License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2020.34
URN: urn:nbn:de:0030-drops-126372
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12637/
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Guruswami, Venkatesan ; Opršal, Jakub ; Sandeep, Sai

Revisiting Alphabet Reduction in Dinur’s PCP

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LIPIcs-APPROX34.pdf (0.5 MB)

Abstract

Dinur’s celebrated proof of the PCP theorem alternates two main steps in several iterations: gap amplification to increase the soundness gap by a large constant factor (at the expense of much larger alphabet size), and a composition step that brings back the alphabet size to an absolute constant (at the expense of a fixed constant factor loss in the soundness gap). We note that the gap amplification can produce a Label Cover CSP. This allows us to reduce the alphabet size via a direct long-code based reduction from Label Cover to a Boolean CSP. Our composition step thus bypasses the concept of Assignment Testers from Dinur’s proof, and we believe it is more intuitive - it is just a gadget reduction. The analysis also uses only elementary facts (Parseval’s identity) about Fourier Transforms over the hypercube.

BibTeX - Entry

@InProceedings{guruswami_et_al:LIPIcs:2020:12637,
  author =	{Venkatesan Guruswami and Jakub Opr{\v{s}}al and Sai Sandeep},
  title =	{{Revisiting Alphabet Reduction in Dinur’s PCP}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)},
  pages =	{34:1--34:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-164-1},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{176},
  editor =	{Jaros{\l}aw Byrka and Raghu Meka},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12637},
  URN =		{urn:nbn:de:0030-drops-126372},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2020.34},
  annote =	{Keywords: PCP theorem, CSP, discrete Fourier analysis, label cover, long code}
}

Keywords: PCP theorem, CSP, discrete Fourier analysis, label cover, long code
Collection: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)
Issue Date: 2020
Date of publication: 11.08.2020

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