Approximating partition functions of bounded-degree Boolean counting Constraint Satisfaction Problems
Abstract
We study the complexity of approximate counting Constraint Satisfaction Problems (#CSPs) in a bounded degree setting. Specifically, given a Boolean constraint language and a degree bound , we study the complexity of #CSP, which is the problem of counting satisfying assignments to CSP instances with constraints from and whose variables can appear at most times. Our main result shows that: (i) if every function in is affine, then #CSP is in FP for all , (ii) otherwise, if every function in is in a class called IM, then for all sufficiently large , #CSP is equivalent under approximation-preserving (AP) reductions to the counting problem #BIS (the problem of counting independent sets in bipartite graphs) (iii) otherwise, for all sufficiently large , it is NP-hard to approximate the number of satisfying assignments of an instance of #CSP, even within an exponential factor. Our result extends previous results, which apply only in the so-called "conservative" case.
Cite
@article{arxiv.1610.04055,
title = {Approximating partition functions of bounded-degree Boolean counting Constraint Satisfaction Problems},
author = {Andreas Galanis and Leslie Ann Goldberg and Kuan Yang},
journal= {arXiv preprint arXiv:1610.04055},
year = {2020}
}
Comments
To appear in JCSS. This version: minor corrections to typos