2026-04-14T07:38:46Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1196222025-12-04T20:46:50Zcom_2072_1057col_2072_478822col_2072_478917

00925njm 22002777a 4500 dc Sagarra Pascual, Oleguer Josep author Pérez-Vicente, Conrado, 1962- author Díaz Guilera, Albert author 2018-02-06T14:10:41Z 2018-02-06T14:10:41Z 2015-11-30 2018-02-06T14:10:41Z Complex network null models based on entropy maximization are becoming a powerful tool to characterize and analyze data from real systems. However, it is not easy to extract good and unbiased information from these models: A proper understanding of the nature of the underlying events represented in them is crucial. In this paper we emphasize this fact stressing how an accurate counting of configurations compatible with given constraints is fundamental to build good null models for the case of networks with integer-valued adjacency matrices constructed from an aggregation of one or multiple layers. We show how different assumptions about the elements from which the networks are built give rise to distinctively different statistics, even when considering the same observables to match those of real data. We illustrate our findings by applying the formalism to three data sets using an open-source software package accompanying the present work and demonstrate how such differences are clearly seen when measuring network observables. Xarxes complexes (Física) Entropia Complex networks (Physics) Entropy Role of adjacency-matrix degeneracy in maximum-entropy-weighted network models