Sparsification upper and lower bounds for graph problems and Not-All-Equal SAT

Research output: Book/ReportReportAcademic

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

We present several sparsification lower and upper bounds for classic problems in graph theory and logic. For the problems 4-Coloring, (Directed) Hamiltonian Cycle, and (Connected) Dominating Set, we prove that there is no polynomial-time algorithm that reduces any n-vertex input to an equivalent instance, of an arbitrary problem, with bitsize O(n^{2-e}) for e > 0, unless NP is in coNP/poly and the polynomial-time hierarchy collapses. These results imply that existing linear-vertex kernels for k-Nonblocker and k-Max Leaf Spanning Tree (the parametric duals of (Connected) Dominating Set) cannot be improved to have O(k^{2-e}) edges, unless NP is in coNP/poly. We also present a positive result and exhibit a non-trivial sparsification algorithm for d-Not-All-Equal SAT. We give an algorithm that reduces an n-variable input with clauses of size at most d to an equivalent input with O(n^{d-1}) clauses, for any fixed d. Our algorithm is based on a linear-algebraic proof of Lovasz that bounds the number of hyperedges in critically 3-chromatic d-uniform n-vertex hypergraphs by n choose d-1. We show that our kernel is tight under the assumption that NP is not a subset of coNP/poly. Keywords: sparsification, graph coloring, Hamiltonian cycle, satisfiability
Original languageEnglish
Publishers.n.
Number of pages21
Publication statusPublished - 2015

Publication series

NamearXiv
Volume1509.07437 [cs.CC]

Fingerprint Dive into the research topics of 'Sparsification upper and lower bounds for graph problems and Not-All-Equal SAT'. Together they form a unique fingerprint.

Cite this