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Canonical labelling of sparse random graphs

Oleg Verbitsky, Maksim Zhukovskii

TL;DR

The algorithm combines the standard color refinement routine with simple post-processing based on the classical linear-time tree canonization to complete the description of the automorphism group of the 2-core of G(n,p).

Abstract

We show that if $p=O(1/n)$, then the Erdős-Rényi random graph $G(n,p)$ with high probability admits a canonical labeling computable in time $O(n\log n)$. Combined with the previous results on the canonization of random graphs, this implies that $G(n,p)$ with high probability admits a polynomial-time canonical labeling whatever the edge probability function $p$. Our algorithm combines the standard color refinement routine with simple post-processing based on the classical linear-time tree canonization. Noteworthy, our analysis of how well color refinement performs in this setting allows us to complete the description of the automorphism group of the 2-core of $G(n,p)$.

Canonical labelling of sparse random graphs

TL;DR

The algorithm combines the standard color refinement routine with simple post-processing based on the classical linear-time tree canonization to complete the description of the automorphism group of the 2-core of G(n,p).

Abstract

We show that if , then the Erdős-Rényi random graph with high probability admits a canonical labeling computable in time . Combined with the previous results on the canonization of random graphs, this implies that with high probability admits a polynomial-time canonical labeling whatever the edge probability function . Our algorithm combines the standard color refinement routine with simple post-processing based on the classical linear-time tree canonization. Noteworthy, our analysis of how well color refinement performs in this setting allows us to complete the description of the automorphism group of the 2-core of .
Paper Structure (30 sections, 17 theorems, 43 equations)