

    Fraud and plagiarism

    The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

    Course structure

    see canvas

    Contact information

    Coordinator

    • Edan Lerner

    Teaching assistants:

    Tommaso Pettinari (t.pettinari@uva.nl) 

    Twan Hooijschuur (t.hooijschuur@uva.nl) 

     Baptiste Parage (b.m.m.parage@uva.nl)