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Transport on weighted Networks: when correlations are independent of degree

, und .
(September 2006)

Zusammenfassung

Most real-world networks are weighted graphs with the weight of the edges reflecting the relative importance of each connection. In this work, we study non degree dependent correlations between edge weights, generalizing thus the correlations beyond the degree dependent case. We find that two measures, the disparity and the weight range, defined here, are able to discriminate between the different types of correlations. We also study the effect of these weight correlations on the transport properties of the networks. We find that positive correlations dramatically improve transport. The classic case of degree dependent weight correlations corresponds to the limit of our work with positive weight correlations.

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