# Power-law scaling for the adiabatic algorithm for search-engine ranking

@article{Frees2013PowerlawSF, title={Power-law scaling for the adiabatic algorithm for search-engine ranking}, author={Adam Frees and John King Gamble and Kenneth M Rudinger and Eric Bach and Mark Friesen and Robert Joynt and Susan N. Coppersmith}, journal={Physical Review A}, year={2013}, volume={88}, pages={032307} }

An important method for search engine result ranking works by finding the principal eigenvector of the "Google matrix." Recently, a quantum algorithm for preparing this eigenvector and evidence of an exponential speedup for some scale-free networks were presented. Here, we show that the run-time depends on features of the graphs other than the degree distribution, and can be altered sufficiently to rule out a general exponential speedup. For a sample of graphs with degree distributions that…

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