随机里德-所罗门码可通过最佳列表大小进行列表恢复

Dean Doron, S. Venkitesh
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摘要

我们证明,对于任意输入列表大小,具有随机评估点的里德-所罗门(RS)码都能以最佳输出列表大小进行列表恢复。也就是说,给定输入列表大小 $\ell$、指定速率 $R$、任意 $\varepsilon > 0$,我们证明了随机 RS 码在字段大小为 $q=\exp(\ell,1/\varepsilon) \cdot n^2$ 时,可以通过输出列表大小 $L =O(\ell/\varepsilon)$ 从 $1-R-\varepsilon$ 的错误中进行列表恢复。特别是,这表明随机 RS 编码的列表恢复能力超过了 "列表恢复约翰逊边界"。这样的结果甚至连任意随机线性编码都不知道。我们的技术继承并扩展了最近关于随机 RS 码列表解码的工作,特别是 Brakensiek、Gopi 和 Makam(STOC 2023)以及 Guo 和 Zhang(FOCS 2023)的工作。
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Random Reed-Solomon Codes are List Recoverable with Optimal List Size
We prove that Reed-Solomon (RS) codes with random evaluation points are list recoverable up to capacity with optimal output list size, for any input list size. Namely, given an input list size $\ell$, a designated rate $R$, and any $\varepsilon > 0$, we show that a random RS code is list recoverable from $1-R-\varepsilon$ fraction of errors with output list size $L = O(\ell/\varepsilon)$, for field size $q=\exp(\ell,1/\varepsilon) \cdot n^2$. In particular, this shows that random RS codes are list recoverable beyond the ``list recovery Johnson bound''. Such a result was not even known for arbitrary random linear codes. Our technique follows and extends the recent line of work on list decoding of random RS codes, specifically the works of Brakensiek, Gopi, and Makam (STOC 2023), and of Guo and Zhang (FOCS 2023).
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