Random walks in complex networks (Yuan Lin)

Abstract

Random walks in complex networks are a fascinating research field, not only for their intrinsic theoretical beauty but also for their wide ranging applications across various scientific issues.

In this talk, I will present our recent works on random walks in complex networks. We propose a general framework for random walks in weighted networks. By utilizing the spectral graph theory, we provide an exact formula for mean first-passage time (MFPT) in terms of the eigenvalues and eigenvectors of Laplacian matrix, based on which we further derive a sharp lower bound for MFPT. Then, applying our framework, we study two significant biased random walks, maximal entropy random walks and non-backtracking centrality based random walks. We evaluate the key quantities for both biased random walks and investigate the impact of network topology on their dynamical behaviors.

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