Introducing Quantum Computing into Statistical Physics: Random Walks and the Ising Model with Qiskit

TL;DR

This paper introduces two educational modules that integrate quantum computing with statistical physics concepts, enabling students to simulate quantum random walks and the Ising model using Qiskit, thereby enhancing understanding of quantum phenomena.

Contribution

It provides practical, classroom-ready modules that combine quantum computing with statistical physics education, including sample code and activities for undergraduate courses.

Findings

Students can simulate quantum and classical systems for better understanding.

Modules demonstrate superposition, interference, and statistical distributions.

Enhanced student engagement with statistical physics concepts.

Abstract

Quantum computing offers a powerful new perspective on probabilistic and collective behaviors traditionally taught in statistical physics. This paper presents two classroom-ready modules that integrate quantum computing into the undergraduate curriculum using Qiskit: the quantum random walk and the Ising model. Both modules allow students to simulate and contrast classical and quantum systems, deepening their understanding of concepts such as superposition, interference, and statistical distributions. We outline the quantum circuits involved, provide sample code and student activities, and discuss how each example can be used to enhance student engagement with statistical physics. These modules are suitable for integration into courses in statistical mechanics, modern physics, or as part of an introductory unit on quantum computing.