String Synchronizing Sets: Sublinear-Time BWT Construction and Optimal LCE Data Structure
Abstract
Burrows-Wheeler transform (BWT) is an invertible text transformation that, given a text of length , permutes its symbols according to the lexicographic order of suffixes of . BWT is one of the most heavily studied algorithms in data compression with numerous applications in indexing, sequence analysis, and bioinformatics. Its construction is a bottleneck in many scenarios, and settling the complexity of this task is one of the most important unsolved problems in sequence analysis that has remained open for 25 years. Given a binary string of length , occupying machine words, the BWT construction algorithm due to Hon et al. (SIAM J. Comput., 2009) runs in time and space. Recent advancements (Belazzougui, STOC 2014, and Munro et al., SODA 2017) focus on removing the alphabet-size dependency in the time complexity, but they still require time. In this paper, we propose the first algorithm that breaks the -time barrier for BWT construction. Given a binary string of length , our procedure builds the Burrows-Wheeler transform in time and space. We complement this result with a conditional lower bound proving that any further progress in the time complexity of BWT construction would yield faster algorithms for the very well studied problem of counting inversions: it would improve the state-of-the-art -time solution by Chan and P\v{a}tra\c{s}cu (SODA 2010). Our algorithm is based on a novel concept of string synchronizing sets, which is of independent interest. As one of the applications, we show that this technique lets us design a data structure of the optimal size that answers Longest Common Extension queries (LCE queries) in time and, furthermore, can be deterministically constructed in the optimal time.
Keywords
Cite
@article{arxiv.1904.04228,
title = {String Synchronizing Sets: Sublinear-Time BWT Construction and Optimal LCE Data Structure},
author = {Dominik Kempa and Tomasz Kociumaka},
journal= {arXiv preprint arXiv:1904.04228},
year = {2020}
}
Comments
Full version of a paper accepted to STOC 2019