List Recovery for Random Low-Rate Linear Codes
cs.ITmath.IT2026-05v1license
Abstract
We prove a list recovery guarantee for random low-rate linear codes over sufficiently large prime fields. For fixed dimension , error fraction , and accuracy parameter , a random -dimensional linear code is, with high probability, -list recoverable simultaneously for all input list sizes . The proof is inspired by work of Matou\v{s}ek, P\v{r}\'{\i}v\v{e}tiv\'{y}, and \v{S}kovro\v{n} on reconstructing point sets from their projections. It combines a deterministic graph-theoretic certificate, a nonvanishing determinant criterion, and the Schwartz--Zippel lemma. We also give a lower bound showing that any linear code of dimension at least two cannot be -list recoverable for feasible list sizes . In this sense, our result is nearly optimal.
Cite
@article{arxiv.2605.30101,
title = {List Recovery for Random Low-Rate Linear Codes},
author = {Isaac M Hair and Amit Sahai},
journal= {arXiv preprint arXiv:2605.30101},
year = {2026}
}