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Potential energy of complex networks: a quantum mechanical perspective
by
Bellantuono, Loredana
, Pascazio, Saverio
, Amoroso, Nicola
, Bellotti, Roberto
, Lombardi, Angela
, Monaco, Alfonso
, Tangaro, Sabina
in
639/766/25
/ 639/766/259
/ 639/766/483
/ 639/766/530/2795
/ 639/766/530/2801
/ Humanities and Social Sciences
/ multidisciplinary
/ Phase transitions
/ Potential energy
/ Science
/ Science (multidisciplinary)
2020
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Potential energy of complex networks: a quantum mechanical perspective
by
Bellantuono, Loredana
, Pascazio, Saverio
, Amoroso, Nicola
, Bellotti, Roberto
, Lombardi, Angela
, Monaco, Alfonso
, Tangaro, Sabina
in
639/766/25
/ 639/766/259
/ 639/766/483
/ 639/766/530/2795
/ 639/766/530/2801
/ Humanities and Social Sciences
/ multidisciplinary
/ Phase transitions
/ Potential energy
/ Science
/ Science (multidisciplinary)
2020
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Do you wish to request the book?
Potential energy of complex networks: a quantum mechanical perspective
by
Bellantuono, Loredana
, Pascazio, Saverio
, Amoroso, Nicola
, Bellotti, Roberto
, Lombardi, Angela
, Monaco, Alfonso
, Tangaro, Sabina
in
639/766/25
/ 639/766/259
/ 639/766/483
/ 639/766/530/2795
/ 639/766/530/2801
/ Humanities and Social Sciences
/ multidisciplinary
/ Phase transitions
/ Potential energy
/ Science
/ Science (multidisciplinary)
2020
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Potential energy of complex networks: a quantum mechanical perspective
Journal Article
Potential energy of complex networks: a quantum mechanical perspective
2020
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Overview
We propose a characterization of complex networks, based on the potential of an associated Schrödinger equation. The potential is designed so that the energy spectrum of the Schrödinger equation coincides with the graph spectrum of the normalized Laplacian. Crucial information is retained in the reconstructed potential, which provides a compact representation of the properties of the network structure. The median potential over several random network realizations, which we call
ensemble potential
, is fitted via a Landau-like function, and its length scale is found to diverge as the critical connection probability is approached from above. The ruggedness of the ensemble potential profile is quantified by using the Higuchi fractal dimension, which displays a maximum at the critical connection probability. This demonstrates that this technique can be successfully employed in the study of random networks, as an alternative indicator of the percolation phase transition. We apply the proposed approach to the investigation of real-world networks describing infrastructures (US power grid). Curiously, although no notion of phase transition can be given for such networks, the fractality of the
ensemble
potential displays signatures of criticality. We also show that standard techniques (such as the scaling features of the largest connected component) do not detect any signature or remnant of criticality.
Publisher
Nature Publishing Group UK,Nature Publishing Group
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