Even-Cycle Detection in the Randomized and Quantum CONGEST Model

Fuente: arXiv
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Autori principali: Fraigniaud, Pierre, Luce, Mael, Magniez, Frederic, Todinca, Ioan
Natura: Preprint
Pubblicazione: 2024
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author Fraigniaud, Pierre
Luce, Mael
Magniez, Frederic
Todinca, Ioan
author_facet Fraigniaud, Pierre
Luce, Mael
Magniez, Frederic
Todinca, Ioan
contents We show that, for every $k\geq 2$, $C_{2k}$-freeness can be decided in $O(n^{1-1/k})$ rounds in the \CONGEST{} model by a randomized Monte-Carlo distributed algorithm with one-sided error probability $1/3$. This matches the best round-complexities of previously known algorithms for $k\in\{2,3,4,5\}$ by Drucker et al. [PODC'14] and Censor-Hillel et al. [DISC'20], but improves the complexities of the known algorithms for $k>5$ by Eden et al. [DISC'19], which were essentially of the form $\tilde O(n^{1-2/k^2})$. Our algorithm uses colored BFS-explorations with threshold, but with an original \emph{global} approach that enables to overcome a recent impossibility result by Fraigniaud et al. [SIROCCO'23] about using colored BFS-exploration with \emph{local} threshold for detecting cycles. We also show how to quantize our algorithm for achieving a round-complexity $\tilde O(n^{\frac{1}{2}-\frac{1}{2k}})$ in the quantum setting for deciding $C_{2k}$ freeness. Furthermore, this allows us to improve the known quantum complexities of the simpler problem of detecting cycles of length \emph{at most}~$2k$ by van Apeldoorn and de Vos [PODC'22]. Our quantization is in two steps. First, the congestion of our randomized algorithm is reduced, to the cost of reducing its success probability too. Second, the success probability is boosted using a new quantum framework derived from sequential algorithms, namely Monte-Carlo quantum amplification.
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id arxiv_https___arxiv_org_abs_2402_12018
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Even-Cycle Detection in the Randomized and Quantum CONGEST Model
Fraigniaud, Pierre
Luce, Mael
Magniez, Frederic
Todinca, Ioan
Distributed, Parallel, and Cluster Computing
Quantum Physics
We show that, for every $k\geq 2$, $C_{2k}$-freeness can be decided in $O(n^{1-1/k})$ rounds in the \CONGEST{} model by a randomized Monte-Carlo distributed algorithm with one-sided error probability $1/3$. This matches the best round-complexities of previously known algorithms for $k\in\{2,3,4,5\}$ by Drucker et al. [PODC'14] and Censor-Hillel et al. [DISC'20], but improves the complexities of the known algorithms for $k>5$ by Eden et al. [DISC'19], which were essentially of the form $\tilde O(n^{1-2/k^2})$. Our algorithm uses colored BFS-explorations with threshold, but with an original \emph{global} approach that enables to overcome a recent impossibility result by Fraigniaud et al. [SIROCCO'23] about using colored BFS-exploration with \emph{local} threshold for detecting cycles. We also show how to quantize our algorithm for achieving a round-complexity $\tilde O(n^{\frac{1}{2}-\frac{1}{2k}})$ in the quantum setting for deciding $C_{2k}$ freeness. Furthermore, this allows us to improve the known quantum complexities of the simpler problem of detecting cycles of length \emph{at most}~$2k$ by van Apeldoorn and de Vos [PODC'22]. Our quantization is in two steps. First, the congestion of our randomized algorithm is reduced, to the cost of reducing its success probability too. Second, the success probability is boosted using a new quantum framework derived from sequential algorithms, namely Monte-Carlo quantum amplification.
title Even-Cycle Detection in the Randomized and Quantum CONGEST Model
topic Distributed, Parallel, and Cluster Computing
Quantum Physics
url https://arxiv.org/abs/2402.12018