PY 541 Statistical Physics, Fall 2022


This is the website for PY 541, Statistical Physics. This website will be updated with lecture notes and homework assignments.

Course information and syllabus pdf

Office Hours: Pankaj Mehta: Wed 3:30-4:30pm, SCI 323.

Instructor: Pankaj Mehta


Textbook: Entropy, Order Parametes, and Complexity by Jim Sethna. Available free here. There are hints to problems at this page . You can find a beautiful introduction to these topics at a more elementary undergrad level in Gould and Tobochnik Statistical and Thermal Physics available online here.

Programming:We will perform programming exercises Programming exercises will be performed in Python (there are also hint files for Mathematica). For Python (the preferred language for the class), I recommend the Anaconda distribution with Jupyter lab here Please bring Laptops to class. You can get mathematica here.

Midterm pdf. Remember you have 3 hours from moment you open pdf. Please follow honor coder. Due Nov 3rd. Password:midterm

Problem Set 1
Problem Set 1 pdf. HW Tuesday Sept 20th. Pre-class exercises due as indicated.
Suggested Readings: Chapter 1, Chapter 2.1-2.2, any set of good notes on probability theory.
Handout: pdf

Problem Set 2
Problem Set 2 pdf. Due Sept. 29th
Suggested Readings: Rest of Chapter 2, Chapter 3.

Problem Set 3
Problem Set 3 pdf. Due Oct. 6th
Suggested Readings: Chapter 4,5. Notes on thermodynamic identity Notes.
Check out this paper that experimentally tests Jarzynski's inequality.

Problem Set 4
Problem Set 4 pdf. Due Oct 13th.
Suggested Readings: Chapter 5. Additional reading: Mackay's masterful Information Theory, Inference, and Learning Algorithms

Problem Set 5
Problem Set 5 pdf. Due Oct 27th.
Suggested Readings: Chapter 6+8 (we are skipping chapter 7 for now and will return after chapter 8)
Please see these notes on Legendre transforms from Gatsby tea. Notes.

Problem Set 6
Problem Set 6 pdf. Due Nov 10th.
Suggested Readings: Chpater 8

Problem Set 7
Problem Set 7 pdf. Due Nov 22nd.
Readings Chapter 9. For derivation of Variational Methods and MFT please see Section 14.1 of our ML review and Chapter 1 of David Tong's Statistical Field Theory Course.

Problem Set 8
Problem Set 8 pdf. Due Dec 1st.
Readings: Chapter 10.

Problem Set 9
Problem Set 9 pdf. Due Dec. 13th.
Readings: Chapter 7 .