Droplet finite-size scaling of the contact process on scale-free networks revisited

D. S. M. Alencar, T. F. A. Alves, R. S. Ferreira, G. A. Alves, A. Macedo-Filho and F. W. S. Lima
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D. S. M. Alencar: Departamento de Física, Universidade Federal do Piauí, 57072-970 Teresina, Piauí, Brazil
T. F. A. Alves: Departamento de Física, Universidade Federal do Piauí, 57072-970 Teresina, Piauí, Brazil
R. S. Ferreira: Departamento de Ciências Exatas e Aplicadas, Universidade Federal de Ouro Preto, 35931-008 João Monlevade, MG, Brazil
G. A. Alves: Departamento de Física, Universidade Estadual do Piauí, 64002-150 Teresina, PI, Brazil
A. Macedo-Filho: Departamento de Física, Universidade Estadual do Piauí, 64002-150 Teresina, PI, Brazil
F. W. S. Lima: Departamento de Física, Universidade Federal do Piauí, 57072-970 Teresina, PI, Brazil

International Journal of Modern Physics C (IJMPC), 2023, vol. 34, issue 08, 1-18

Abstract: We present an alternative finite-size scaling (FSS) of the contact process on scale-free networks compatible with mean-field scaling and test it with extensive Monte Carlo simulations. In our FSS theory, the dependence on the system size enters the external field, which represents spontaneous contamination in the context of an epidemic model. In addition, dependence on the finite size in the scale-free networks also enters the network cutoff. We show that our theory reproduces the results of other mean-field theories on finite lattices already reported in the literature. To simulate the dynamics, we impose quasi-stationary states by reactivation. We insert spontaneously infected individuals, equivalent to a droplet perturbation to the system scaling as N−1. The system presents an absorbing phase transition where the critical behavior obeys the mean-field exponents, as we show theoretically and by simulations. However, the quasi-stationary state gives finite-size logarithmic corrections, predicted by our FSS theory, and reproduces equivalent results in the literature in the thermodynamic limit. We also report the critical threshold estimates of basic reproduction number R0=λc of the model as a linear function of the network connectivity inverse 1∕z, and the extrapolation of the critical threshold function for z→∞ yields the basic reproduction number R0=1 of the complete graph, as expected. Decreasing the network connectivity increases the critical R0 for this model.

Keywords: Barabási–Albert network; epidemic processes; directed percolation; continuous phase transition; logarithmic corrections; external field (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S012918312350105X

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