11 research outputs found

    The Iteration Number of the Weisfeiler-Leman Algorithm

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    We prove new upper and lower bounds on the number of iterations the kk-dimensional Weisfeiler-Leman algorithm (kk-WL) requires until stabilization. For k≄3k \geq 3, we show that kk-WL stabilizes after at most O(knk−1log⁥n)O(kn^{k-1}\log n) iterations (where nn denotes the number of vertices of the input structures), obtaining the first improvement over the trivial upper bound of nk−1n^{k}-1 and extending a previous upper bound of O(nlog⁥n)O(n \log n) for k=2k=2 [Lichter et al., LICS 2019]. We complement our upper bounds by constructing kk-ary relational structures on which kk-WL requires at least nΩ(k)n^{\Omega(k)} iterations to stabilize. This improves over a previous lower bound of nΩ(k/log⁥k)n^{\Omega(k / \log k)} [Berkholz, Nordstr\"{o}m, LICS 2016]. We also investigate tradeoffs between the dimension and the iteration number of WL, and show that dd-WL, where d=⌈3(k+1)2⌉d = \lceil\frac{3(k+1)}{2}\rceil, can simulate the kk-WL algorithm using only O(k2⋅n⌊k/2⌋+1log⁥n)O(k^2 \cdot n^{\lfloor k/2\rfloor + 1} \log n) many iterations, but still requires at least nΩ(k)n^{\Omega(k)} iterations for any dd (that is sufficiently smaller than nn). The number of iterations required by kk-WL to distinguish two structures corresponds to the quantifier rank of a sentence distinguishing them in the (k+1)(k + 1)-variable fragment Ck+1C_{k+1} of first-order logic with counting quantifiers. Hence, our results also imply new upper and lower bounds on the quantifier rank required in the logic Ck+1C_{k+1}, as well as tradeoffs between variable number and quantifier rank.Comment: 30 pages, 1 figure, full version of a paper accepted at LICS 2023; second version improves the presentation of the result

    The Weisfeiler-Leman Dimension of Planar Graphs is at most 3

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    We prove that the Weisfeiler-Leman (WL) dimension of the class of all finite planar graphs is at most 3. In particular, every finite planar graph is definable in first-order logic with counting using at most 4 variables. The previously best known upper bounds for the dimension and number of variables were 14 and 15, respectively. First we show that, for dimension 3 and higher, the WL-algorithm correctly tests isomorphism of graphs in a minor-closed class whenever it determines the orbits of the automorphism group of any arc-colored 3-connected graph belonging to this class. Then we prove that, apart from several exceptional graphs (which have WL-dimension at most 2), the individualization of two correctly chosen vertices of a colored 3-connected planar graph followed by the 1-dimensional WL-algorithm produces the discrete vertex partition. This implies that the 3-dimensional WL-algorithm determines the orbits of a colored 3-connected planar graph. As a byproduct of the proof, we get a classification of the 3-connected planar graphs with fixing number 3.Comment: 34 pages, 3 figures, extended version of LICS 2017 pape

    The Iteration Number of Colour Refinement

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    The Colour Refinement procedure and its generalisation to higher dimensions, the Weisfeiler-Leman algorithm, are central subroutines in approaches to the graph isomorphism problem. In an iterative fashion, Colour Refinement computes a colouring of the vertices of its input graph. A trivial upper bound on the iteration number of Colour Refinement on graphs of order n is n-1. We show that this bound is tight. More precisely, we prove via explicit constructions that there are infinitely many graphs G on which Colour Refinement takes |G|-1 iterations to stabilise. Modifying the infinite families that we present, we show that for every natural number n ? 10, there are graphs on n vertices on which Colour Refinement requires at least n-2 iterations to reach stabilisation

    Cutting Planes Width and the Complexity of Graph Isomorphism Refutations

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    The width complexity measure plays a central role in Resolution and other propositional proof systems like Polynomial Calculus (under the name of degree). The study of width lower bounds is the most extended method for proving size lower bounds, and it is known that for these systems, proofs with small width also imply the existence of proofs with small size. Not much has been studied, however, about the width parameter in the Cutting Planes (CP) proof system, a measure that was introduced by Dantchev and Martin in 2011 under the name of CP cutwidth. In this paper, we study the width complexity of CP refutations of graph isomorphism formulas. For a pair of non-isomorphic graphs G and H, we show a direct connection between the Weisfeiler-Leman differentiation number WL(G, H) of the graphs and the width of a CP refutation for the corresponding isomorphism formula Iso(G, H). In particular, we show that if WL(G, H) ? k, then there is a CP refutation of Iso(G, H) with width k, and if WL(G, H) > k, then there are no CP refutations of Iso(G, H) with width k-2. Similar results are known for other proof systems, like Resolution, Sherali-Adams, or Polynomial Calculus. We also obtain polynomial-size CP refutations from our width bound for isomorphism formulas for graphs with constant WL-dimension

    From Quantifier Depth to Quantifier Number: Separating Structures with k Variables

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    Given two nn-element structures, A\mathcal{A} and B\mathcal{B}, which can be distinguished by a sentence of kk-variable first-order logic (Lk\mathcal{L}^k), what is the minimum f(n)f(n) such that there is guaranteed to be a sentence ϕ∈Lk\phi \in \mathcal{L}^k with at most f(n)f(n) quantifiers, such that A⊚ϕ\mathcal{A} \models \phi but B⊚̞ϕ\mathcal{B} \not \models \phi? We present various results related to this question obtained by using the recently introduced QVT games. In particular, we show that when we limit the number of variables, there can be an exponential gap between the quantifier depth and the quantifier number needed to separate two structures. Through the lens of this question, we will highlight some difficulties that arise in analysing the QVT game and some techniques which can help to overcome them. As a consequence, we show that Lk+1\mathcal{L}^{k+1} is exponentially more succinct than Lk\mathcal{L}^{k}. We also show, in the setting of the existential-positive fragment, how to lift quantifier depth lower bounds to quantifier number lower bounds. This leads to almost tight bounds.Comment: 53 pages, 8 figures; added new result on the relative succinctness of finite variable logi

    36th International Symposium on Theoretical Aspects of Computer Science: STACS 2019, March 13-16, 2019, Berlin, Germany

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    Lifting with Simple Gadgets and Applications to Circuit and Proof Complexity

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    We significantly strengthen and generalize the theorem lifting Nullstellensatz degree to monotone span program size by Pitassi and Robere (2018) so that it works for any gadget with high enough rank, in particular, for useful gadgets such as equality and greater-than. We apply our generalized theorem to solve two open problems: * We present the first result that demonstrates a separation in proof power for cutting planes with unbounded versus polynomially bounded coefficients. Specifically, we exhibit CNF formulas that can be refuted in quadratic length and constant line space in cutting planes with unbounded coefficients, but for which there are no refutations in subexponential length and subpolynomial line space if coefficients are restricted to be of polynomial magnitude. * We give the first explicit separation between monotone Boolean formulas and monotone real formulas. Specifically, we give an explicit family of functions that can be computed with monotone real formulas of nearly linear size but require monotone Boolean formulas of exponential size. Previously only a non-explicit separation was known. An important technical ingredient, which may be of independent interest, is that we show that the Nullstellensatz degree of refuting the pebbling formula over a DAG G over any field coincides exactly with the reversible pebbling price of G. In particular, this implies that the standard decision tree complexity and the parity decision tree complexity of the corresponding falsified clause search problem are equal

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum
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