Independent set in $k$-Claw-Free Graphs: Conditional $\chi$-boundedness and the Power of LP/SDP Relaxations

TL;DR

This paper investigates the limits of convex relaxations for approximating maximum-weight independent sets in $k$-claw-free graphs, revealing that certain desirable bounds do not extend beyond the case $k=3$ and providing insights into the power of LP/SDP methods.

Contribution

It demonstrates that the conditional $ ext{chi}$-boundedness property does not hold for $k$-claw-free graphs when $k>3$, and establishes lower bounds on the strength of convex relaxations in this context.

Findings

Conditional $ ext{chi}$-boundedness fails for $k>3$.

SDP relaxations cannot always approximate maximum-weight independent sets within certain factors.

Provides lower bounds on convex program families stronger than existing relaxations.

Abstract

This paper studies $k$-claw-free graphs, exploring the connection between an extremal combinatorics question and the power of a convex program in approximating the maximum-weight independent set in this graph class. For the extremal question, we consider the notion, that we call \textit{conditional $\chi$-boundedness} of a graph: Given a graph $G$ that is assumed to contain an independent set of a certain (constant) size, we are interested in upper bounding the chromatic number in terms of the clique number of $G$. This question, besides being interesting on its own, has algorithmic implications (which have been relatively neglected in the literature) on the performance of SDP relaxations in estimating the value of maximum-weight independent set. For $k=3$, Chudnovsky and Seymour (JCTB 2010) prove that any $3$-claw-free graph $G$ with an independent set of size three must satisfy $\chi(G) \leq 2 \omega(G)$. Their result implies a factor $2$-estimation algorithm for the maximum weight independent set via an SDP relaxation (providing the first non-trivial result for maximum-weight independent set in such graphs via a convex relaxation). An obvious open question is whether a similar conditional $\chi$-boundedness phenomenon holds for any $k$-claw-free graph. Our main result answers this question negatively. We further present some evidence that our construction could be useful in studying more broadly the power of convex relaxations in the context of approximating maximum weight independent set in $k$-claw free graphs. In particular, we prove a lower bound on families of convex programs that are stronger than known convex relaxations used algorithmically in this context.