Literature DB >> 26382462

Complex quantum network geometries: Evolution and phase transitions.

Ginestra Bianconi1, Christoph Rahmede2, Zhihao Wu3.   

Abstract

Networks are topological and geometric structures used to describe systems as different as the Internet, the brain, or the quantum structure of space-time. Here we define complex quantum network geometries, describing the underlying structure of growing simplicial 2-complexes, i.e., simplicial complexes formed by triangles. These networks are geometric networks with energies of the links that grow according to a nonequilibrium dynamics. The evolution in time of the geometric networks is a classical evolution describing a given path of a path integral defining the evolution of quantum network states. The quantum network states are characterized by quantum occupation numbers that can be mapped, respectively, to the nodes, links, and triangles incident to each link of the network. We call the geometric networks describing the evolution of quantum network states the quantum geometric networks. The quantum geometric networks have many properties common to complex networks, including small-world property, high clustering coefficient, high modularity, and scale-free degree distribution. Moreover, they can be distinguished between the Fermi-Dirac network and the Bose-Einstein network obeying, respectively, the Fermi-Dirac and Bose-Einstein statistics. We show that these networks can undergo structural phase transitions where the geometrical properties of the networks change drastically. Finally, we comment on the relation between quantum complex network geometries, spin networks, and triangulations.

Year:  2015        PMID: 26382462     DOI: 10.1103/PhysRevE.92.022815

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  7 in total

1.  Complex Quantum Network Manifolds in Dimension d > 2 are Scale-Free.

Authors:  Ginestra Bianconi; Christoph Rahmede
Journal:  Sci Rep       Date:  2015-09-10       Impact factor: 4.379

2.  Navigability of Random Geometric Graphs in the Universe and Other Spacetimes.

Authors:  William Cunningham; Konstantin Zuev; Dmitri Krioukov
Journal:  Sci Rep       Date:  2017-08-18       Impact factor: 4.379

3.  Magnetisation Processes in Geometrically Frustrated Spin Networks with Self-Assembled Cliques.

Authors:  Bosiljka Tadić; Miroslav Andjelković; Milovan Šuvakov; Geoff J Rodgers
Journal:  Entropy (Basel)       Date:  2020-03-14       Impact factor: 2.524

4.  The Evolution of Hyperedge Cardinalities and Bose-Einstein Condensation in Hypernetworks.

Authors:  Jin-Li Guo; Qi Suo; Ai-Zhong Shen; Jeffrey Forrest
Journal:  Sci Rep       Date:  2016-09-27       Impact factor: 4.379

5.  Hidden geometries in networks arising from cooperative self-assembly.

Authors:  Milovan Šuvakov; Miroslav Andjelković; Bosiljka Tadić
Journal:  Sci Rep       Date:  2018-01-31       Impact factor: 4.379

6.  Geometric Deep Lean Learning: Deep Learning in Industry 4.0 Cyber-Physical Complex Networks.

Authors:  Javier Villalba-Díez; Martin Molina; Joaquín Ordieres-Meré; Shengjing Sun; Daniel Schmidt; Wanja Wellbrock
Journal:  Sensors (Basel)       Date:  2020-01-30       Impact factor: 3.576

7.  The topology of higher-order complexes associated with brain hubs in human connectomes.

Authors:  Miroslav Andjelković; Bosiljka Tadić; Roderick Melnik
Journal:  Sci Rep       Date:  2020-10-14       Impact factor: 4.379

  7 in total

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