TY - JOUR

T1 - Optimal paths in complex networks with correlated weights

T2 - The worldwide airport network

AU - Wu, Zhenhua

AU - Braunstein, Lidia A.

AU - Colizza, Vittoria

AU - Cohen, Reuven

AU - Havlin, Shlomo

AU - Stanley, H. Eugene

PY - 2006

Y1 - 2006

N2 - We study complex networks with weights wij associated with each link connecting node i and j. The weights are chosen to be correlated with the network topology in the form found in two real world examples: (a) the worldwide airport network and (b) the E. Coli metabolic network. Here wij ∼ xij (ki kj) α, where ki and kj are the degrees of nodes i and j, xij is a random number, and α represents the strength of the correlations. The case α>0 represents correlation between weights and degree, while α<0 represents anticorrelation and the case α=0 reduces to the case of no correlations. We study the scaling of the lengths of the optimal paths, ℓopt, with the system size N in strong disorder for scale-free networks for different α. We find two different universality classes for ℓopt in strong disorder depending on α: (i) if α>0, then for λ>2 the scaling law ℓopt ∼ N1/3, where λ is the power-law exponent of the degree distribution of scale-free networks, and (ii) if α≤0, then ℓopt ∼ N νopt with νopt identical to its value for the uncorrelated case α=0. We calculate the robustness of correlated scale-free networks with different α and find the networks with α<0 to be the most robust networks when compared to the other values of α. We propose an analytical method to study percolation phenomena on networks with this kind of correlation, and our numerical results suggest that for scale-free networks with α<0, the percolation threshold pc is finite for λ>3, which belongs to the same universality class as α=0. We compare our simulation results with the real worldwide airport network, and we find good agreement.

AB - We study complex networks with weights wij associated with each link connecting node i and j. The weights are chosen to be correlated with the network topology in the form found in two real world examples: (a) the worldwide airport network and (b) the E. Coli metabolic network. Here wij ∼ xij (ki kj) α, where ki and kj are the degrees of nodes i and j, xij is a random number, and α represents the strength of the correlations. The case α>0 represents correlation between weights and degree, while α<0 represents anticorrelation and the case α=0 reduces to the case of no correlations. We study the scaling of the lengths of the optimal paths, ℓopt, with the system size N in strong disorder for scale-free networks for different α. We find two different universality classes for ℓopt in strong disorder depending on α: (i) if α>0, then for λ>2 the scaling law ℓopt ∼ N1/3, where λ is the power-law exponent of the degree distribution of scale-free networks, and (ii) if α≤0, then ℓopt ∼ N νopt with νopt identical to its value for the uncorrelated case α=0. We calculate the robustness of correlated scale-free networks with different α and find the networks with α<0 to be the most robust networks when compared to the other values of α. We propose an analytical method to study percolation phenomena on networks with this kind of correlation, and our numerical results suggest that for scale-free networks with α<0, the percolation threshold pc is finite for λ>3, which belongs to the same universality class as α=0. We compare our simulation results with the real worldwide airport network, and we find good agreement.

UR - http://www.scopus.com/inward/record.url?scp=33750726100&partnerID=8YFLogxK

U2 - 10.1103/PhysRevE.74.056104

DO - 10.1103/PhysRevE.74.056104

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AN - SCOPUS:33750726100

SN - 1539-3755

VL - 74

JO - Physical Review E

JF - Physical Review E

IS - 5

M1 - 056104

ER -