Introduction to supervised machine learning for physics students

We discuss a simple supervised machine learning algorithm using logistic regression to classify phases in the Ising model of magnetization and the trajectories of a particle subject to either a spring or a gravitational force. Several pedagogical problems are provided as a means to introduce students to the basic ideas of machine learning.

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Publication Details

Journal
American Journal of Physics
Published
2026-02-19
DOI
https://doi.org/10.1119/5.0285290
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Introduction to supervised machine learning for physics students

Harvey Gould, Jan Tobochnik
American Journal of Physics
Computational Physics and Python Applications
article

Introduction to supervised machine learning for physics students

Harvey Gould, Jan Tobochnik
article en

Abstract

We discuss a simple supervised machine learning algorithm using logistic regression to classify phases in the Ising model of magnetization and the trajectories of a particle subject to either a spring or a gravitational force. Several pedagogical problems are provided as a means to introduce students to the basic ideas of machine learning.

American Journal of PhysicsVol. 94(3)
Clark University (US), Kalamazoo College (US)
Quality Education
Openalex Percentile: Top 53%
Computational Physics and Python Applications
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