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Center for Nonlinear Studies |
An important method for search engine result ranking works by finding the principal eigenvector of the "Google matrix." Here, we show that a recently proposed quantum algorithm for preparing this eigenvector has a run-time that depends on features of the graphs other than the degree distribution. For a sample of graphs with degree distributions that more closely resemble the Web than in previous work, the proposed algorithm for eigenvector preparation does not appear to run exponentially faster than the classical case.
Host: Robert Ecke