AG Codes Achieve List Decoding Capacity over Constant-Sized Fields
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi, Zihan Zhang
摘要
The recently-emerging field of higher order MDS codes has sought to unify a number of concepts in coding theory. Such areas captured by higher order MDS codes include maximally recoverable (MR) tensor codes, codes with optimal list-decoding guarantees, and codes with constrained generator matrices (as in the GM-MDS theorem). By proving these equivalences, Brakensiek-Gopi-Makam showed the existence of optimally list-decodable Reed-Solomon codes over exponential sized fields. Building on this, recent breakthroughs by Guo-Zhang and Alrabiah-Guruswami-Li have shown that randomly punctured Reed-Solomon codes achieve list-decoding capacity (which is a relaxation of optimal list-decodability) over linear size fields. We extend these works by developing a formal theory of relaxed higher order MDS codes. In particular, we show that there are two inequivalent relaxations which we call lower and upper relaxations. The lower relaxation is equivalent to relaxed optimal list-decodable codes and the upper relaxation is equivalent to relaxed MR tensor codes with a single parity check per column. We then generalize the techniques of Guo-Zhang and Alrabiah-Guruswami-Li to show that both these relaxations can be constructed over constant size fields by randomly puncturing suitable algebraic-geometric codes. For this, we crucially use the generalized GM-MDS theorem for polynomial codes recently proved by Brakensiek-Dhar-Gopi. We obtain the following corollaries from our main result: Randomly punctured algebraic-geometric codes of rate R are list-decodable up to radius L/L+1(1−R−є) with list size L over fields of size exp(O(L/є)). In particular, they achieve list-decoding capacity with list size O(1/є) and field size exp(O(1/є2)). Prior to this work, AG codes were not even known to achieve list-decoding capacity. By randomly puncturing algebraic-geometric codes, we can construct relaxed MR tensor codes with a single parity check per column over constant-sized fields, whereas (non-relaxed) MR tensor codes require exponential field size.
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引用它的顶会 Paper9
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- From Random to Explicit via Subspace Designs with Applications to Local Properties and MatroidsJoshua Brakensiek, Yeyuan Chen, Manik Dhar, Zihan ZhangSTOC 2026 · 被引用 19 次
- Optimal Proximity Gaps for Subspace-Design Codes and (Random) Reed-Solomon CodesRohan Goyal, Venkatesan GuruswamiSTOC 2026 · 被引用 16 次
- List Decoding Expander-Based Codes up to Capacity in Near-Linear TimeShashank Srivastava, Madhur TulsianiFOCS 2025 · 被引用 11 次
- Generalized GM-MDS: Polynomial Codes Are Higher Order MDSJoshua Brakensiek, Manik Dhar, Sivakanth GopiSTOC 2024 · 被引用 6 次
它引用的顶会 Paper7
- Generic Reed-Solomon Codes Achieve List-Decoding CapacityJoshua Brakensiek, Sivakanth Gopi, Visu MakamSTOC 2023 · 被引用 22 次
- Efficient list-decoding with constant alphabet and list sizesZeyu Guo, Noga Ron-ZewiSTOC 2021 · 被引用 21 次
- Randomly Punctured Reed-Solomon Codes Achieve the List Decoding Capacity over Polynomial-Size AlphabetsZeyu Guo, Zihan ZhangFOCS 2023 · 被引用 20 次
- Randomly Punctured Reed-Solomon Codes Achieve List-Decoding Capacity over Linear-Sized FieldsOmar Alrabiah, Venkatesan Guruswami, Ray LiSTOC 2024 · 被引用 17 次
- Generalized GM-MDS: Polynomial Codes Are Higher Order MDSJoshua Brakensiek, Manik Dhar, Sivakanth GopiSTOC 2024 · 被引用 6 次
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