Mathematical physics sits at the fascinating intersection where abstract equations meet the fundamental laws of our universe. This field uses rigorous mathematical tools to model everything from the behavior of subatomic particles to the curvature of spacetime, turning complex theories into testable predictions. It is the language through which physicists describe reality, bridging the gap between pure mathematics and physical observation.

On Gist.Science, we process every new preprint published in this category on arXiv to make these dense studies accessible to everyone. Whether you are a specialist or a curious reader, you will find both plain-language overviews and detailed technical summaries for each paper. Below are the latest mathematical physics papers from arXiv, curated to help you explore the cutting edge of theoretical science.

Semi-classical limit of the massive Klein-Gordon-Maxwell system toward the relativistic Euler-Maxwell system via an adapted modulated energy method

This paper establishes the convergence of the massive Klein-Gordon-Maxwell system to the relativistic Euler-Maxwell system in the semi-classical limit using an adapted modulated energy method, while also proving the well-posedness of the latter and clarifying its relationship to the relativistic massive Vlasov-Maxwell equations.

Tony Salvi2026-02-24🔢 math-ph

Plabic Tangles and Cluster Promotion Maps

Inspired by BCFW recurrence, this paper introduces plabic tangles and mm-vector-relation configurations to define promotion maps between Grassmannian products, conjecturing and proving that these maps are quasi-cluster homomorphisms with significant implications for the amplituhedron's geometry and scattering amplitudes in planar N=4\mathcal{N}=4 super Yang-Mills theory.

Chaim Even-Zohar, Matteo Parisi, Melissa Sherman-Bennett, Ran Tessler, Lauren Williams2026-02-24🔢 math-ph

Do quantum linear solvers offer advantage for networks-based system of linear equations?

This exploratory numerical study evaluates the potential for quantum advantage in solving network-based linear systems by analyzing 50 graph families across multiple quantum algorithms, identifying specific "good" families that offer exponential speedups over classical solvers, and proposing visual conjectures to predict these advantages while acknowledging practical hardware limitations.

Disha Shetty, Supriyo Dutta, Palak Chawla, Akshaya Jayashankar, Jordi Riu, Jan Nogue, K. Sugisaki, V. S. Prasannaa2026-02-24🔢 math-ph