Polynomially Low Error PCPs with polyloglog n Queries via Modular Composition
Irit Dinur, Prahladh Harsha, Guy Kindler

TL;DR
This paper presents a new PCP construction with exponentially improved parameters, achieving low error with polyloglog n queries and small alphabet size, using a novel modular composition and distributional soundness.
Contribution
It introduces a modular PCP construction with distributional soundness, enabling multiple compositions without increasing soundness error, improving previous bounds significantly.
Findings
Achieves $1/ ext{poly}(n)$ soundness with $O( ext{poly}\log\log n)$ queries
Uses a new notion of distributional soundness for modular composition
Provides an exponential improvement over prior PCP constructions
Abstract
We show that every language in NP has a PCP verifier that tosses random coins, has perfect completeness, and a soundness error of at most , while making at most queries into a proof over an alphabet of size at most . Previous constructions that obtain soundness error used either queries or an exponential sized alphabet, i.e. of size for some . Our result is an exponential improvement in both parameters simultaneously. Our result can be phrased as a polynomial-gap hardness for approximate CSPs with arity and alphabet size . The ultimate goal, in this direction, would be to prove polynomial hardness for CSPs with constant arity and polynomial alphabet size (aka the sliding scale conjecture for…
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Taxonomy
TopicsAlgorithms and Data Compression · Advanced Database Systems and Queries · Optical Network Technologies
