Let G(N,1/N t_N) be the Erdős–Rényi graph with connection probability 1/N t_N as N → ∞ for a fixed t ∈ (0, ∞). We derive a large-deviations principle for the empirical measure of the sizes of all the connected components of G(N,1/N t_N), registered according to microscopic sizes (i.e., of finite order), macroscopic ones (i.e., of order N), and mesoscopic ones (everything in between). The rate function explicitly describes the microscopic and macroscopic components and the fraction of vertices in components of mesoscopic sizes. Moreover, it clearly captures the well known phase transition at t = 1 as part of a comprehensive picture. The proofs rely on elementary combinatorics and on known estimates and asymptotics for the probability that subgraphs are connected. We also draw conclusions for the strongly related model of the multiplicative coalescent, the Marcus–Lushnikov coagulation model with monodisperse initial condition, and its gelation phase transition.
A large‐deviations principle for all the cluster sizes of a sparse Erdős–Rényi graph / Andreis, Luisa; König, Wolfgang; Patterson, Robert I. A.. - In: RANDOM STRUCTURES & ALGORITHMS. - ISSN 1042-9832. - ELETTRONICO. - 59:(2021), pp. 522-553. [10.1002/rsa.21007]
A large‐deviations principle for all the cluster sizes of a sparse Erdős–Rényi graph
Andreis, Luisa
;
2021
Abstract
Let G(N,1/N t_N) be the Erdős–Rényi graph with connection probability 1/N t_N as N → ∞ for a fixed t ∈ (0, ∞). We derive a large-deviations principle for the empirical measure of the sizes of all the connected components of G(N,1/N t_N), registered according to microscopic sizes (i.e., of finite order), macroscopic ones (i.e., of order N), and mesoscopic ones (everything in between). The rate function explicitly describes the microscopic and macroscopic components and the fraction of vertices in components of mesoscopic sizes. Moreover, it clearly captures the well known phase transition at t = 1 as part of a comprehensive picture. The proofs rely on elementary combinatorics and on known estimates and asymptotics for the probability that subgraphs are connected. We also draw conclusions for the strongly related model of the multiplicative coalescent, the Marcus–Lushnikov coagulation model with monodisperse initial condition, and its gelation phase transition.File | Dimensione | Formato | |
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