TY - GEN
T1 - List-Recovery of Random Linear Codes over Small Fields
AU - Doron, Dean
AU - Mosheiff, Jonathan
AU - Resch, Nicolas
AU - Ribeiro, João
N1 - Publisher Copyright: © Dean Doron, Jonathan Mosheiff, Nicolas Resch, and João Ribeiro; licensed under Creative Commons License CC-BY 4.0.
PY - 2025/9/15
Y1 - 2025/9/15
N2 - We study list-recoverability of random linear codes over small fields, both from errors and from erasures. We consider codes of rate ϵ-close to capacity, and aim to bound the dependence of the output list size L on ϵ, the input list size ℓ, and the alphabet size q. Prior to our work, the best upper bound was L = qO(ℓ/ϵ) (Zyablov and Pinsker, Prob. Per. Inf. 1981). Previous work has identified cases in which linear codes provably perform worse than non-linear codes with respect to list-recovery. While there exist non-linear codes that achieve L = O(ℓ/ϵ), we know that L ≥ ℓΩ(1/ϵ) is necessary for list recovery from erasures over fields of small characteristic, and for list recovery from errors over large alphabets. We show that in other relevant regimes there is no significant price to pay for linearity, in the sense that we get the correct dependence on the gap-to-capacity ϵ and go beyond the Zyablov-Pinsker bound for the first time. Specifically, when q is constant and ϵ approaches zero, For list-recovery from erasures over prime fields, we show that L ≥ C1/ϵ. By prior work, such a result cannot be obtained for low-characteristic fields. For list-recovery from errors over arbitrary fields, we prove that L ≥ C2/ϵ. Above, C1 and C2 depend on the decoding radius, input list size, and field size. We provide concrete bounds on the constants above, and the upper bounds on L improve upon the Zyablov-Pinsker bound whenever q ≥ 2(1/ϵ)c for some small universal constant c > 0.
AB - We study list-recoverability of random linear codes over small fields, both from errors and from erasures. We consider codes of rate ϵ-close to capacity, and aim to bound the dependence of the output list size L on ϵ, the input list size ℓ, and the alphabet size q. Prior to our work, the best upper bound was L = qO(ℓ/ϵ) (Zyablov and Pinsker, Prob. Per. Inf. 1981). Previous work has identified cases in which linear codes provably perform worse than non-linear codes with respect to list-recovery. While there exist non-linear codes that achieve L = O(ℓ/ϵ), we know that L ≥ ℓΩ(1/ϵ) is necessary for list recovery from erasures over fields of small characteristic, and for list recovery from errors over large alphabets. We show that in other relevant regimes there is no significant price to pay for linearity, in the sense that we get the correct dependence on the gap-to-capacity ϵ and go beyond the Zyablov-Pinsker bound for the first time. Specifically, when q is constant and ϵ approaches zero, For list-recovery from erasures over prime fields, we show that L ≥ C1/ϵ. By prior work, such a result cannot be obtained for low-characteristic fields. For list-recovery from errors over arbitrary fields, we prove that L ≥ C2/ϵ. Above, C1 and C2 depend on the decoding radius, input list size, and field size. We provide concrete bounds on the constants above, and the upper bounds on L improve upon the Zyablov-Pinsker bound whenever q ≥ 2(1/ϵ)c for some small universal constant c > 0.
KW - List recovery
KW - random linear codes
UR - https://www.scopus.com/pages/publications/105019534586
U2 - 10.4230/LIPIcs.APPROX/RANDOM.2025.57
DO - 10.4230/LIPIcs.APPROX/RANDOM.2025.57
M3 - Conference contribution
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2025
A2 - Ene, Alina
A2 - Chattopadhyay, Eshan
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 28th International Conference on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2025 and the 29th International Conference on Randomization and Computation, RANDOM 2025
Y2 - 11 August 2025 through 13 August 2025
ER -