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新论文 · v1arXiv:2611.08397

一种近乎最优的广义排序算法

A Near-Optimal Generalized Sorting Algorithm

Sanjeev Khanna, Aaron Putterman, Junkai Song

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作者提出一种随机算法,在期望 O(n log^4 n) 次比较内解决广义排序问题,说明该问题在忽略对数因子后并不比普通排序更难。

cs.DS

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We continue the study of the classic \emph{generalized sorting problem}, a basic variant of ordinary sorting. There are $n$ elements and an (initially hidden) total ordering $π$ over them. Unlike in ordinary sorting, however, only \emph{some} comparisons are allowed: those given by the edges of an undirected graph $G = (V, E)$ on the elements. How many comparisons are needed to find the total ordering? In ordinary sorting, $Θ(n \log n)$ comparisons are necessary and sufficient. For generalized sorting, however, the best known upper bound has been $\tilde{O}(n^{3/2})$ since the work of Huang, Kannan, and Khanna (FOCS 2011), who even asked whether the problem might in fact require $n^{1+Ω(1)}$ comparisons. We show that it does not: we give a randomized algorithm that uses $O(n \log^4 n)$ comparisons in expectation. Thus, up to logarithmic factors, generalized sorting is no harder than ordinary sorting.