Power law scaling for the adiabatic algorithm for search engine ranking
Quantum Physics
2013-09-11 v4 Physics and Society
Abstract
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 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.
Cite
@article{arxiv.1211.2248,
title = {Power law scaling for the adiabatic algorithm for search engine ranking},
author = {Adam Frees and John King Gamble and Kenneth Rudinger and Eric Bach and Mark Friesen and Robert Joynt and S. N. Coppersmith},
journal= {arXiv preprint arXiv:1211.2248},
year = {2013}
}
Comments
6 pages, 4 figures