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Uncertainty propagation in complex networks: From noisy links to critical properties

  • Dades identificatives

    Identificador: imarina:6162120
    Autors:
    Arola-Fernandez, LluisMosquera-Donate, GuillemSteinegger, BenjaminArenas, Alex
    Resum:
    Many complex networks are built up from empirical data prone to experimental error. Thus, the determination of the specific weights of the links is a noisy measure. Noise propagates to those macroscopic variables researchers are interested in, such as the critical threshold for synchronization of coupled oscillators or for the spreading of a disease. Here, we apply error propagation to estimate the macroscopic uncertainty in the critical threshold for some dynamical processes in networks with noisy links. We obtain closed form expressions for the mean and standard deviation of the critical threshold depending on the properties of the noise and the moments of the degree distribution of the network. The analysis provides confidence intervals for critical predictions when dealing with uncertain measurements or intrinsic fluctuations in empirical networked systems. Furthermore, our results unveil a nonmonotonous behavior of the uncertainty of the critical threshold that depends on the specific network structure.
  • Altres:

    Autor segons l'article: Arola-Fernandez, Lluis; Mosquera-Donate, Guillem; Steinegger, Benjamin; Arenas, Alex
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Arenas Moreno, Alejandro / Arola Fernández, Lluís / Steinegger, Benjamin Franz Josef
    Paraules clau: Hashtag Etiqueta «#» @uroweb @residentesaeu @infoAeu
    Resum: Many complex networks are built up from empirical data prone to experimental error. Thus, the determination of the specific weights of the links is a noisy measure. Noise propagates to those macroscopic variables researchers are interested in, such as the critical threshold for synchronization of coupled oscillators or for the spreading of a disease. Here, we apply error propagation to estimate the macroscopic uncertainty in the critical threshold for some dynamical processes in networks with noisy links. We obtain closed form expressions for the mean and standard deviation of the critical threshold depending on the properties of the noise and the moments of the degree distribution of the network. The analysis provides confidence intervals for critical predictions when dealing with uncertain measurements or intrinsic fluctuations in empirical networked systems. Furthermore, our results unveil a nonmonotonous behavior of the uncertainty of the critical threshold that depends on the specific network structure.
    Àrees temàtiques: Statistical and nonlinear physics Physics, mathematical Physics and astronomy (miscellaneous) Physics and astronomy (all) Medicine (miscellaneous) Medicina veterinaria Medicina ii Mathematics, applied Mathematical physics Matemática / probabilidade e estatística Interdisciplinar Geociências General physics and astronomy Engenharias iv Engenharias iii Engenharias ii Engenharias i Ciências ambientais Ciência da computação Astronomia / física Applied mathematics
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1054-1500
    Adreça de correu electrònic de l'autor: benjamin.steinegger@estudiants.urv.cat lluis.arola@estudiants.urv.cat lluis.arola@estudiants.urv.cat alexandre.arenas@urv.cat
    Identificador de l'autor: 0000-0002-0723-1536 0000-0003-0937-0334
    Data d'alta del registre: 2024-09-28
    Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
    Enllaç font original: https://aip.scitation.org/doi/10.1063/1.5129630
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Chaos. 30 (2): 023129-
    Referència de l'ítem segons les normes APA: Arola-Fernandez, Lluis; Mosquera-Donate, Guillem; Steinegger, Benjamin; Arenas, Alex (2020). Uncertainty propagation in complex networks: From noisy links to critical properties. Chaos, 30(2), 023129- . DOI: 10.1063/1.5129630
    DOI de l'article: 10.1063/1.5129630
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2020
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Applied Mathematics,Mathematical Physics,Mathematics, Applied,Medicine (Miscellaneous),Physics and Astronomy (Miscellaneous),Physics, Mathematical,Statistical and Nonlinear Physics
    Statistical and nonlinear physics
    Physics, mathematical
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Medicine (miscellaneous)
    Medicina veterinaria
    Medicina ii
    Mathematics, applied
    Mathematical physics
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General physics and astronomy
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Ciências ambientais
    Ciência da computação
    Astronomia / física
    Applied mathematics
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