Power Series Composition in Near-Linear Time

Fuente: arXiv
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Auteurs principaux: Kinoshita, Yasunori, Li, Baitian
Format: Preprint
Publié: 2024
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author Kinoshita, Yasunori
Li, Baitian
author_facet Kinoshita, Yasunori
Li, Baitian
contents We present an algebraic algorithm that computes the composition of two power series in softly linear time complexity. The previous best algorithms are $\mathop{\mathrm O}(n^{1+o(1)})$ by Kedlaya and Umans (FOCS 2008) and an $\mathop{\mathrm O}(n^{1.43})$ algebraic algorithm by Neiger, Salvy, Schost and Villard (JACM 2023). Our algorithm builds upon the recent Graeffe iteration approach to manipulate rational power series introduced by Bostan and Mori (SOSA 2021).
format Preprint
id arxiv_https___arxiv_org_abs_2404_05177
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Power Series Composition in Near-Linear Time
Kinoshita, Yasunori
Li, Baitian
Symbolic Computation
I.1.2
We present an algebraic algorithm that computes the composition of two power series in softly linear time complexity. The previous best algorithms are $\mathop{\mathrm O}(n^{1+o(1)})$ by Kedlaya and Umans (FOCS 2008) and an $\mathop{\mathrm O}(n^{1.43})$ algebraic algorithm by Neiger, Salvy, Schost and Villard (JACM 2023). Our algorithm builds upon the recent Graeffe iteration approach to manipulate rational power series introduced by Bostan and Mori (SOSA 2021).
title Power Series Composition in Near-Linear Time
topic Symbolic Computation
I.1.2
url https://arxiv.org/abs/2404.05177