Modular networks emerge from multiconstraint optimization
| dc.creator | Pan, Raj Kumar | |
| dc.creator | Sinha, Sitabhra | |
| dc.date | 2007-03-04 | |
| dc.date | 2007-11-05 | |
| dc.date.accessioned | 2026-07-07T08:40:20Z | |
| dc.date.available | 2026-07-07T08:40:20Z | |
| dc.description | Modular structure is ubiquitous among complex networks. We note that most such systems are subject to multiple structural and functional constraints, e.g., minimizing the average path length and the total number of links, while maximizing robustness against perturbations in node activity. We show that the optimal networks satisfying these three constraints are characterized by the existence of multiple subnetworks (modules) sparsely connected to each other. In addition, these modules have distinct hubs, resulting in an overall heterogeneous degree distribution. | |
| dc.description | 5 pages, 4 figures; Published version | |
| dc.identifier | https://arxiv.org/abs/physics/0703033 | |
| dc.identifier | http://arxiv.org/abs/physics/0703033 | |
| dc.identifier | Phys. Rev. E 76, 045103(R) (2007) (4 pages) | |
| dc.identifier | doi:10.1103/PhysRevE.76.045103 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/141345 | |
| dc.subject | Physics and Society | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.title | Modular networks emerge from multiconstraint optimization | |
| dc.type | text |