Hard properties with (very) short Pcpps and their applications

Omri Ben-Eliezer, Eldar Fischer, Amit Levi, Ron D. Rothblum

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

Abstract

We show that there exist properties that are maximally hard for testing, while still admitting PCPPs with a proof size very close to linear. Specifically, for every fixed `, we construct a property P(`) ⊆ {0, 1}n satisfying the following: Any testing algorithm for P(`) requires Ω(n) many queries, and yet P(`) has a constant query PCPP whose proof size is O(n · log(`) n), where log(`) denotes the ` times iterated log function (e.g., log(2) n = log log n). The best previously known upper bound on the PCPP proof size for a maximally hard to test property was O(n · polylog n). As an immediate application, we obtain stronger separations between the standard testing model and both the tolerant testing model and the erasure-resilient testing model: for every fixed `, we construct a property that has a constant-query tester, but requires Ω(n/log(`)(n)) queries for every tolerant or erasure-resilient tester.

Original languageEnglish
Title of host publication11th Innovations in Theoretical Computer Science Conference, ITCS 2020
EditorsThomas Vidick
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959771344
DOIs
StatePublished - Jan 2020
Externally publishedYes
Event11th Innovations in Theoretical Computer Science Conference, ITCS 2020 - Seattle, United States
Duration: 12 Jan 202014 Jan 2020

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume151
ISSN (Print)1868-8969

Conference

Conference11th Innovations in Theoretical Computer Science Conference, ITCS 2020
Country/TerritoryUnited States
CitySeattle
Period12/01/2014/01/20

Bibliographical note

Publisher Copyright:
© Omri Ben-Eliezer, Eldar Fischer, Amit Levi, and Ron D. Rothblum.

Keywords

  • Coding theory
  • Erasure resilient testing
  • PCPP
  • Property testing
  • Randomized encoding
  • Tolerant testing

ASJC Scopus subject areas

  • Software

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