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

  • Datos identificativos

    Identificador: imarina:6162120
    Autores:
    Arola-Fernandez, LluisMosquera-Donate, GuillemSteinegger, BenjaminArenas, Alex
    Resumen:
    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.
  • Otros:

    Autor según el artículo: Arola-Fernandez, Lluis; Mosquera-Donate, Guillem; Steinegger, Benjamin; Arenas, Alex
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Arenas Moreno, Alejandro / Arola Fernández, Lluís / Steinegger, Benjamin Franz Josef
    Palabras clave: Hashtag Etiqueta «#» @uroweb @residentesaeu @infoAeu
    Resumen: 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.
    Áreas temáticas: 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
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1054-1500
    Direcció de correo del autor: benjamin.steinegger@estudiants.urv.cat lluis.arola@estudiants.urv.cat lluis.arola@estudiants.urv.cat alexandre.arenas@urv.cat
    Identificador del autor: 0000-0002-0723-1536 0000-0003-0937-0334
    Fecha de alta del registro: 2024-09-28
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://aip.scitation.org/doi/10.1063/1.5129630
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Chaos. 30 (2): 023129-
    Referencia 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 del artículo: 10.1063/1.5129630
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2020
    Tipo de publicación: Journal Publications
  • Palabras clave:

    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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