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We present an algorithm that, with high probability, generates a random spanning tree from an edge-weighted undirected graph in $\tilde{O}(n^{4/3}m^{1/2}+n^{2})$ time (The $\tilde{O}(\cdot)$ notation hides $\operatorname{polylog}(n)$…

Data Structures and Algorithms · Computer Science 2017-06-22 David Durfee , Rasmus Kyng , John Peebles , Anup B. Rao , Sushant Sachdeva

In this paper, we set forth a new algorithm for generating approximately uniformly random spanning trees in undirected graphs. We show how to sample from a distribution that is within a multiplicative $(1+\delta)$ of uniform in expected…

Data Structures and Algorithms · Computer Science 2009-08-12 Jonathan A. Kelner , Aleksander Madry

We present a new algorithm for generating a uniformly random spanning tree in an undirected graph. Our algorithm samples such a tree in expected $\tilde{O}(m^{4/3})$ time. This improves over the best previously known bound of…

Data Structures and Algorithms · Computer Science 2017-03-16 Aleksander Madry , Damian Straszak , Jakub Tarnawski

We give an $m^{1+o(1)}\beta^{o(1)}$-time algorithm for generating a uniformly random spanning tree in an undirected, weighted graph with max-to-min weight ratio $\beta$. We also give an $m^{1+o(1)}\epsilon^{-o(1)}$-time algorithm for…

Data Structures and Algorithms · Computer Science 2017-11-20 Aaron Schild

We give an algorithm for finding the arboricity of a weighted, undirected graph, defined as the minimum number of spanning forests that cover all edges of the graph, in $\sqrt{n} m^{1+o(1)}$ time. This improves on the previous best bound of…

Data Structures and Algorithms · Computer Science 2025-07-22 Ruoxu Cen , Henry Fleischmann , George Z. Li , Jason Li , Debmalya Panigrahi

We study the problem of maximizing the number of spanning trees in a connected graph by adding at most $k$ edges from a given candidate edge set. We give both algorithmic and hardness results for this problem: - We give a greedy algorithm…

Data Structures and Algorithms · Computer Science 2018-07-17 Huan Li , Stacy Patterson , Yuhao Yi , Zhongzhi Zhang

We present a quantum algorithm for sampling random spanning trees from a weighted graph in $\widetilde{O}(\sqrt{mn})$ time, where $n$ and $m$ denote the number of vertices and edges, respectively. Our algorithm has sublinear runtime for…

Quantum Physics · Physics 2025-04-25 Simon Apers , Minbo Gao , Zhengfeng Ji , Chenghua Liu

We present an algorithm for min-cost flow in graphs with $n$ vertices and $m$ edges, given a tree decomposition of width $\tau$ and size $S$, and polynomially bounded, integral edge capacities and costs, running in…

Data Structures and Algorithms · Computer Science 2024-07-02 Sally Dong , Guanghao Ye

We present new approaches to constructing graph sparsifiers --- weighted subgraphs for which every cut has the same value as the original graph, up to a factor of $(1 \pm \epsilon)$. Our first approach independently samples each edge $uv$…

Data Structures and Algorithms · Computer Science 2010-08-10 Wai Shing Fung , Nicholas J. A. Harvey

We provide new algorithms and conditional hardness for the problem of estimating effective resistances in $n$-node $m$-edge undirected, expander graphs. We provide an $\widetilde{O}(m\epsilon^{-1})$-time algorithm that produces with high…

Data Structures and Algorithms · Computer Science 2023-06-27 Rajat Vadiraj Dwaraknath , Ishani Karmarkar , Aaron Sidford

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate our technique by proving that in random order streams with…

Data Structures and Algorithms · Computer Science 2017-11-15 Pan Peng , Christian Sohler

Constructing a sparse spanning subgraph is a fundamental primitive in graph theory. In this paper, we study this problem in the Centralized Local model, where the goal is to decide whether an edge is part of the spanning subgraph by…

Data Structures and Algorithms · Computer Science 2017-07-20 Christoph Lenzen , Reut Levi

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge $e$ is in a specific spanning tree,…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld

We demonstrate that for expander graphs, for all $\epsilon > 0,$ there exists a data structure of size $\widetilde{O}(n\epsilon^{-1})$ which can be used to return $(1 + \epsilon)$-approximations to effective resistances in…

Data Structures and Algorithms · Computer Science 2022-11-04 Lawrence Li , Sushant Sachdeva

We present faster algorithms for approximate maximum flow in undirected graphs with good separator structures, such as bounded genus, minor free, and geometric graphs. Given such a graph with $n$ vertices, $m$ edges along with a recursive…

Data Structures and Algorithms · Computer Science 2012-10-19 Gary Miller , Richard Peng

We consider the ``minimum degree spanning tree'' problem. As input, we receive an undirected, connected graph $G=(V, E)$ with $n$ nodes and $m$ edges, and our task is to find a spanning tree $T$ of $G$ that minimizes $\max_{u \in V}…

Data Structures and Algorithms · Computer Science 2026-03-02 Sayan Bhattacharya , Ermiya Farokhnejad , Haoze Wang

The girth of a graph, i.e. the length of its shortest cycle, is a fundamental graph parameter. Unfortunately all known algorithms for computing, even approximately, the girth and girth-related structures in directed weighted $m$-edge and…

Data Structures and Algorithms · Computer Science 2018-08-14 Jakub Pachocki , Liam Roditty , Aaron Sidford , Roei Tov , Virginia Vassilevska Williams

We propose an efficient algorithm for graph matching based on similarity scores constructed from counting a certain family of weighted trees rooted at each vertex. For two Erd\H{o}s-R\'enyi graphs $\mathcal{G}(n,q)$ whose edges are…

Data Structures and Algorithms · Computer Science 2023-02-15 Cheng Mao , Yihong Wu , Jiaming Xu , Sophie H. Yu

The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…

Data Structures and Algorithms · Computer Science 2020-09-24 Jakub Tětek

We develop a time-optimal $O(mn^2)$-time algorithm to construct the subtree prune-regraft (SPR) graph on a collection of m phylogenetic trees with n leaves. This improves on the previous bound of $O(mn^3)$. Such graphs are used to better…

Data Structures and Algorithms · Computer Science 2017-04-28 Chris Whidden , Frederick A. Matsen
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