Deterministic Negative-Weight Shortest Paths in Nearly Linear Time via Path Covers

TL;DR

This paper introduces a deterministic nearly-linear time algorithm for solving single-source shortest paths with negative weights in directed graphs, using a novel structural primitive called path cover.

Contribution

It presents the first deterministic nearly-linear time algorithm for negative-weight shortest paths in directed graphs, overcoming reliance on randomized low-diameter decompositions.

Findings

Achieves nearly-linear time complexity $ ilde{O}(m) imes ext{polylog}(nW)$.

Introduces the concept of path cover as a new structural primitive.

Provides a foundation for future deterministic algorithms on directed graphs.

Abstract

We present the first deterministic nearly-linear time algorithm for single-source shortest paths with negative edge weights on directed graphs: given a directed graph $G$ with $n$ vertices, $m$ edges whose weights are integer in $\{-W,\dots,W\}$, our algorithm either computes all distances from a source $s$ or reports a negative cycle in time $\tilde{O}(m)\cdot \log(nW)$ time. All known near-linear time algorithms for this problem have been inherently randomized, as they crucially rely on low-diameter decompositions. To overcome this barrier, we introduce a new structural primitive for directed graphs called the path cover. This plays a role analogous to neighborhood covers in undirected graphs, which have long been central to derandomizing algorithms that use low-diameter decomposition in the undirected setting. We believe that path covers will serve as a fundamental tool for the design of future deterministic algorithms on directed graphs.