Reconstructing Strings from Substrings with Quantum Queries

TL;DR

This paper presents a quantum algorithm that reconstructs an unknown string from substrings with significantly fewer queries than classical methods, using Grover search and novel subroutines, along with lower bounds on query complexity.

Contribution

The paper introduces a quantum query algorithm for string reconstruction that outperforms classical approaches and establishes fundamental lower bounds for the problem.

Findings

Quantum algorithm achieves at most 3/4 N + o(N) queries

Classical query complexity is N

Lower bounds show limitations on query efficiency

Abstract

This paper investigates the number of quantum queries made to solve the problem of reconstructing an unknown string from its substrings in a certain query model. More concretely, the goal of the problem is to identify an unknown string $S$ by making queries of the following form: "Is $s$ a substring of $S$?", where $s$ is a query string over the given alphabet. The number of queries required to identify the string $S$ is the query complexity of this problem. First we show a quantum algorithm that exactly identifies the string $S$ with at most $3/4N + o(N)$ queries, where $N$ is the length of $S$. This contrasts sharply with the classical query complexity $N$. Our algorithm uses Skiena and Sundaram's classical algorithm and the Grover search as subroutines. To make them effectively work, we develop another subroutine that finds a string appearing only once in $S$, which may have an independent interest. We also prove two lower bounds. The first one is a general lower bound of $\Omega(\frac{N}{\log^2{N}})$, which means we cannot achieve a query complexity of $O(N^{1-\epsilon})$ for any constant $\epsilon$. The other one claims that if we cannot use queries of length roughly between $\log N$ and $3 \log N$, then we cannot achieve a query complexity of any sublinear function in $N$.