# Physics 530, Fall 2013: Statistical Mechanics

### D. M. Wood

Office: Meyer Hall 454

Phone: (303) 273-3853

e-mail: dmwood@Mines.EDU

Syllabus and text errata

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.

### Lecture notes

Introduction to ideas and thermo

Review of thermodynamics

Non-Sethna stat mech

Sethna stat mech

Phase transitions, Ginzburg-Landau

### Figures used for examples

Within each file, figures are in no particular order, alas.

### Homework assignments

Homework 1, due Tuesday, September 3

Homework 2, due Tuesday, September 10

Homework 3, due Tuesday, September 17

Homework 4, due Tuesday, September 24

Homework 5, due Tuesday, October 1

Homework 6, due Tuesday, October 8

Homework 7, due Tuesday, October 15

Homework 8, due Tuesday, October 29

Fortran 90 source code;
Input file for code

Random seeds file for code

Homework 9, due Tuesday, November 5

Homework 10, due Tuesday, November 12;
Human hemoglobin data file

Homework 11, due Tuesday, November 19

Homework 12, due Tuesday, December 4

### Practice Exams

### Handouts

Useful math tricks

Notes on Metropolis Monte Carlo

## 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:
- 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.

These Notebooks will display as text files. Save them as .nb files so you can
run them.
Sample non-linear fits [SampNLFit.nb];
Sample non-linear fit data [SampNL.data]

Importance sampling MC

ListAutoCorrelation example

## Using Mathematica

CSM Field Session tutorial
Wolfram
screencast of Basics of Mathematica version 7

Wolfram
hands-on learners tutorial screencast

Wolfram screencasts
for accomplishing common tasks

Send comments & questions to dmwood@mines.
edu

Last Modified: December 6, 2013