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相关论文: Quantum Algorithms for Matching and Network Flows

200 篇论文

A matching in a graph is a set of edges no two of which share a common vertex. A matching M is an induced matching if no edge connects two edges of M. The problem of finding a maximum induced matching is known to be NP-hard in general and…

离散数学 · 计算机科学 2014-04-28 Ruzayn Quaddoura

We introduce a `concrete complexity' model for studying algorithms for matching in bipartite graphs. The model is based on the "demand query" model used for combinatorial auctions. Most (but not all) known algorithms for bipartite matching…

计算复杂性 · 计算机科学 2019-06-12 Noam Nisan

The Maximum Matching problem has a quantum query complexity lower bound of $\Omega(n^{3/2})$ for graphs on $n$ vertices represented by an adjacency matrix. The current best quantum algorithm has the query complexity $O(n^{7/4})$, which is…

量子物理 · 物理学 2025-10-31 Alcides Gomes Andrade Júnior , Akira Matsubayashi

We present two deterministic dynamic algorithms for the maximum matching problem. (1) An algorithm that maintains a $(2+\epsilon)$-approximate maximum matching in general graphs with $O(\text{poly}(\log n, 1/\epsilon))$ update time. (2) An…

数据结构与算法 · 计算机科学 2016-04-21 Sayan Bhattacharya , Monika Henzinger , Danupon Nanongkai

We are presented with a graph, $G$, on $n$ vertices with $m$ edges whose edge set is unknown. Our goal is to learn the edges of $G$ with as few queries to an oracle as possible. When we submit a set $S$ of vertices to the oracle, it tells…

量子物理 · 物理学 2024-03-01 Asaf Ferber , Liam Hardiman

We give an iterative algorithm for finding the maximum flow between a set of sources and sinks that lie on the boundary of a planar graph. Our algorithm uses only O(n) queries to simple data structures, achieving an O(n log n) running time…

数据结构与算法 · 计算机科学 2013-06-25 Glencora Borradaile , Anna Harutyunyan

The bottleneck network flow problem (BNFP) is a generalization of several well-studied bottleneck problems such as the bottleneck transportation problem (BTP), bottleneck assignment problem (BAP), bottleneck path problem (BPP), and so on.…

数据结构与算法 · 计算机科学 2007-12-27 Abraham P. Punnen , Ruonan Zhang

In this paper we present an O(n log n) algorithm for finding a maximum flow in a directed planar graph, where the vertices are subject to capacity constraints, in addition to the arcs. If the source and the sink are on the same face, then…

离散数学 · 计算机科学 2009-05-05 Haim Kaplan , Yahav Nussbaum

We give the first O(m polylog(n)) time algorithms for approximating maximum flows in undirected graphs and constructing polylog(n) -quality cut-approximating hierarchical tree decompositions. Our algorithm invokes existing algorithms for…

数据结构与算法 · 计算机科学 2015-11-18 Richard Peng

We study a variant of the subgraph isomorphism problem that is of high interest to the quantum computing community. Our results give an algorithm to perform pattern matching in quantum circuits for many patterns simultaneously,…

量子物理 · 物理学 2024-02-22 Luca Mondada , Pablo Andrés-Martínez

We study the maximum matching problem in the random-order semi-streaming setting. In this problem, the edges of an arbitrary $n$-vertex graph $G=(V, E)$ arrive in a stream one by one and in a random order. The goal is to have a single pass…

数据结构与算法 · 计算机科学 2021-03-02 Sepehr Assadi , Soheil Behnezhad

In this paper we provide an algorithm which given any $m$-edge $n$-vertex directed graph with integer capacities at most $U$ computes a maximum $s$-$t$ flow for any vertices $s$ and $t$ in $m^{4/3+o(1)}U^{1/3}$ time. This improves upon the…

数据结构与算法 · 计算机科学 2020-04-16 Yang P. Liu , Aaron Sidford

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

数据结构与算法 · 计算机科学 2020-09-02 Yin Tat Lee , Aaron Sidford

We present space-efficient algorithms for computing cut vertices in a given graph with $n$ vertices and $m$ edges in linear time using $O(n+\min\{m,n\log \log n\})$ bits. With the same time and using $O(n+m)$ bits, we can compute the…

数据结构与算法 · 计算机科学 2016-12-09 Frank Kammer , Dieter Kratsch , Moritz Laudahn

This paper explores the use of quantum computing, specifically the use of HHL and VQLS algorithms, to solve optimal power flow problem in electrical grids. We investigate the effectiveness of these quantum algorithms in comparison to…

量子物理 · 物理学 2024-12-10 Sajad Fathi Hafshejani , Md Mohsin Uddin , David Neufeld , Daya Gaur , Robert Benkoczi

We consider the well-studied problem of finding a perfect matching in $d$-regular bipartite graphs with $2n$ vertices and $m = nd$ edges. While the best-known algorithm for general bipartite graphs (due to Hopcroft and Karp) takes $O(m…

数据结构与算法 · 计算机科学 2009-07-30 Ashish Goel , Michael Kapralov , Sanjeev Khanna

In this survey, we describe two recent developments in quantum algorithms. The first new development is a quantum algorithm for evaluating a Boolean formula consisting of AND and OR gates of size N in time O(\sqrt{N}). This provides quantum…

量子物理 · 物理学 2015-05-19 Andris Ambainis

We give an O(sqrt n log n)-query quantum algorithm for evaluating size-n AND-OR formulas. Its running time is poly-logarithmically greater after efficient preprocessing. Unlike previous approaches, the algorithm is based on a quantum walk…

量子物理 · 物理学 2011-10-11 Ben W. Reichardt

We present an $\tilde O(m+n^{1.5})$-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on $m$-edge, $n$-node graphs. For…

数据结构与算法 · 计算机科学 2021-10-15 Jan van den Brand , Yin-Tat Lee , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Aaron Sidford , Zhao Song , Di Wang

We provide $\widetilde{O}(\epsilon^{-1})$-pass semi-streaming algorithms for computing $(1-\epsilon)$-approximate maximum cardinality matchings in bipartite graphs. Our most efficient methods are deterministic and use optimal, $O(n)$,…

数据结构与算法 · 计算机科学 2021-08-04 Sepehr Assadi , Arun Jambulapati , Yujia Jin , Aaron Sidford , Kevin Tian