Approximate Trace Reconstruction via Median String (In Average-Case)

Diptarka Chakraborty, Debarati Das, Robert Krauthgamer

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Scopus citations

    Abstract

    We consider an approximate version of the trace reconstruction problem, where the goal is to recover an unknown string s ∈ {0, 1}n from m traces (each trace is generated independently by passing s through a probabilistic insertion-deletion channel with rate p). We present a deterministic near-linear time algorithm for the average-case model, where s is random, that uses only three traces. It runs in near-linear time Õ(n) and with high probability reports a string within edit distance Õ(p2n) from s, which significantly improves over the straightforward bound of O(pn). Technically, our algorithm computes a (1 + ϵ)-approximate median of the three input traces. To prove its correctness, our probabilistic analysis shows that an approximate median is indeed close to the unknown s. To achieve a near-linear time bound, we have to bypass the well-known dynamic programming algorithm that computes an optimal median in time O(n3).

    Original languageEnglish (US)
    Title of host publication41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2021
    EditorsMikolaj Bojanczyk, Chandra Chekuri
    PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
    ISBN (Electronic)9783959772150
    DOIs
    StatePublished - Dec 1 2021
    Event41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2021 - Virtual, Online
    Duration: Dec 15 2021Dec 17 2021

    Publication series

    NameLeibniz International Proceedings in Informatics, LIPIcs
    Volume213
    ISSN (Print)1868-8969

    Conference

    Conference41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2021
    CityVirtual, Online
    Period12/15/2112/17/21

    All Science Journal Classification (ASJC) codes

    • Software

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