Literature DB >> 26765034

Breaking of Ensemble Equivalence in Networks.

Tiziano Squartini1,2, Joey de Mol1,3, Frank den Hollander3, Diego Garlaschelli.   

Abstract

It is generally believed that, in the thermodynamic limit, the microcanonical description as a function of energy coincides with the canonical description as a function of temperature. However, various examples of systems for which the microcanonical and canonical ensembles are not equivalent have been identified. A complete theory of this intriguing phenomenon is still missing. Here we show that ensemble nonequivalence can manifest itself also in random graphs with topological constraints. We find that, while graphs with a given number of links are ensemble equivalent, graphs with a given degree sequence are not. This result holds irrespective of whether the energy is nonadditive (as in unipartite graphs) or additive (as in bipartite graphs). In contrast with previous expectations, our results show that (1) physically, nonequivalence can be induced by an extensive number of local constraints, and not necessarily by long-range interactions or nonadditivity, (2) mathematically, nonequivalence is determined by a different large-deviation behavior of microcanonical and canonical probabilities for a single microstate, and not necessarily for almost all microstates. The latter criterion, which is entirely local, is not restricted to networks and holds in general.

Year:  2015        PMID: 26765034     DOI: 10.1103/PhysRevLett.115.268701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  4 in total

1.  Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data.

Authors:  Alexander P Kartun-Giles; Dmitri Krioukov; James P Gleeson; Yamir Moreno; Ginestra Bianconi
Journal:  Entropy (Basel)       Date:  2018-04-07       Impact factor: 2.524

2.  Thermodynamics of structure-forming systems.

Authors:  Jan Korbel; Simon David Lindner; Rudolf Hanel; Stefan Thurner
Journal:  Nat Commun       Date:  2021-02-18       Impact factor: 14.919

3.  Comparing alternatives to the fixed degree sequence model for extracting the backbone of bipartite projections.

Authors:  Zachary P Neal; Rachel Domagalski; Bruce Sagan
Journal:  Sci Rep       Date:  2021-12-14       Impact factor: 4.379

4.  Estimating degree-degree correlation and network cores from the connectivity of high-degree nodes in complex networks.

Authors:  R J Mondragón
Journal:  Sci Rep       Date:  2020-03-27       Impact factor: 4.379

  4 in total

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