Color Refinement for Relational Structures
Benjamin Scheidt, Nicole Schweikardt

TL;DR
This paper generalizes the classical Color Refinement algorithm from graphs to arbitrary relational structures, providing logical and combinatorial characterizations of its distinguishing power and an efficient implementation.
Contribution
It introduces Relational Color Refinement (RCR), extending the method to relational structures with equivalent logical and combinatorial characterizations and a near-linear runtime.
Findings
RCR distinguishes structures by homomorphisms from acyclic structures.
RCR characterizes structures definable by guarded fragment logic with counting.
RCR runs in O(N log N) time for fixed signatures.
Abstract
Color Refinement, also known as Naive Vertex Classification, is a classical method to distinguish graphs by iteratively computing a coloring of their vertices. While it is mainly used as an imperfect way to test for isomorphism, the algorithm permeated many other, seemingly unrelated, areas of computer science. The method is algorithmically simple, and it has a well-understood distinguishing power: It is logically characterized by Cai, F\"urer and Immerman (1992), who showed that it distinguishes precisely those graphs that can be distinguished by a sentence of first-order logic with counting quantifiers and only two variables. A combinatorial characterization is given by Dvo\v{r}\'ak (2010), who shows that it distinguishes precisely those graphs that can be distinguished by the number of homomorphisms from some tree. In this paper, we introduce Relational Color Refinement (RCR, for…
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