Efficient List-decoding of Polynomial Ideal Codes with Optimal List Size

Abstract

In a recent breakthrough [BGM23, GZ23, AGL23], it was shown that randomly punctured Reed-Solomon codes are list decodable with optimal list size with high probability, i.e., they attain the Singleton bound for list decoding [ST20, Rot22, GST22]. We extend this result to the family of polynomial ideal codes, a large class of error-correcting codes which includes several well-studied families of codes such as Reed-Solomon, folded Reed-Solomon, and multiplicity codes. More specifically, similarly to the Reed-Solomon setting, we show that randomly punctured polynomial ideal codes over an exponentially large alphabet exactly achieve the Singleton bound for list-decoding; while such codes over a polynomially large alphabet approximately achieve it. Combining our results with the efficient list-decoding algorithm for a large subclass of polynomial ideal codes of [BHKS21], implies as a corollary that a large subclass of polynomial ideal codes (over random evaluation points) is efficiently list decodable with optimal list size. To the best of our knowledge, this gives the first family of codes that can be efficiently list decoded with optimal list size (for all list sizes), as well as the first family of linear codes of rate $R$ that can be efficiently list decoded up to a radius of $1 -R-ε$ with list size that is polynomial (and even linear) in $1/ε$. Our result applies to natural families of codes with algebraic structure such as folded Reed-Solomon or multiplicity codes (over random evaluation points). Our proof follows the general framework of [BGM23, GZ23, AGL23], but several new ingredients are needed. The main two new ingredients are a polynomial-ideal GM-MDS theorem (extending the algebraic GM-MDS theorem of [YH19, Lov21]), as well as a duality theorem for polynomial ideal codes, both of which may be of independent interest.