Analysis of Perfect Sampling Methods for Hard-sphere Models

Author:

Moka S. B.1,Juneja S.2,Mandjes M. R. H.3

Affiliation:

1. UQ, Brisbane

2. TIFR, Mumbai

3. University of Amsterdam

Abstract

We consider the problem of generating perfect samples from a Gibbs point process, a spatial process that is absolutely continuous w.r.t. a Poisson point process. Examples include area-interaction processes, hard-sphere models and Strauss processes. Traditionally, this is addressed using coupling from the past (CFTP) based methods. We consider acceptance-rejection methods that, unlike the common CFTP methods, do not have the impatient-user bias. Our key contribution is a novel importance sampling based acceptance- rejection methodology for generating perfect samples from Gibbs point processes. We focus on a simpler setting of hard-sphere models in a d-dimensional hypercube that we analyze in an asymptotic regime where the number of spheres generated increases to infinity while the sphere radius decreases to zero at varying rates.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Spectral Independence View on Hard Spheres via Block Dynamics;SIAM Journal on Discrete Mathematics;2022-09

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