Lacon-,灌木-和奇偶分解:表征有界展开类的转导

Jannik Dreier
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引用次数: 0

摘要

有界展开的概念提供了一种健壮的方法来捕获具有有趣算法属性的稀疏图类。最值得注意的是,在一阶逻辑中可定义的所有问题都可以在线性时间内在有界展开图类上得到解决。稀疏图类的一阶解释和转换导致了更一般、更密集的图类,这些图类似乎继承了它们的稀疏对应类的许多好的算法属性。本文通过lacon分解、灌木分解和奇偶分解,证明了可以对具有结构有界展开的类中的图进行编码。这些分解对于将属性从稀疏提升到结构稀疏的图类非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lacon-, Shrub- and Parity-Decompositions: Characterizing Transductions of Bounded Expansion Classes
The concept of bounded expansion provides a robust way to capture sparse graph classes with interesting algorithmic properties. Most notably, every problem definable in first-order logic can be solved in linear time on bounded expansion graph classes. First-order interpretations and transductions of sparse graph classes lead to more general, dense graph classes that seem to inherit many of the nice algorithmic properties of their sparse counterparts. In this paper, we show that one can encode graphs from a class with structurally bounded expansion via lacon-, shrub- and parity-decompositions from a class with bounded expansion. These decompositions are useful for lifting properties from sparse to structurally sparse graph classes.
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