Proximity gaps for reed-solomon codes

Eli Ben-Sasson, Dan Carmon, Yuval Ishai, Swastik Kopparty, Shubhangi Saraf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

A collection of sets displays a proximity gap with respect to some property if for every set in the collection, either (i) all members are delta-close to the property in relative Hamming distance or (ii) only a tiny fraction of members are delta-close to the property. In particular, no set in the collection has roughly half of its members delta-close to the property and the others delta-far from it. We show that the collection of affine spaces displays a proximity gap with respect to Reed-Solomon (RS) codes, even over small fields, of size polynomial in the dimension of the code, and the gap applies to any delta smaller than the Johnson/Guruswami-Sudan list-decoding bound of the RS code. We also show near-optimal gap results, over fields of (at least) linear size in the RS code dimension, for delta smaller than the unique decoding radius. Concretely, if delta is smaller than half the minimal distance of an RS code v subset mathbb{F} {q}{n}, every affine space is either entirely delta-close to the code, or alternatively at most an (n/q)-fraction of it is delta-close to the code. Finally, we discuss several applications of our proximity gap results to distributed storage, multi-party cryptographic protocols, and concretely efficient proof systems. We prove the proximity gap results by analyzing the execution of classical algebraic decoding algorithms for Reed-Solomon codes (due to Berlekamp-Welch and Guruswami-Sudan) on a formal element of an affine space. This involves working with Reed-Solomon codes whose base field is an (infinite) rational function field. Our proofs are obtained by developing an extension (to function fields) of a strategy of Arora and Sudan for analyzing low-degree tests.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 61st Annual Symposium on Foundations of Computer Science, FOCS 2020
Pages900-909
Number of pages10
ISBN (Electronic)9781728196213
DOIs
StatePublished - Nov 2020
Event61st IEEE Annual Symposium on Foundations of Computer Science, FOCS 2020 - Virtual, Durham, United States
Duration: 16 Nov 202019 Nov 2020

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
Volume2020-November
ISSN (Print)0272-5428

Conference

Conference61st IEEE Annual Symposium on Foundations of Computer Science, FOCS 2020
Country/TerritoryUnited States
CityVirtual, Durham
Period16/11/2019/11/20

ASJC Scopus subject areas

  • General Computer Science

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