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 3:304:30pm, SCI 323.
Instructor: Pankaj Mehta
Grader:
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
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. Preclass exercises due as indicated.
Suggested Readings: Chapter 1, Chapter 2.12.2, 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 .
