Random walks on weighted networks: a survey of local and non-local dynamics


Por: Riascos, A. P., Mateos, Jose L.

Publicada: 18 sep 2021
Resumen:
In this article, we present a survey of different types of random walk models with local and non-local transitions on undirected weighted networks. We present a general approach by defining the dynamics as a discrete-time Markovian process with transition probabilities expressed in terms of a symmetric matrix of weights. In the first part, we describe the matrices of weights that define local random walk dynamics like the normal random walk, biased random walks and preferential navigation, random walks in the context of digital image processing and maximum entropy random walks. In addition, we explore non-local random walks, like Levy flights on networks, fractional transport through the new formalism of fractional graph Laplacians, and applications in the context of human mobility. Explicit relations for the stationary probability distribution, the mean first passage time and global times to characterize random walks are obtained in terms of the elements of the matrix of weights and its respective eigenvalues and eigenvectors. Finally, we apply the results to the analysis of particular local and non-local random walk dynamics, and we discuss their capacity to explore several types of networks. Our results allow us to study and compare the global dynamics of different types of random walk models.

Filiaciones:
Riascos, A. P.:
 Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, Ciudad de México, 01000, Mexico

 Univ Nacl Autonoma Mexico, Inst Fis, Apartado Postal 20-364, Ciudad De Mexico 01000, Mexico

Mateos, Jose L.:
 Instituto de Física, Universidad Nacional Autónoma de México, Apartado Postal 20-364, Ciudad de México, 01000, Mexico

 Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Apartado Postal 04510, Ciudad de México, Mexico

 Univ Nacl Autonoma Mexico, Inst Fis, Apartado Postal 20-364, Ciudad De Mexico 01000, Mexico

 Univ Nacl Autonoma Mexico, Ctr Ciencias Complejidad, Apartado Postal 04510, Ciudad De Mexico, Mexico
ISSN: 20511310





Journal of Complex Networks
Editorial
Oxford University Press, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, Estados Unidos America
Tipo de documento: Review
Volumen: 9 Número: 5
Páginas:
WOS Id: 000755218500004
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