Degree distribution of complex networks from statistical mechanics principles
| dc.creator | Bianconi, Ginestra | |
| dc.date | 2006-06-14 | |
| dc.date | 2006-12-21 | |
| dc.date.accessioned | 2026-07-07T07:36:30Z | |
| dc.date.available | 2026-07-07T07:36:30Z | |
| dc.description | In this paper we describe the emergence of scale-free degree distributions from statistical mechanics principles. We define an energy associated to a degree sequence as the logarithm of the number of indistinguishable simple networks it is possible to draw given the degree sequence. Keeping fixed the total number of nodes and links, we show that the energy of scale-free distribution is much higher than the energy associated to the degree sequence of regular random graphs. This results unable us to estimate the annealed average of the number of distinguishable simple graphs it is possible to draw given a scale-free distribution with structural cutoff. In particular we shaw that this number for large networks is strongly suppressed for power -law exponent γ->2. | |
| dc.description | (3 figures) | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0606365 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0606365 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/120449 | |
| dc.subject | Statistical Mechanics | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.title | Degree distribution of complex networks from statistical mechanics principles | |
| dc.type | text |