paper

Polynomial-time trace reconstruction in the smoothed complexity model

arXiv:2008.12386

Abstract

In the \emph{trace reconstruction problem}, an unknown source string is sent through a probabilistic \emph{deletion channel} which independently deletes each bit with probability and concatenates the surviving bits, yielding a \emph{trace} of . The problem is to reconstruct given independent traces. This problem has received much attention in recent years both in the worst-case setting where may be an arbitrary string in \cite{DOS17,NazarovPeres17,HHP18,HL18,Chase19} and in the average-case setting where is drawn uniformly at random from \cite{PeresZhai17,HPP18,HL18,Chase19}. This paper studies trace reconstruction in the \emph{smoothed analysis} setting, in which a ``worst-case'' string $x^{\worst}$ is chosen arbitrarily from , and then a perturbed version $\bx$ of $x^{\worst}$ is formed by independently replacing each coordinate by a uniform random bit with probability . The problem is to reconstruct $\bx$ given independent traces from it. Our main result is an algorithm which, for any constant perturbation rate and any constant deletion rate , uses $\poly(n)$ running time and traces and succeeds with high probability in reconstructing the string $\bx$. This stands in contrast with the worst-case version of the problem, for which is the best known time and sample complexity \cite{DOS17,NazarovPeres17}. Our approach is based on reconstructing $\bx$ from the multiset of its short subwords and is quite different from previous algorithms for either the worst-case or average-case versions of the problem. The heart of our work is a new $\poly(n)$-time procedure for reconstructing the multiset of all -length subwords of any source string given access to traces of .