Distributed Spectral Decomposition in Networks by Complex Diffusion and Quantum Random Walk

In this paper, we address the problem of finding top k eigenvalues and corresponding eigenvectors of symmetric graph matrices in networks in a distributed way. We propose a novel idea called complex power iterations, in order to decompose the eigenvalues and eigenvectors at node level analogous to timefrequency analysis in signal processing