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arXiv 1605.03480cs.LOcs.CCmath.CO
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一阶逻辑中图区分量词深度的上界

Upper Bounds on the Quantifier Depth for Graph Differentiation in First-Order Logic

Sandra Kiefer, Pascal Schweitzer

AI总结:

该论文证明二维 Weisfeiler-Leman 算法在 n 顶点图上稳定所需迭代次数为 O(n^2/log(n)),改进了平凡上界,并由此导出 C3 与 L3 逻辑中量词深度的对应上界。

摘要:

我们证明,在具有 n 个顶点的图上,二维 Weisfeiler-Leman 算法达到稳定所需的迭代次数至多为 O(n^2/log(n))。这特别表明,先前最佳的平凡上界 O(n^2) 在渐近意义上并不紧。在逻辑设定中,这转化为如下陈述:如果两个大小为 n 的图可以通过带计数的一阶逻辑公式(即 C3 逻辑)区分,那么它们也可以通过一个量词深度至多为 O(n^2/log(n)) 的 C3 公式区分。为了证明该结果,我们定义了一个双人博弈,它使我们能够解耦算法多次迭代中同时发生的过程之间的因果依赖关系。这允许我们分别处理大的颜色类和小的颜色类。作为证明的一部分,我们表明对于颜色类大小有界的图,达到稳定所需的迭代次数至多与顶点数成线性关系。这也产生了带计数的一阶逻辑中的相应陈述。类似的结果也可以在没有计数量词的相应逻辑(即 L3 逻辑)中获得。

英文摘要:

We show that on graphs with n vertices, the 2-dimensional Weisfeiler-Leman algorithm requires at most O(n^2/log(n)) iterations to reach stabilization. This in particular shows that the previously best, trivial upper bound of O(n^2) is asymptotically not tight. In the logic setting, this translates to the statement that if two graphs of size n can be distinguished by a formula in first-order logic with counting with 3 variables (i.e., in C3), then they can also be distinguished by a C3-formula that has quantifier depth at most O(n^2/log(n)). To prove the result we define a game between two players that enables us to decouple the causal dependencies between the processes happening simultaneously over several iterations of the algorithm. This allows us to treat large color classes and small color classes separately. As part of our proof we show that for graphs with bounded color class size, the number of iterations until stabilization is at most linear in the number of vertices. This also yields a corresponding statement in first-order logic with counting. Similar results can be obtained for the respective logic without counting quantifiers, i.e., for the logic L3.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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