Teaching statistical physics by thinking about models and algorithms

TL;DR

This paper explores effective methods for teaching statistical physics by using models and algorithms to improve students' understanding of core concepts without necessarily requiring programming skills.

Contribution

It introduces various illustrative models and algorithms to enhance teaching of statistical physics, emphasizing physical accuracy over programming.

Findings

Using models clarifies fundamental concepts.

Discussing algorithm results aids understanding.

Models improve student engagement and comprehension.

Abstract

We discuss several ways of illustrating fundamental concepts in statistical and thermal physics by considering various models and algorithms. We emphasize the importance of replacing students' incomplete mental images by models that are physically accurate. In some cases it is sufficient to discuss the results of an algorithm or the behavior of a model rather than having students write a program.