Unified framework for hybrid percolation transitions based on microscopic dynamics
Hoyun Choi, Y.S. Cho, Raissa D'Souza, J\'anos Kert\'esz and, B. Kahng

TL;DR
This paper develops a unified microscopic framework to understand hybrid percolation transitions, revealing a three-step process involving cluster accumulation, rapid merging, and Erdős-Rényi dynamics, supported by extensive simulations.
Contribution
It introduces a universal microscopic mechanism for hybrid percolation transitions based on cluster merging models, unifying previous understanding of different transition types.
Findings
Identified a three-step process in HPT dynamics.
Derived scaling relations between critical exponents.
Validated the theory with extensive finite-size scaling simulations.
Abstract
A hybrid percolation transition (HPT) exhibits both discontinuity of the order parameter and critical behavior at the transition point. Such dynamic transitions can occur in two ways: by cluster pruning with suppression of loop formation of cut links or by cluster merging with suppression of the creation of large clusters. While the microscopic mechanism of the former is understood in detail, a similar framework is missing for the latter. By studying two distinct cluster merging models, we uncover the universal mechanism of the features of HPT-s at a microscopic level. We find that these features occur in three steps: (i) medium-sized clusters accumulate due to the suppression rule hindering the growth of large clusters, (ii) those medium size clusters eventually merge and a giant cluster increases rapidly, and (iii) the suppression effect becomes obsolete and the kinetics is governed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and statistical mechanics · Complex Network Analysis Techniques · Theoretical and Computational Physics
