English

Quasipolynomial-time algorithms for Gibbs point processes

Data Structures and Algorithms 2023-05-24 v2 Probability

Abstract

We demonstrate a quasipolynomial-time deterministic approximation algorithm for the partition function of a Gibbs point process interacting via a finite-range stable potential. This result holds for all activities λ\lambda for which the partition function satisfies a zero-free assumption in a neighborhood of the interval [0,λ][0,\lambda]. As a corollary, for all finite-range stable potentials we obtain a quasipolynomial-time determinsitic algorithm for all λ</(eB+1C^ϕ)\lambda < /(e^{B + 1} \hat C_\phi) where C^ϕ\hat C_\phi is a temperedness parameter and BB is the stability constant of ϕ\phi. In the special case of a repulsive potential such as the hard-sphere gas we improve the range of activity by a factor of at least e2e^2 and obtain a quasipolynomial-time deterministic approximation algorithm for all λ<e/Δϕ\lambda < e/\Delta_\phi, where Δϕ\Delta_\phi is the potential-weighted connective constant of the potential ϕ\phi. Our algorithm approximates coefficients of the cluster expansion of the partition function and uses the interpolation method of Barvinok to extend this approximation throughout the zero-free region.

Keywords

Cite

@article{arxiv.2209.10453,
  title  = {Quasipolynomial-time algorithms for Gibbs point processes},
  author = {Matthew Jenssen and Marcus Michelen and Mohan Ravichandran},
  journal= {arXiv preprint arXiv:2209.10453},
  year   = {2023}
}

Comments

Results extended to include stable potentials

R2 v1 2026-06-28T01:49:49.290Z