Introducing Quantum Computing into Statistical Physics: Random Walks and the Ising Model with Qiskit
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.
Cite
@article{arxiv.2511.03696,
title = {Introducing Quantum Computing into Statistical Physics: Random Walks and the Ising Model with Qiskit},
author = {Zihan Li and Dan A. Mazilu and Irina Mazilu},
journal= {arXiv preprint arXiv:2511.03696},
year = {2025}
}
Comments
Please reference the accompanying Jupyter Notebook at https://github.com/ZihanLi26/Introducing-Quantum-Computing-into-Statistical-Physics-Random-Walks-and-the-Ising-Model-with-Qiskit.git