On List Recovery of High-Rate Tensor Codes

Abstract

We continue the study of list recovery properties of high-rate tensor codes, initiated by Hemenway, Ron-Zewi, and Wootters (FOCS'17). In that work it was shown that the tensor product of an efficient (poly-time) high-rate globally list recoverable code is approximately locally list recoverable, as well as globally list recoverable in probabilistic near-linear time. This was used in turn to give the first capacity-achieving list decodable codes with (1) local list decoding algorithms, and with (2) probabilistic near-linear time global list decoding algorithms. This also yielded constant-rate codes approaching the Gilbert-Varshamov bound with probabilistic near-linear time global unique decoding algorithms. In the current work we obtain the following results: 1. The tensor product of an efficient (poly-time) high-rate globally list recoverable code is globally list recoverable in deterministic near-linear time. This yields in turn the first capacity-achieving list decodable codes with deterministic near-linear time global list decoding algorithms. It also gives constant-rate codes approaching the Gilbert-Varshamov bound with deterministic near-linear time global unique decoding algorithms. 2. If the base code is additionally locally correctable, then the tensor product is (genuinely) locally list recoverable. This yields in turn (non-explicit) constant-rate codes approaching the Gilbert-Varshamov bound that are locally correctable with query complexity and running time N o(1). This improves over prior work by Gopi et. al. (SODA'17; IEEE Transactions on Information Theory'18) that only gave query complexity N ε with rate that is exponentially small in 1/ε. 3. A nearly-tight combinatorial lower bound on output list size for list recovering high-rate tensor codes. This bound implies in turn a nearly-tight lower bound of N Ω(1/ log log N) on the product of query complexity and output list size for locally list recovering high-rate tensor codes. 2012 ACM Subject Classification Mathematics of computing → Coding theory; Theory of computation → Pseudorandomness and derandomization Keywords and phrases Coding theory, Tensor codes, List-decoding and recovery, Local codes

Synchronization Strings and Codes for Insertions and Deletions -- a Survey

“…Therefore, it would allow one to improve the decoding complexity of these codes upon discovery of high-rate list-recoverable codes with faster decoders, potentially to near-linear time. A recent work of Kopparty et al [47] has broken this barrier and offers listrecoverable tensor codes with a deterministic n 1+o (1) time decoding. Using such codes in a similar scheme would yield a near-linear time list-decodable family of codes with similar properties as of Theorem 2.8 albeit over alphabet sizes that grow in terms of the block length of the code.…”