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List Decoding Expander-Based Codes via Fast Approximation of Expanding CSPs: I

Published: September 5, 2025 | arXiv ID: 2509.05203v1

By: Fernando Granha Jeronimo, Aman Singh

Potential Business Impact:

Makes computers fix garbled messages faster.

Business Areas:
DSP Hardware

We present near-linear time list decoding algorithms (in the block-length $n$) for expander-based code constructions. More precisely, we show that (i) For every $\delta \in (0,1)$ and $\epsilon > 0$, there is an explicit family of good Tanner LDPC codes of (design) distance $\delta$ that is $(\delta - \epsilon, O_\varepsilon(1))$ list decodable in time $\widetilde{\mathcal{O}}_{\varepsilon}(n)$ with alphabet size $O_\delta(1)$, (ii) For every $R \in (0,1)$ and $\epsilon > 0$, there is an explicit family of AEL codes of rate $R$, distance $1-R -\varepsilon$ that is $(1-R-\epsilon, O_\varepsilon(1))$ list decodable in time $\widetilde{\mathcal{O}}_{\varepsilon}(n)$ with alphabet size $\text{exp}(\text{poly}(1/\epsilon))$, and (iii) For every $R \in (0,1)$ and $\epsilon > 0$, there is an explicit family of AEL codes of rate $R$, distance $1-R-\varepsilon$ that is $(1-R-\epsilon, O(1/\epsilon))$ list decodable in time $\widetilde{\mathcal{O}}_{\varepsilon}(n)$ with alphabet size $\text{exp}(\text{exp}(\text{poly}(1/\epsilon)))$ using recent near-optimal list size bounds from [JMST25]. Our results are obtained by phrasing the decoding task as an agreement CSP [RWZ20,DHKNT19] on expander graphs and using the fast approximation algorithm for $q$-ary expanding CSPs from [Jer23], which is based on weak regularity decomposition [JST21,FK96]. Similarly to list decoding $q$-ary Ta-Shma's codes in [Jer23], we show that it suffices to enumerate over assignments that are constant in each part (of the constantly many) of the decomposition in order to recover all codewords in the list.

Country of Origin
🇺🇸 United States

Page Count
25 pages

Category
Computer Science:
Data Structures and Algorithms