Multidimensional Period Recovery

Amihood Amir, Ayelet Butman, Eitan Kondratovsky, Avivit Levy, Dina Sokol

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Multidimensional data are widely used in real-life applications. Intel’s new brand of SSDs, called 3D XPoint, is an example of three-dimensional data. Motivated by a structural analysis of multidimensional data, we introduce the multidimensional period recovery problem, defined as follows. The input is a d-dimensional text array, with dimensions n1× n2× ⋯ × nd, that contains corruptions, while the original text without the corruptions is periodic. The goal is then to report the period of the original text. We show that, if the number of corruptions is at most ⌊12+ϵ⌊n1p1⌋⋯⌊ndpd⌋⌋, where ϵ> 0 and p1× ⋯ × pd are the period’s dimensions, then the amount of possible period candidates is O(log N) , where N=Πi=1dni. The independency of this bound of the number of dimensions is a surprising key contribution of this paper. We present an O(Πi=1dniΠi=1dlogni) algorithm for any constant dimension d (linear time up to logarithmic factor), to report these candidates. The tightness of the bound on the number of errors enabling a small size candidate set is demonstrated by showing that if the number of errors is equal to ⌊12⌊n1p1⌋⋯⌊ndpd⌋⌋, a family of texts with Θ(N) period candidates can be constructed for any dimension d≥ 2.

Original languageEnglish
Pages (from-to)1490-1510
Number of pages21
JournalAlgorithmica
Volume84
Issue number6
DOIs
StatePublished - Jun 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Funding

Amihood Amir: Partly supported by ISF Grant 1475/18 and BSF Grant 2018141. Dina Sokol: Partly supported by BSF Grant 2018141.

FundersFunder number
United States - Israel Binational Science Foundation
United States-Israel Binational Science Foundation2018141
Israel Science Foundation1475/18

    Keywords

    • Error recovery under Hamming distance
    • Multidimensional periodicity
    • Period recovery
    • Periodicity

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