Physics 606 Syllabus

Spring 2014


Arlette Baljon,


Required: “Equilibrium Statistical Physics”, Leonard M. Sander.

The book is available at Amazon:

Please note that this is a new book and we are among the first to use it.  There are bound to be typos. Please let me know it if you find any (even if you are not entirely sure).  We will figure it out and let the author know. The author will post known errors at:  Python codes for the computational homework can be found there as well.


“Statistical Mechanics: Entropy, Order Parameters, and Complexity”, J. P. Sethna (Oxford University Press, 2006), free online at This book discusses application of statistical physics in areas such as social sciences, financial markets, and biological sciences.  The website also has excellent codes:, which you can use for your computational homework.

“Classical and Statistical Thermodynamics”, A. H. Carter (Prentice Hall, Upper Saddle River 2001).   This is an excellent UG level textbook.  I placed it on reserve at the library.

“An Introduction to Thermal Physics”, D. V. Schroeder (Addison Wesley, Boston 2000). This textbook is used at the UG level at SDSU.

 Many more textbooks are mentioned in Sander’s book.


Thermodynamics, Many-particle Systems, Probability, Statistical Ensembles, Interacting particles, Phase Transitions (first order and continues), Quantum statistical mechanics, Ideal quantum gasses, Ising Model, Computer Simulations.


Statistical physics is a field that builds on thermodynamics, classical mechanics and quantum mechanics.  Hence students will need a good understanding of these areas. Although a (recent) UG degree including these fields (SDSU: Physics 350, 360 and 410) should be sufficient, I recommend that students take this class after they take Physics 608 and concurrent with Physics 610A. 


TTh 15.00-16.00 or by appointment.  Room 136 (Physics building)


Reading assignment on each Chapter.  A short quiz will be given in class.  The schedule is below.  Note that since this is a new textbook, I have not listed the exceptions yet.  I will do so at least a week before the reading is due.


Class time will be used for problem solving sessions on Jan 28, Feb 6, 25 March 4, 18, 27; April 17; May 1, 8. Credit will be earned by participating in these sessions.


The book has a subtitle.  “With Computer Simulations in Python”.  The author, like me, believes that valuable physical insight can be obtained by doing computer simulations.  I will assign three computational problem sets. Due days are listed below.


There will be a midterm and a final.  You are allowed one sheet of equations written on both sides. 25 points can be earned on the midterm and 40 on the final. .  15 points (max) can be earned by participating in the problem sessions (1 point each) and by performing well in reading quizzes (1 point each if more than 50% of answers is right).  Finally 20 points can be earned on computational problem sets.

A 90 points; A- 86 points; B+ 81 points; B 77 points; B- 73 points; C+ 68 points; C 64 points; C- 60 points; D+ 55 points; D 51 points; D- 47 points; F <47 points.


After taking this class you will have the problem solving skills and knowledge of thermodynamics and statistical mechanics required for a productive career as a professional physicist.  You also will learn to appreciate how new behavior emerges from interactions of many degrees of freedom…how order can emerge from many random fluctuations…Students will understand how during the last 50 years the ideas of statistical mechanics have influenced many aspects of every day life.


Points can be earned by attending seminars in the area of statmech.  I will post abstracts of such talks on Bb. You have to write a summary (200 to 300 words) of the talk by May 19 to receive credit.  You can receive 2 credit points for up to 2 seminars.  In addition the last computational problem set will contain an optional problem for which you can earn 3 extra credit points.











Jan 28

Chap 1

Reading assignment


Feb 6

Chap 2

Reading assignment


Feb 25

Chap 3

Reading assignment


Feb 27


Computational problem set 1 due


March 4

Chap 4

Reading assignment


March 11


Chapters 1-4


March 18

Chap 5

Reading assignment


March 27

Chap 6

Reading assignment


April 8


Computational problem set 2 due


April 17

Chap 7

Reading assignment


May 1

Chap 8

Reading assignment


May 8

Chap 9

Reading assignment


May 13  3.30-5.30


Chapters 5-9


May 19


Computational problem set 3 due.


No class on February 18 and 20. There will be an online lecture instead and students are encouraged to work on the first problem set.