517 research outputs found

    Even Delta-Matroids and the Complexity of Planar Boolean CSPs

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    The main result of this paper is a generalization of the classical blossom algorithm for finding perfect matchings. Our algorithm can efficiently solve Boolean CSPs where each variable appears in exactly two constraints (we call it edge CSP) and all constraints are even Δ\Delta-matroid relations (represented by lists of tuples). As a consequence of this, we settle the complexity classification of planar Boolean CSPs started by Dvorak and Kupec. Using a reduction to even Δ\Delta-matroids, we then extend the tractability result to larger classes of Δ\Delta-matroids that we call efficiently coverable. It properly includes classes that were known to be tractable before, namely co-independent, compact, local, linear and binary, with the following caveat: we represent Δ\Delta-matroids by lists of tuples, while the last two use a representation by matrices. Since an n×nn\times n matrix can represent exponentially many tuples, our tractability result is not strictly stronger than the known algorithm for linear and binary Δ\Delta-matroids.Comment: 33 pages, 9 figure

    Matching

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    A Hall-type theorem with algorithmic consequences in planar graphs

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    Given a graph G=(V,E)G=(V,E), for a vertex set S⊆VS\subseteq V, let N(S)N(S) denote the set of vertices in VV that have a neighbor in SS. Extending the concept of binding number of graphs by Woodall~(1973), for a vertex set X⊆VX \subseteq V, we define the binding number of XX, denoted by \bind(X), as the maximum number bb such that for every S⊆XS \subseteq X where N(S)≠V(G)N(S)\neq V(G) it holds that ∣N(S)∣≥b∣S∣|N(S)|\ge b {|S|}. Given this definition, we prove that if a graph V(G)V(G) contains a subset XX with \bind(X)= 1/k where kk is an integer, then GG possesses a matching of size at least ∣X∣/(k+1)|X|/(k+1). Using this statement, we derive tight bounds for the estimators of the matching size in planar graphs. These estimators are previously used in designing sublinear space algorithms for approximating the maching size in the data stream model of computation. In particular, we show that the number of locally superior vertices is a 33 factor approximation of the matching size in planar graphs. The previous analysis by Jowhari (2023) proved a 3.53.5 approximation factor. As another application, we show a simple variant of an estimator by Esfandiari \etal (2015) achieves 33 factor approximation of the matching size in planar graphs. Namely, let ss be the number of edges with both endpoints having degree at most 22 and let hh be the number of vertices with degree at least 33. We prove that when the graph is planar, the size of matching is at least (s+h)/3(s+h)/3. This result generalizes a known fact that every planar graph on nn vertices with minimum degree 33 has a matching of size at least n/3n/3.Comment: 9 page

    The many faces of planarity : matching, augmentation, and embedding algorithms for planar graphs

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