The Chv\'atal-Sankoff problem: Understanding random string comparison through stochastic processes

TL;DR

This paper investigates the longstanding problem of determining the asymptotic expected length of the longest common subsequence in random binary strings, linking it to stochastic processes to derive new estimates for the key constant.

Contribution

It introduces a novel approach connecting the LCS problem to stochastic particle processes, providing a new estimate for the Chvátal-Sankoff constant.

Findings

Derived a new estimate for the Chvátal-Sankoff constant γ

Linked LCS problem to stochastic particle processes

Enhanced understanding of LCS structure through statistical mechanics

Abstract

Given two equally long, uniformly random binary strings, the expected length of their longest common subsequence (LCS) is asymptotically proportional to the strings' length. Finding the proportionality coefficient $\gamma$, i.e. the limit of the normalised LCS length for two random binary strings of length $n \to \infty$, is a very natural problem, first posed by Chv\'atal and Sankoff in 1975, and as yet unresolved. This problem has relevance to diverse fields ranging from combinatorics and algorithm analysis to coding theory and computational biology. Using methods of statistical mechanics, as well as some existing results on the combinatorial structure of LCS, we link constant $\gamma$ to the parameters of a certain stochastic particle process, which we use to obtain a new estimate for $\gamma$.