Searching for Key Cycles in a Complex Network.

Searching for key nodes and edges in a network is a long-standing problem. Recently cycle structure in a network has received more attention. Is it possible to propose a ranking algorithm for cycle importance? We address the problem of identifying the key cycles of a network. First, we provide a more concrete definition of importance-in terms of Fiedler value (the second smallest Laplacian eigenvalue). Key cycles are those that contribute most substantially to the dynamical behavior of the network. Second, by comparing the sensitivity of Fiedler value to different cycles, a neat index for ranking cycles is provided. Numerical examples are given to show the effectiveness of this method.