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Killing a Vortex

Online AM: 14 May 2024 Publication History
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  • Abstract

    The Graph Minors Structure Theorem of Robertson and Seymour asserts that, for every graph H, every H-minor-free graph can be obtained by clique-sums of “almost embeddable” graphs. Here a graph is “almost embeddable” if it can be obtained from a graph of bounded Euler-genus by pasting graphs of bounded pathwidth in an “orderly fashion” into a bounded number of faces, called the vortices, and then adding a bounded number of additional vertices, called apices, with arbitrary neighborhoods. Our main result is a full classification of all graphs H for which the use of vortices in the theorem above can be avoided. To this end we identify a (parametric) graph \( \mathscr{S}_t \) and prove that all \( \mathscr{S}_t \)-minor-free graphs can be obtained by clique-sums of graphs embeddable in a surface of bounded Euler-genus after deleting a bounded number of vertices. We show that this result is tight in the sense that the appearance of vortices cannot be avoided for H-minor-free graphs, whenever H is not a minor of \( \mathscr{S}_t \) for some \(t\in \mathbb {N}. \) Using our new structure theorem, we design an algorithm that, given an \( \mathscr{S}_t \)-minor-free graph G, computes the generating function of all perfect matchings of G in polynomial time. Our results, combined with known complexity results, imply a complete characterization of minor-closed graph classes where the number of perfect matchings is polynomially computable: They are exactly those graph classes that do not contain every \( \mathscr{S}_t \) as a minor. This provides a sharp complexity dichotomy for the problem of counting perfect matchings in minor-closed classes.

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    cover image Journal of the ACM
    Journal of the ACM Just Accepted
    ISSN:0004-5411
    EISSN:1557-735X
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    Publication History

    Online AM: 14 May 2024
    Accepted: 02 May 2024
    Revised: 04 February 2024
    Received: 26 July 2022

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    Author Tags

    1. Perfect Matchings
    2. Permanent
    3. Pfaffian Orientations
    4. Graph Minors
    5. Counting Algorithms
    6. Graph Parameters

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