稀疏图转导的树状分解

Jannik Dreier, Jakub Gajarsk'y, Sandra Kiefer, Michal Pilipczuk, Szymon Toruńczyk
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引用次数: 8

摘要

我们给出了可以用一阶逻辑从稀疏图类——更准确地说,从有界展开的类和无处密集的类——转换成一类图的新的分解定理。在这两种情况下,分解都采用有界深度的单色根树的形式,此外,树中不相关的节点之间可能存在链接。约束是由树和链接形成的结构必须是稀疏的。利用无处密集类的变换分解定理,我们证明了无处密集类允许有大小的低灌木深度覆盖,其中n为顶点数,ε > 0为任意固定实数。这解决了Gajarský等人(ACM TOCL ' 20)和Briański等人(SIDMA ' 21)提出的一个开放问题。
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Treelike Decompositions for Transductions of Sparse Graphs
We give new decomposition theorems for classes of graphs that can be transduced in first-order logic from classes of sparse graphs — more precisely, from classes of bounded expansion and nowhere dense classes. In both cases, the decomposition takes the form of a single colored rooted tree of bounded depth where, in addition, there can be links between nodes that are not related in the tree. The constraint is that the structure formed by the tree and the links has to be sparse. Using the decomposition theorem for transductions of nowhere dense classes, we show that they admit low-shrubdepth covers of size , where n is the vertex count and ε > 0 is any fixed real. This solves an open problem posed by Gajarský et al. (ACM TOCL ’20) and also by Briański et al. (SIDMA ’21).
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