Faster Sublinear-Time Edit Distance
Abstract: We study the fundamental problem of approximating the edit distance of two strings. After an extensive line of research led to the development of a constant-factor approximation algorithm in almost-linear time, recent years have witnessed a notable shift in focus towards sublinear-time algorithms. Here, the task is typically formalized as the -gap edit distance problem: Distinguish whether the edit distance of two strings is at most or more than . Surprisingly, it is still possible to compute meaningful approximations in this challenging regime. Nevertheless, in almost all previous work, truly sublinear running time of (for a constant $\varepsilon > 0$) comes at the price of at least polynomial gap . Only recently, [Bringmann, Cassis, Fischer, and Nakos; STOC'22] broke through this barrier and solved the sub-polynomial -gap edit distance problem in time , which is truly sublinear if .The term is inevitable (already for Hamming distance), but it remains an important task to optimize the term and, in general, solve the -gap edit distance problem in sublinear-time for larger values of . In this work, we design an improved algorithm for the -gap edit distance problem in sublinear time , yielding a significant quadratic speed-up over the previous -time algorithm. Notably, our algorithm is unconditionally almost-optimal (up to subpolynomial factors) in the regime where and improves upon the state of the art for .
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