Abstract

In the multicoloring problem, also known as ( a : b )- coloring or b-fold coloring , we are given a graph G and a set of a colors, and the task is to assign a subset of b colors to each vertex of G so that adjacent vertices receive disjoint color subsets. This natural generalization of the classic coloring problem (the b =1 case) is equivalent to finding a homomorphism to the Kneser graph KG a,b and gives relaxations approaching the fractional chromatic number. We study the complexity of determining whether a graph has an ( a : b )-coloring. Our main result is that this problem does not admit an algorithm with runtime f ( b )ċ 2 o (log b )ċ n for any computable f(b) unless the Exponential Time Hypothesis (ETH) fails. A ( b +1) n ċ poly( n )-time algorithm due to Nederlof [33] shows that this is tight. A direct corollary of our result is that the graph homomorphism problem does not admit a 2 O ( n + h ) algorithm unless the ETH fails even if the target graph is required to be a Kneser graph. This refines the understanding given by the recent lower bound of Cygan et al. [9]. The crucial ingredient in our hardness reduction is the usage of detecting matrices of Lindström [28], which is a combinatorial tool that, to the best of our knowledge, has not yet been used for proving complexity lower bounds. As a side result, we prove that the runtime of the algorithms of Abasi et al. [1] and of Gabizon et al. [14] for the r -monomial detection problem are optimal under the ETH.

Highlights

  • The complexity of determining the chromatic number of a graph is undoubtedly among the most intensively studied computational problems

  • We prove that the running time of the algorithms of Abasi et al [MFCS 2014] and of Gabizon et al [ESA 2015] for the r-monomial detection problem are optimal under Exponential Time Hypothesis (ETH)

  • The (a:b)-coloring problem asks whether G admits an (a:b)-coloring

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Summary

Introduction

The complexity of determining the chromatic number of a graph is undoubtedly among the most intensively studied computational problems. By taking all maximal independent sets to be the family in the Multi Set Cover problem, and applying the classic Moon-Moser upper bound on their number [31], we obtain an algorithm for (a:b)-coloring that runs in time O (3n/3 · (b + 1)n) and uses polynomial space. H needs not be sparse to admit efficient homomorphism testing: the family of cliques admits the O (2n) running time as shown by Björklund et al [2] As noted above, this generalizes to Kneser graphs KGa,b, by the O ((b + 1)n)-time algorithm of Nederlof. Corollary 2 in particular excludes any algorithm for testing homomorphisms into Kneser graphs with running time 2O(n+h) It cannot give a tight lower bound matching the result of. Proofs of statements marked with (♠) are deferred to the full version [3] of this paper

Preliminaries
The nonuniform case
The uniform case
Low-degree testing
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