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Emergence Of Multiscaling In Heterogeneous Complex Networks

Author

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  • A. SANTIAGO

    (Grupo de Sistemas Complejos, Departamento de Física y Mecánica, Escuela Técnica Superior de Ingenieros Agrónomos, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • R. M. BENITO

    (Grupo de Sistemas Complejos, Departamento de Física y Mecánica, Escuela Técnica Superior de Ingenieros Agrónomos, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

Abstract

In this paper we provide numerical evidence of the richer behavior of the connectivity degrees in heterogeneous preferential attachment networks in comparison to their homogeneous counterparts. We analyze the degree distribution in the threshold model, a preferential attachment model where the affinity between node states biases the attachment probabilities of links. We show that the degree densities exhibit a power-law multiscaling which points to a signature of heterogeneity in preferential attachment networks. This translates into a power-law scaling in the degree distribution, whose exponent depends on the specific form of heterogeneity in the attachment mechanism.

Suggested Citation

  • A. Santiago & R. M. Benito, 2007. "Emergence Of Multiscaling In Heterogeneous Complex Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(10), pages 1591-1607.
    • Handle: RePEc:wsi:ijmpcx:v:18:y:2007:i:10:n:s0129183107011571
    DOI: 10.1142/S0129183107011571
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    Cited by:

    1. Santiago, A. & Benito, R.M., 2009. "Robustness of heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(11), pages 2234-2242.
    2. Santiago, A. & Benito, R.M., 2009. "Local affinity in heterogeneous growing networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2941-2948.
    3. Santiago, A. & Benito, R.M., 2008. "Connectivity degrees in the threshold preferential attachment model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2365-2376.

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