The satisfiability threshold and solution space of random uniquely extendable constraint satisfaction problems

TL;DR

This paper investigates the satisfiability threshold and solution space structure of random uniquely extendable constraint satisfaction problems, extending previous models and establishing thresholds under broad conditions.

Contribution

It introduces a flexible model for random UE-CSPs with arbitrary distributions and determines their satisfiability thresholds, linking them to the classical $k$-XORSAT threshold.

Findings

Threshold matches the classical $k$-XORSAT threshold under certain conditions.

Model encompasses both linear systems and previous UE-SAT models.

Provides a unified framework for analyzing random UE-CSPs.

Abstract

We study the satisfiability threshold and solution-space geometry of random constraint satisfaction problems defined over uniquely extendable (UE) constraints. Motivated by a conjecture of Connamacher and Molloy, we consider random $k$-ary UE-SAT instances in which each constraint function is drawn, according to a certain distribution $\pi$, from a specified subset of uniquely extendable constraints over an $r$-spin set. We introduce a flexible model $H_n(\pi,k,m)$ that allows arbitrary distributions $\pi$ on constraint types, encompassing both random linear systems and previously studied UE-SAT models. Our main result determines the satisfiability threshold for a wide family of distributions $\pi$. Under natural reducibility or symmetry conditions on $\operatorname{supp}(\pi)$, we prove that the satisfiability threshold of $H_n(\pi,k,m)$ coincides with the classical $k$-XORSAT threshold.