A polynomial-time algorithm for estimating the partition function of the ferromagnetic Ising model on a regular matroid

TL;DR

This paper presents a polynomial-time randomized approximation scheme for estimating the partition function of the ferromagnetic Ising model on regular matroids, extending previous results beyond graphic matroids.

Contribution

The authors develop an FPRAS for regular matroids by leveraging Seymour's decomposition theorem, filling a gap between graphic and binary matroids.

Findings

FPRAS exists for regular matroids.

Extends approximation algorithms from graphic to regular matroids.

Provides insights into the computational complexity of Ising model partition functions.

Abstract

We investigate the computational difficulty of approximating the partition function of the ferromagnetic Ising model on a regular matroid. Jerrum and Sinclair have shown that there is a fully polynomial randomised approximation scheme (FPRAS) for the class of graphic matroids. On the other hand, the authors have previously shown, subject to a complexity-theoretic assumption, that there is no FPRAS for the class of binary matroids, which is a proper superset of the class of graphic matroids. In order to map out the region where approximation is feasible, we focus on the class of regular matroids, an important class of matroids which properly includes the class of graphic matroids, and is properly included in the class of binary matroids. Using Seymour's decomposition theorem, we give an FPRAS for the class of regular matroids.