paper

On the Approximability of Max-Cut on 3-Colorable Graphs and Graphs with Large Independent Sets

arXiv:2604.10318

Abstract

Max-Cut is a classical graph-partitioning problem where given a graph , the objective is to find a cut which maximizes the number of edges crossing the cut. In a seminal work, Goemans and Williamson gave an -factor approximation algorithm for the problem, which was later shown to be tight by the work of Khot, Kindler, Mossel, and O'Donnell. Since then, there has been a steady progress in understanding the approximability at even finer levels, and a fundamental goal in this context is to understand how the structure of the underlying graph affects the approximability of the Max-Cut problem. In this work, we investigate this question by exploring how the chromatic structure of a graph affects the Max-Cut problem. While it is well-known that Max-Cut can be solved perfectly and near-perfectly in -colorable and almost -colorable graphs in polynomial time, here we explore its approximability under much weaker structural conditions such as when the graph is -colorable or contains a large independent set. Our main contributions in this context are as follows: 1. We show Max-Cut is -hard to approximate for -colorable graphs. 2. We identify a natural threshold such that the following holds. Firstly, for graphs which contain an independent set of size up to , Max-Cut continues to be -factor hard to approximate. Furthermore, for any graph that contains an independent set of size , there exists an efficient -approximation algorithm for Max-Cut. Our hardness results are derived using various analytical tools and novel variants of the Majority-Is-Stablest theorem, which might be of independent interest. Our algorithmic results are based on a novel SDP relaxation, which is then rounded and analyzed using interval arithmetic.

56 Pages. Abstract is shortened to fit arXiv requirements