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

机译:在一阶逻辑中的图形差异化的量化深度上限

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We show that on graphs with n vertices the 2-dimensional Weisfei-ler-Leman algorithm requires at most O(n2/log(n)) iterations to reach stabilization. This in particular shows that the previously best, trivial upper bound of O(n2) 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 (n2/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.
机译:我们展示在N顶点的图表上,二维Weisfei-Ler-Leman算法最多需要O(n 2 / log(n))迭代以达到稳定。特别是o(n的先前最好的琐碎的上限 2 )渐近地不紧。在逻辑设置中,这转化为语句,如果可以通过第一顺序逻辑中的公式区分,则可以通过与3个变量计数的公式来区分(即,在c中 3 )然后它们也可以通过c区分 3 - 大多数o的量化深度offormula(n 2 /log(n)。证明我们在两个玩家之间定义了一个游戏的结果,使我们能够在算法的几个迭代在几个迭代中同时切换进程之间的因果依赖性。这使我们可以单独处理大型颜色类和小颜色类。作为我们证据的一部分,我们展示了具有有界颜色类大小的图表,迭代的数量在稳定状态下在顶点的数量上是最多线性的。这也在第一顺序逻辑中产生相应的语句,其中可以为各个逻辑获得混合结果,而无需计数量子,即逻辑L.,即逻辑L 3

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