In this talk I will present a novel method for finding optimal paths and optimal weight distributions. It is based on the analysis of large deviations of random walks on networks, and it leads to a generalization of the standard definitions to encompass paths and weight distributions tailored to a given statistical characterization of time-extensive observables in the presence of constraints. All dynamical aspects of the problem (the random walk transition matrix, the observables and the statistical ensemble) are chosen so as to best reveal the underlying structural features of interest. After a discussion of the main aspects of the theoretical framework, some examples involving random graphs and spatial networks will be presented. Referencia: Phys. Rev. E 103, 022319 (2021).
Ponente: Ricardo Gutiérrez. Complex Systems Interdisciplinary Group, Department of Mathematics, Universidad Carlos III de Madrid.
Fecha y hora: viernes, 12 de marzo de 2021 a las 12:00.
Lugar: Online en https://meet.google.com/bjy-gcmc-ioo.