Relaxed Local Correctability from Local Testing

TL;DR

This paper introduces a novel construction of relaxed locally correctable codes with polylogarithmic query complexity, achieving near-optimal parameters by leveraging high-rate locally testable codes and recursive boosting techniques.

Contribution

It presents the first asymptotically good relaxed locally correctable codes with polylogarithmic query complexity, improving bounds close to theoretical limits.

Findings

Achieves asymptotically good relaxed locally correctable codes with polylogarithmic queries.

Uses a recursive boosting framework combining locally testable and correctable codes.

Codes approach the Gilbert-Varshamov bound in rate and distance.

Abstract

We construct the first asymptotically good relaxed locally correctable codes with polylogarithmic query complexity, bringing the upper bound polynomially close to the lower bound of Gur and Lachish (SICOMP 2021). Our result follows from showing that a high-rate locally testable code can boost the block length of a smaller relaxed locally correctable code, while preserving the correcting radius and incurring only a modest additive cost in rate and query complexity. We use the locally testable code's tester to check if the amount of corruption in the input is low; if so, we can "zoom-in" to a suitable substring of the input and recurse on the smaller code's local corrector. Hence, iterating this operation with a suitable family of locally testable codes due to Dinur, Evra, Livne, Lubotzky, and Mozes (STOC 2022) yields asymptotically good codes with relaxed local correctability, arbitrarily large block length, and polylogarithmic query complexity. Our codes asymptotically inherit the rate and distance of any locally testable code used in the final invocation of the operation. Therefore, our framework also yields nonexplicit relaxed locally correctable codes with polylogarithmic query complexity that have rate and distance approaching the Gilbert-Varshamov bound.