2548 papers
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.
This paper conjectures and numerically verifies that the Mayer series coefficients for dimer gases on various regular bipartite lattices follow a specific asymptotic exponential form, while also exploring connections to renormalization group theory, Ising model susceptibility, and the properties of partition and prime number functions.
This paper presents analytical results on exact tensor network representations and correlation functions for the first examples of 2D ground states exhibiting quantum phase transitions between area law and extensive entanglement entropy, utilizing 3D tessellation-based networks that generalize 1D holographic models to reveal exotic phase characteristics through random surface scaling.
This paper establishes the existence of gapped, translation-symmetry-breaking dimerized ground states with exponentially decaying correlations in -invariant quantum spin chains for sufficiently large across an expanded region of the phase diagram, utilizing a probabilistic random loop representation and adapting methods from loop models.
This paper establishes that the iterative Faddeev-Jackiw reduction for singular Lagrangian systems is a geometrically constrained instance of the Matrix Bordering Technique, deriving an exact determinant factorization that links algorithm termination to the nondegeneracy of the constraint algebra and enabling a fully symbolic implementation in the Wolfram Language.
This paper resolves the paradox of imaginary momentum in quantum tunneling by introducing a complex-time parametrization that reinterprets evanescent traversal as a causal, light-speed-bounded process, a theory validated through its analogy to transmission delay in non-Hermitian microwave scattering experiments.
NestyNet-DE is a novel framework that discovers complex, nonlinear differential equations and their underlying geometric symmetries directly from data without relying on fixed libraries, successfully recovering fundamental physical laws such as the reduced-Kepler hierarchy and Schrödinger equation through a combination of sparse-library and operator-factorized search strategies.
This paper presents a no-go theorem demonstrating that standard finite-width neural network ensembles cannot consistently realize either quantum or effective field theories on a computer due to failures in reflection positivity and scale separation, with only specific infinite-width limits or relaxations of finite variance and rotation invariance offering potential escapes.
This paper classifies differential operators of the form whose monic eigenpolynomials satisfy a finite-term recurrence relation, proving that such a recurrence exists if and only if and divides , in which case the authors explicitly determine the recurrence coefficients and confirm that the associated difference operator has order , thereby verifying specific predictions of the Horozov--Shapiro--Tater conjecture.
This paper derives a novel exact expression linking the Coriolis force to pressure gradients via two-point correlations and demonstrates that while the Coriolis force does not alter the spherically averaged energy and enstrophy transfer rates in two-dimensional -plane turbulence, it is responsible for anisotropic large-scale organization and the formation of zonal jets.
The paper introduces ARCHER, a zero-shot, amortized contrastive classifier that generalizes cryo-EM pose estimation across diverse protein structures by conditioning on reference volumes in Fourier space, achieving high accuracy and preserving conformational signals without the need for per-structure retraining.