### Abstract

We consider nonequilibrium phase transitions, such as epidemic spreading, in weighted scale-free networks, in which highly connected nodes have a relatively smaller ability to transfer infection. We solve the dynamical mean-field equations and discuss finite-size scaling theory. The theoretical predictions are confronted with the results of large scale Monte Carlo simulations on the weighted Barabási-Albert network. Local scaling exponents are found different at a typical site and at a node with very large connectivity.

Original language | English |
---|---|

Article number | 036116 |

Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |

Volume | 73 |

Issue number | 3 |

DOIs | |

Publication status | Published - 2006 |

### Fingerprint

### ASJC Scopus subject areas

- Physics and Astronomy(all)
- Condensed Matter Physics
- Statistical and Nonlinear Physics
- Mathematical Physics

### Cite this

**Nonequilibrium phase transitions and finite-size scaling in weighted scale-free networks.** / Karsai, Márton; Juhász, Róbert; Iglói, F.

Research output: Contribution to journal › Article

*Physical Review E - Statistical, Nonlinear, and Soft Matter Physics*, vol. 73, no. 3, 036116. https://doi.org/10.1103/PhysRevE.73.036116

}

TY - JOUR

T1 - Nonequilibrium phase transitions and finite-size scaling in weighted scale-free networks

AU - Karsai, Márton

AU - Juhász, Róbert

AU - Iglói, F.

PY - 2006

Y1 - 2006

N2 - We consider nonequilibrium phase transitions, such as epidemic spreading, in weighted scale-free networks, in which highly connected nodes have a relatively smaller ability to transfer infection. We solve the dynamical mean-field equations and discuss finite-size scaling theory. The theoretical predictions are confronted with the results of large scale Monte Carlo simulations on the weighted Barabási-Albert network. Local scaling exponents are found different at a typical site and at a node with very large connectivity.

AB - We consider nonequilibrium phase transitions, such as epidemic spreading, in weighted scale-free networks, in which highly connected nodes have a relatively smaller ability to transfer infection. We solve the dynamical mean-field equations and discuss finite-size scaling theory. The theoretical predictions are confronted with the results of large scale Monte Carlo simulations on the weighted Barabási-Albert network. Local scaling exponents are found different at a typical site and at a node with very large connectivity.

UR - http://www.scopus.com/inward/record.url?scp=33645014174&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33645014174&partnerID=8YFLogxK

U2 - 10.1103/PhysRevE.73.036116

DO - 10.1103/PhysRevE.73.036116

M3 - Article

AN - SCOPUS:33645014174

VL - 73

JO - Physical review. E

JF - Physical review. E

SN - 2470-0045

IS - 3

M1 - 036116

ER -