Dynamic (1+ϵ)-Approximate Matching Size in Truly Sublinear Update Time

Dynamic (1+ϵ)-Approximate Matching Size in Truly Sublinear Update Time
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真正次线性更新时间内的动态 (1+ϵ)-近似匹配大小

DOI:
10.1109/focs57990.2023.00095
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发表时间:
2023
期刊:
2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS)
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--
通讯作者:
Thatchaphol Saranurak
Thatchaphol Saranurak
中科院分区:
--
文献类型:
--
作者:
Sayan Bhattacharya;Peter Kiss;Thatchaphol Saranurak

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我们给出了一个完全动态的算法,用$m^{0.5-\Omega_{\epsilon}(1)}$更新时间来保持n点m边图的最大匹配的$(1+\epsilon)$-近似大小。这是对长期存在的$O(N)$更新时间的第一次多项式改进,该时间可以通过定期重新计算获得。因此,我们解决了动态图算法文献(例如,参见[Gupta and Peng FOCS‘13]、[Bernstein and Stein Soda’16]、[Behnezhad and Khanna Soda‘22])的一个主要开放问题的值版本。我们的关键技术部分是关于稠密图上运行时间为次线性的$(1,n)$的第一个次线性算法。所有以前的算法都经历了至少1.499的乘法逼近因子,或者假设图具有非常小的最大度。
We show a fully dynamic algorithm for maintaining $(1+\epsilon)$-approximate size of maximum matching of the graph with n vertices and m edges using $m^{0.5-\Omega_{\epsilon}(1)}$ update time. This is the first polynomial improvement over the long-standing $O(n)$ update time, which can be trivially obtained by periodic recomputation. Thus, we resolve the value version of a major open question of the dynamic graph algorithms literature (see, e.g., [Gupta and Peng FOCS’13], [Bernstein and Stein SODA’16], [Behnezhad and Khanna SODA’22]). Our key technical component is the first sublinear algorithm for $(1, \epsilon n)$-approximate maximum matching with sublinear running time on dense graphs. All previous algorithms suffered a multiplicative approximation factor of at least 1.499 or assumed that the graph has a very small maximum degree.
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