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Bivariate Linear Operator Codes

Aaron L. Putterman, Vadim Zaripov

TL;DR

The paper generalizes the linear operator code framework from univariate to bivariate polynomials, formulating B-LO and its LELO extension (B-LELO) to capture a broader class of capacity-achieving, list-decodable codes. It proves a general list-decoding theorem for B-LELO codes under a list-composition criterion, unifying previous results for LO-based codes and enabling capacity-list-decodability proofs in the multivariate setting. A key achievement is showing that Permuted Product Codes (PPC) fit neatly into the B-LELO framework, thereby deriving their list-decodability up to capacity and connecting PPC with RS/FRS/Multiplicity families. The framework suggests new avenues for discovering additional capacity-achieving codes by exploring higher-dimensional operator families and their interactions, with potential impact on explicit constructions in coding theory.

Abstract

In this work, we present a generalization of the linear operator family of codes that captures more codes that achieve list decoding capacity. Linear operator (LO) codes were introduced by Bhandari, Harsha, Kumar, and Sudan [BHKS24] as a way to capture capacity-achieving codes. In their framework, a code is specified by a collection of linear operators that are applied to a message polynomial and then evaluated at a specified set of evaluation points. We generalize this idea in a way that can be applied to bivariate message polynomials, getting what we call bivariate linear operator (B-LO) codes. We show that bivariate linear operator codes capture more capacity-achieving codes, including permuted product codes introduced by Berman, Shany, and Tamo [BST24]. These codes work with bivariate message polynomials, which is why our generalization is necessary to capture them as a part of the linear operator framework. Similarly to the initial paper on linear operator codes, we present sufficient conditions for a bivariate linear operator code to be list decodable. Using this characterization, we are able to derive the theorem characterizing list-decodability of LO codes as a specific case of our theorem for B-LO codes. We also apply this theorem to show that permuted product codes are list decodable up to capacity, thereby unifying this result with those of known list-decodable LO codes, including Folded Reed-Solomon, Multiplicity, and Affine Folded Reed-Solomon codes.

Bivariate Linear Operator Codes

TL;DR

The paper generalizes the linear operator code framework from univariate to bivariate polynomials, formulating B-LO and its LELO extension (B-LELO) to capture a broader class of capacity-achieving, list-decodable codes. It proves a general list-decoding theorem for B-LELO codes under a list-composition criterion, unifying previous results for LO-based codes and enabling capacity-list-decodability proofs in the multivariate setting. A key achievement is showing that Permuted Product Codes (PPC) fit neatly into the B-LELO framework, thereby deriving their list-decodability up to capacity and connecting PPC with RS/FRS/Multiplicity families. The framework suggests new avenues for discovering additional capacity-achieving codes by exploring higher-dimensional operator families and their interactions, with potential impact on explicit constructions in coding theory.

Abstract

In this work, we present a generalization of the linear operator family of codes that captures more codes that achieve list decoding capacity. Linear operator (LO) codes were introduced by Bhandari, Harsha, Kumar, and Sudan [BHKS24] as a way to capture capacity-achieving codes. In their framework, a code is specified by a collection of linear operators that are applied to a message polynomial and then evaluated at a specified set of evaluation points. We generalize this idea in a way that can be applied to bivariate message polynomials, getting what we call bivariate linear operator (B-LO) codes. We show that bivariate linear operator codes capture more capacity-achieving codes, including permuted product codes introduced by Berman, Shany, and Tamo [BST24]. These codes work with bivariate message polynomials, which is why our generalization is necessary to capture them as a part of the linear operator framework. Similarly to the initial paper on linear operator codes, we present sufficient conditions for a bivariate linear operator code to be list decodable. Using this characterization, we are able to derive the theorem characterizing list-decodability of LO codes as a specific case of our theorem for B-LO codes. We also apply this theorem to show that permuted product codes are list decodable up to capacity, thereby unifying this result with those of known list-decodable LO codes, including Folded Reed-Solomon, Multiplicity, and Affine Folded Reed-Solomon codes.

Paper Structure

This paper contains 18 sections, 5 theorems, 31 equations.

Key Result

theorem 1.1

Suppose $\mathbb{F}$ is a field of size $q$ and $L:\mathbb{F}[X]\to \mathbb{F}[X]$ a degree-preserving linear operator and $A$ a set of evaluation points such that for $\mathcal{L}= (L^0, L^1, \dots,L^{s-1})$ the corresponding code $\mathcal{C}$ is a linearly-extendible linear operator code. Furthe

Theorems & Definitions (22)

  • theorem 1.1: BHKS24
  • theorem 1.2
  • theorem 1.3
  • definition 2.1: codes, rate, distance
  • definition 2.2: linear codes
  • definition 2.3: list decoding
  • definition 2.4: list-decoding capacity
  • definition 2.5: Reed-Solomon code
  • definition 2.6: Folded Reed-Solomon code
  • definition 2.7: Permuted Product code BST24
  • ...and 12 more