Literature DB >> 26066129

Lifespan method as a tool to study criticality in absorbing-state phase transitions.

Angélica S Mata1,2, Marian Boguñá3, Claudio Castellano4,5, Romualdo Pastor-Satorras2.   

Abstract

In a recent work, a new numerical method (the lifespan method) has been introduced to study the critical properties of epidemic processes on complex networks [M. Boguñá, C. Castellano, and R. Pastor-Satorras, Phys. Rev. Lett. 111, 068701 (2013)]. Here, we present a detailed analysis of the viability of this method for the study of the critical properties of generic absorbing-state phase transitions in lattices. Focusing on the well-understood case of the contact process, we develop a finite-size scaling theory to measure the critical point and its associated critical exponents. We show the validity of the method by studying numerically the contact process on a one-dimensional lattice and comparing the findings of the lifespan method with the standard quasistationary method. We find that the lifespan method gives results that are perfectly compatible with those of quasistationary simulations and with analytical results. Our observations confirm that the lifespan method is a fully legitimate tool for the study of the critical properties of absorbing phase transitions in regular lattices.

Year:  2015        PMID: 26066129     DOI: 10.1103/PhysRevE.91.052117

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  From subcritical behavior to a correlation-induced transition in rumor models.

Authors:  Guilherme Ferraz de Arruda; Lucas G S Jeub; Angélica S Mata; Francisco A Rodrigues; Yamir Moreno
Journal:  Nat Commun       Date:  2022-06-01       Impact factor: 17.694

2.  Effect of risk perception on epidemic spreading in temporal networks.

Authors:  Antoine Moinet; Romualdo Pastor-Satorras; Alain Barrat
Journal:  Phys Rev E       Date:  2018-01       Impact factor: 2.529

3.  Predicting the epidemic threshold of the susceptible-infected-recovered model.

Authors:  Wei Wang; Quan-Hui Liu; Lin-Feng Zhong; Ming Tang; Hui Gao; H Eugene Stanley
Journal:  Sci Rep       Date:  2016-04-19       Impact factor: 4.379

  3 in total

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