The Set Cover Conjecture and Subgraph Isomorphism with a Tree Pattern

TL;DR

This paper explores the deep connections between the Set Cover Conjecture and the complexity of the Subgraph Isomorphism problem with a tree pattern, proposing new conjectures and algorithms that impact multiple related computational problems.

Contribution

It introduces the Log-SeCoCo conjecture, links it to the complexity of kTree and Directed Hamiltonicity, and provides improved algorithms for p-Partial Cover under certain assumptions.

Findings

Weakening of the Set Cover Conjecture to Log-SeCoCo.

Conditional lower bounds linking Set Cover and kTree complexities.

New nearly optimal algorithm for p-Partial Cover.

Abstract

In the Set Cover problem, the input is a ground set of $n$ elements and a collection of $m$ sets, and the goal is to find the smallest sub-collection of sets whose union is the entire ground set. The fastest algorithm known runs in time $O(mn2^n)$ [Fomin et al., WG 2004], and the Set Cover Conjecture (SeCoCo) [Cygan et al., TALG 2016] asserts that for every fixed $\varepsilon>0$, no algorithm can solve Set Cover in time $2^{(1-\varepsilon)n}poly(m)$, even if set sizes are bounded by $\Delta=\Delta(\varepsilon)$. We show strong connections between this problem and kTree, a special case of Subgraph Isomorphism where the input is an $n$-node graph $G$ and a $k$-node tree $T$, and the goal is to determine whether $G$ has a subgraph isomorphic to $T$. First, we propose a weaker conjecture Log-SeCoCo, that allows input sets of size $\Delta=O(1/\varepsilon \cdot\log n)$, and show that an algorithm breaking Log-SeCoCo would imply a faster algorithm than the currently known $2^n poly(n)$-time algorithm [Koutis and Williams, TALG 2016] for Directed nTree, which is kTree with $k=n$ and arbitrary directions to the edges of $G$ and $T$. This would also improve the running time for Directed Hamiltonicity, for which no algorithm significantly faster than $2^n poly(n)$ is known despite extensive research. Second, we prove that if Set Cover cannot be solved significantly faster than $2^npoly(m)$ (an assumption even weaker than Log-SeCoCo), then kTree cannot be computed significantly faster than $2^kpoly(n)$, the running time of the Koutis and Williams' algorithm. Applying the same techniques to the p-Partial Cover problem, a parameterized version of Set Cover that requires covering at least $p$ elements, we obtain a new algorithm with running time $(2+\varepsilon)^p (m+n)^{O(1/\varepsilon)}$ for arbitrary $\varepsilon>0$, which improves previous work and is nearly optimal assuming say Log-SeCoCo.