Physics 530, Fall 2012: Statistical Mechanics
D. M. Wood
Office: Meyer Hall 454
Phone: (303) 273-3853
If you forgot to pick up a problem set or handout, retrieve it from the
list below and print it out.
Let me know if you have difficulties with any PDF file.
Introduction to ideas and thermo
Review of thermodynamics
Microcanonical ensemble, ideal gas
Canonical, grand canonical ensembles and ideal quantum gases
Canonical, grand canonical ensembles and ideal quantum gases (Sethna)
Phase transitions, critical phenomena, Ginzburg-Landau theory
Figures used for examples
Within each file, figures are in no particular order, alas.
Homework 1, due Thursday, August 30th
Homework 2, due Thursday, September 6
Homework 3, due Thursday, September 13
Homework 4, due Thursday, September 20
Homework 5, due Thursday, September 27.
Data set for N2
Homework 6, due Thursday, October 4
Homework 7, due Wednesday, October 17 because
of October 11th Hour Test 1
Homework 8, due Thursday, October 25;
Fortran 90 source code;
Input file for code
Homework 9, due Thursday, November 1
Homework 10, due Thursday, November 8
Homework 11, due Thursday, November 15
Homework 12, due Thursday, December 6
Useful math tricks
Notes on the Monte Carlo method
Useful Mathematica Notebooks
Note: If you choose to use these Mathematica Notebooks as templates
for a solution you turn in, please observe the following rules:
These Notebooks will display as text files. Save them as .nb files so you can
- Remove my comments and section headings (and replace them with your own)
and be sure to put in a written explanation of what you are doing!
- Make sure that your Notebook runs correctly if saved and re-run
from scratch with Mathematica. (I've seen too many Notebooks consisting
of a random sequence of attempts to simplify expressions, with
non-reproducible results because competing variable definitions were
used at different times.)
- If you turn in a printout, make sure it is printed `2up', i.e., with
two logical Notebook pages per physical sheet. This is easy enough to
read without wasting paper.
Sample non-linear fits [SampNLFit.nb];
Sample non-linear fit data [SampNL.data]
Importance sampling Monte Carlo [ImportanceSamplingMC.nb];
CSM Field Session tutorial
screencast of Basics of Mathematica version 7
hands-on learners tutorial screencast
for accomplishing common tasks
Send comments & questions to dmwood@mines.
Last Modified: December 10, 2012