16,417 research outputs found

    Fast Generation of Random Spanning Trees and the Effective Resistance Metric

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    We present a new algorithm for generating a uniformly random spanning tree in an undirected graph. Our algorithm samples such a tree in expected O~(m4/3)\tilde{O}(m^{4/3}) time. This improves over the best previously known bound of min(O~(mn),O(nω))\min(\tilde{O}(m\sqrt{n}),O(n^{\omega})) -- that follows from the work of Kelner and M\k{a}dry [FOCS'09] and of Colbourn et al. [J. Algorithms'96] -- whenever the input graph is sufficiently sparse. At a high level, our result stems from carefully exploiting the interplay of random spanning trees, random walks, and the notion of effective resistance, as well as from devising a way to algorithmically relate these concepts to the combinatorial structure of the graph. This involves, in particular, establishing a new connection between the effective resistance metric and the cut structure of the underlying graph

    Globally and Locally Minimal Weight Spanning Tree Networks

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    The competition between local and global driving forces is significant in a wide variety of naturally occurring branched networks. We have investigated the impact of a global minimization criterion versus a local one on the structure of spanning trees. To do so, we consider two spanning tree structures - the generalized minimal spanning tree (GMST) defined by Dror et al. [1] and an analogous structure based on the invasion percolation network, which we term the generalized invasive spanning tree or GIST. In general, these two structures represent extremes of global and local optimality, respectively. Structural characteristics are compared between the GMST and GIST for a fixed lattice. In addition, we demonstrate a method for creating a series of structures which enable one to span the range between these two extremes. Two structural characterizations, the occupied edge density (i.e., the fraction of edges in the graph that are included in the tree) and the tortuosity of the arcs in the trees, are shown to correlate well with the degree to which an intermediate structure resembles the GMST or GIST. Both characterizations are straightforward to determine from an image and are potentially useful tools in the analysis of the formation of network structures.Comment: 23 pages, 5 figures, 2 tables, typographical error correcte

    Distributed Approximation of Minimum Routing Cost Trees

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    We study the NP-hard problem of approximating a Minimum Routing Cost Spanning Tree in the message passing model with limited bandwidth (CONGEST model). In this problem one tries to find a spanning tree of a graph GG over nn nodes that minimizes the sum of distances between all pairs of nodes. In the considered model every node can transmit a different (but short) message to each of its neighbors in each synchronous round. We provide a randomized (2+ϵ)(2+\epsilon)-approximation with runtime O(D+lognϵ)O(D+\frac{\log n}{\epsilon}) for unweighted graphs. Here, DD is the diameter of GG. This improves over both, the (expected) approximation factor O(logn)O(\log n) and the runtime O(Dlog2n)O(D\log^2 n) of the best previously known algorithm. Due to stating our results in a very general way, we also derive an (optimal) runtime of O(D)O(D) when considering O(logn)O(\log n)-approximations as done by the best previously known algorithm. In addition we derive a deterministic 22-approximation
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