10 research outputs found

    NC Algorithms for Computing a Perfect Matching and a Maximum Flow in One-Crossing-Minor-Free Graphs

    Full text link
    In 1988, Vazirani gave an NC algorithm for computing the number of perfect matchings in K3,3K_{3,3}-minor-free graphs by building on Kasteleyn's scheme for planar graphs, and stated that this "opens up the possibility of obtaining an NC algorithm for finding a perfect matching in K3,3K_{3,3}-free graphs." In this paper, we finally settle this 30-year-old open problem. Building on recent NC algorithms for planar and bounded-genus perfect matching by Anari and Vazirani and later by Sankowski, we obtain NC algorithms for perfect matching in any minor-closed graph family that forbids a one-crossing graph. This family includes several well-studied graph families including the K3,3K_{3,3}-minor-free graphs and K5K_5-minor-free graphs. Graphs in these families not only have unbounded genus, but can have genus as high as O(n)O(n). Our method applies as well to several other problems related to perfect matching. In particular, we obtain NC algorithms for the following problems in any family of graphs (or networks) with a one-crossing forbidden minor: ∙\bullet Determining whether a given graph has a perfect matching and if so, finding one. ∙\bullet Finding a minimum weight perfect matching in the graph, assuming that the edge weights are polynomially bounded. ∙\bullet Finding a maximum stst-flow in the network, with arbitrary capacities. The main new idea enabling our results is the definition and use of matching-mimicking networks, small replacement networks that behave the same, with respect to matching problems involving a fixed set of terminals, as the larger network they replace.Comment: 21 pages, 6 figure

    Tight Bounds for Gomory-Hu-like Cut Counting

    Full text link
    By a classical result of Gomory and Hu (1961), in every edge-weighted graph G=(V,E,w)G=(V,E,w), the minimum stst-cut values, when ranging over all s,t∈Vs,t\in V, take at most ∣V∣−1|V|-1 distinct values. That is, these (∣V∣2)\binom{|V|}{2} instances exhibit redundancy factor Ω(∣V∣)\Omega(|V|). They further showed how to construct from GG a tree (V,E′,w′)(V,E',w') that stores all minimum stst-cut values. Motivated by this result, we obtain tight bounds for the redundancy factor of several generalizations of the minimum stst-cut problem. 1. Group-Cut: Consider the minimum (A,B)(A,B)-cut, ranging over all subsets A,B⊆VA,B\subseteq V of given sizes ∣A∣=α|A|=\alpha and ∣B∣=β|B|=\beta. The redundancy factor is Ωα,β(∣V∣)\Omega_{\alpha,\beta}(|V|). 2. Multiway-Cut: Consider the minimum cut separating every two vertices of S⊆VS\subseteq V, ranging over all subsets of a given size ∣S∣=k|S|=k. The redundancy factor is Ωk(∣V∣)\Omega_{k}(|V|). 3. Multicut: Consider the minimum cut separating every demand-pair in D⊆V×VD\subseteq V\times V, ranging over collections of ∣D∣=k|D|=k demand pairs. The redundancy factor is Ωk(∣V∣k)\Omega_{k}(|V|^k). This result is a bit surprising, as the redundancy factor is much larger than in the first two problems. A natural application of these bounds is to construct small data structures that stores all relevant cut values, like the Gomory-Hu tree. We initiate this direction by giving some upper and lower bounds.Comment: This version contains additional references to previous work (which have some overlap with our results), see Bibliographic Update 1.

    Degree-3 Treewidth Sparsifiers

    Full text link
    We study treewidth sparsifiers. Informally, given a graph GG of treewidth kk, a treewidth sparsifier HH is a minor of GG, whose treewidth is close to kk, ∣V(H)∣|V(H)| is small, and the maximum vertex degree in HH is bounded. Treewidth sparsifiers of degree 33 are of particular interest, as routing on node-disjoint paths, and computing minors seems easier in sub-cubic graphs than in general graphs. In this paper we describe an algorithm that, given a graph GG of treewidth kk, computes a topological minor HH of GG such that (i) the treewidth of HH is Ω(k/polylog(k))\Omega(k/\text{polylog}(k)); (ii) ∣V(H)∣=O(k4)|V(H)| = O(k^4); and (iii) the maximum vertex degree in HH is 33. The running time of the algorithm is polynomial in ∣V(G)∣|V(G)| and kk. Our result is in contrast to the known fact that unless NP⊆coNP/polyNP \subseteq coNP/{\sf poly}, treewidth does not admit polynomial-size kernels. One of our key technical tools, which is of independent interest, is a construction of a small minor that preserves node-disjoint routability between two pairs of vertex subsets. This is closely related to the open question of computing small good-quality vertex-cut sparsifiers that are also minors of the original graph.Comment: Extended abstract to appear in Proceedings of ACM-SIAM SODA 201

    Quasipolynomial multicut-mimicking networks and kernels for multiway cut problems

    Get PDF

    Improved guarantees for vertex sparsification in planar graphs

    Get PDF
    corecore