Finite convergence of sum-of-squares hierarchies for the stability number of a graph

TL;DR

This paper proves finite convergence of certain sum-of-squares hierarchies for the stability number of a graph, especially for acritical graphs, and explores related complexity implications.

Contribution

It establishes finite convergence conditions for sum-of-squares hierarchies in graph stability problems, linking copositive and Motzkin-Straus formulations.

Findings

Finite convergence shown for acritical graphs.

Finite minimizers characterization for Motzkin-Straus formulation.

Deciding finite minimizers is NP-hard.

Abstract

We investigate a hierarchy of semidefinite bounds $\vartheta^{(r)}(G)$ for the stability number $\alpha(G)$ of a graph $G$, based on its copositive programming formulation and introduced by de Klerk and Pasechnik [{\em SIAM J. Optim.} 12 (2002), pp.875--892], who conjectured convergence to $\alpha(G)$ in $r=\alpha(G)-1$ steps. Even the weaker conjecture claiming finite convergence is still open. We establish links between this hierarchy and sum-of-squares hierarchies based on the Motzkin-Straus formulation of $\alpha(G)$, which we use to show finite convergence when $G$ is acritical, i.e., when $\alpha(G\setminus e)=\alpha(G)$ for all edges $e$ of $G$. This relies, in particular, on understanding the structure of the minimizers of the Motzkin-Straus formulation and showing that their number is finite precisely when $G$ is acritical. Moreover we show that these results hold in the general setting of the weighted stable set problem for graphs equipped with positive node weights. In addition, as a byproduct we show that deciding whether a standard quadratic program has finitely many minimizers does not admit a polynomial-time algorithm unless P=NP.