Berit Grußien - Capturing Polynomial Time using Modular Decomposition

lmcs:4416 - Logical Methods in Computer Science, March 5, 2019, Volume 15, Issue 1 - https://doi.org/10.23638/LMCS-15(1:24)2019
Capturing Polynomial Time using Modular DecompositionArticle

Authors: Berit Grußien

    The question of whether there is a logic that captures polynomial time is one of the main open problems in descriptive complexity theory and database theory. In 2010 Grohe showed that fixed point logic with counting captures polynomial time on all classes of graphs with excluded minors. We now consider classes of graphs with excluded induced subgraphs. For such graph classes, an effective graph decomposition, called modular decomposition, was introduced by Gallai in 1976. The graphs that are non-decomposable with respect to modular decomposition are called prime. We present a tool, the Modular Decomposition Theorem, that reduces (definable) canonization of a graph class C to (definable) canonization of the class of prime graphs of C that are colored with binary relations on a linearly ordered set. By an application of the Modular Decomposition Theorem, we show that fixed point logic with counting captures polynomial time on the class of permutation graphs. Within the proof of the Modular Decomposition Theorem, we show that the modular decomposition of a graph is definable in symmetric transitive closure logic with counting. We obtain that the modular decomposition tree is computable in logarithmic space. It follows that cograph recognition and cograph canonization is computable in logarithmic space.


    Volume: Volume 15, Issue 1
    Published on: March 5, 2019
    Accepted on: February 20, 2019
    Submitted on: March 30, 2018
    Keywords: Computer Science - Computational Complexity,Computer Science - Logic in Computer Science

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