Near-Optimal List-Recovery of Linear Code Families
Ray Li, Nikhil Shagrithaya

TL;DR
This paper demonstrates that random linear codes nearly achieve the theoretical limits of list-recovery capacity, providing new bounds and showing that certain Reed-Solomon codes also attain this capacity.
Contribution
It proves that random linear codes and punctured Reed-Solomon codes achieve list-recovery capacity with constant list size, and establishes near-optimal bounds on list size for linear codes.
Findings
Random linear codes achieve list-recovery capacity with constant list size.
Punctured Reed-Solomon codes also attain list-recovery capacity.
Established near-optimal bounds on list size for linear codes.
Abstract
We prove several results on linear codes achieving list-recovery capacity. We show that random linear codes achieve list-recovery capacity with constant output list size (independent of the alphabet size and length). That is, over alphabets of size at least , random linear codes of rate are -list-recoverable for all and . Together with a result of Levi, Mosheiff, and Shagrithaya, this implies that randomly punctured Reed-Solomon codes also achieve list-recovery capacity. We also prove that our output list size is near-optimal among all linear codes: all -list-recoverable linear codes must have . Our simple upper bound combines the Zyablov-Pinsker argument with recent bounds from Kopparty, Ron-Zewi, Saraf,…
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