PH635/715-2D Advanced Statistical Mechanics I Spring, 2021)

Last modified on January 10, 2021

Messages from Instructor:

  • [1/10] Class will meet on Jan 19 at 12:30 am as scheduled in ZOOM.

Class Hour: 12:30-1:45

Course Format: Remote

All lectures are given online via ZOOM.

Course Description:

Through this course students will learn advanced topics in statistical mechanics including computer simulation methods. See Learning Objectives for the list of items included in this course.

Learning Objectives:

  • Classical Mixed States: Phase Density and Liouville Equation
  • Quantum Mixed States: Density Operator and Liuoville-von Neumann Equation
  • Entropy and Information
  • Ensemble Theory of Thermal Equilibrium
  • Critical Phenomena, Landau Theory, Renomalization Group
  • Linear Response Theory, Fluctuation Dissipation Theorem, Onsager Relation
  • Stochastic Dynamics, Langevin Equation, Fokker-Plank Equation
  • Monte Carlo Simulation, Metropolis Algorithm
  • Fluctuation Theorem, Jerzyinski Equality
  • Information and Maxwell Demon
  • The Origin of Statistical Physics: Quantum Typicality

Required Textbook

Statistical Mechanics: Entropy, Order Parameters, and Complexity (2nd Ed.)
by James Sethna
OXford University Press, 2021

The second edition has not been publised. It will be on market at the end of February or in March. Until then, we use the following materials:



Textbook uses MAthematica. It is highly desirable for you to have your own Mathematica on your personal computer. It is free for UAB students. This web page will explain how to get your own copy of Mathematica. Free online tutorials are also available.


Python is a popular computer language and Texbook uses it. Phython source codes are provided for some example problems. Anadonda package is recommended for Microsoft Windows and Mac. The instructor uses Python 3.x (Not Python 2.x). Download Anaconda at If you use Linux and don't know how to install Python and related tools, consult the instructor.


Although Textbook does not use MATLAB. However, it can replace Python if you are already using MATLAB. UAB has a site license and students are elligible to install MATLAB on their computer. Installation instruction is given at


Homework must be turned in electronically by email.  Allowed formats are PDF and Latex. Photograph taken by cell phone is not acceptable. Late submition of homework is accepted for partial credit. It mus be submitted before 12pm, April 23, 2021.


Attendance is required. To pass the course you must attend at least 75% of lectures. Excessive absence will result in administrative withdraw.


Midterm exam: 30 pts, Final exam:30 pts, homework: 40 pts. The total maximum possible points is 100 pts. All students must complete two exams and 75% of homework, and must attend more than 75% of lectures. Otherwise, F is given regardless of the total scores. Letter grades are determined by the rule given in the table.

Grade Total Score
A 90 or above
B 80 or above
C 70 or above
F Otherwise

Where the university can, it is providing a Pass/Fail option in case there are circumstances and/or challenges students are encountering related to the ongoing pandemic that might make a Pass/Fail option a better option. If students are not remaining with the default letter grade method for any of their courses, they must select the Pass/Fail grading method for each course individually. This selection is made toward the end of the semester. Once a student selects the option for a Pass/Fail grading method for a particular course, that decision is not reversible regardless of their performance on remaining assignments or final exams.

About Instructor

I am available to meet with you virtually via Zoom by appointment during my virtual office hours shown below. Please make an appointment via email.

Dr. Ryoichi Kawai

Virtual Office Hour: Wed. 12:30-1:30pm
Tel: (205) 934-3931
Fax: (205) 934-8042
(My PGP public key)


Campbell Hall 309
Department of Physics
University of Alabama at Birmingham
1300 University Blvd.
Birmingham, AL 35294

© Dr. Ryoichi Kawai, 2021 All Rights Reserved. No part of this website or any of its contents may be reproduced, copied, modified or adapted, without the prior written consent of the author, unless otherwise indicated for stand-alone materials.