Super-exponential query complexity reduction via noise-resistant quantum search
Quantum Physics
2017-10-31 v1
Abstract
In the SEARCH WITH ADVICE problem, a single entry of interest within a database of N entries is to be found assuming that an ordering of the entries, from that with the highest probability of being the entry of interest (as determined by a so-called advice distribution) to that with the lowest, is provided. We present a quantum algorithm that, in the presence of significant levels of quantum noise, solves SEARCH WITH ADVICE for a power law advice distribution with average-case query complexity O(1) as N tends to infinity. Since as we also show the best classical algorithms for this problem exhibit average-case query complexity of order no better than log(N), our quantum algorithm provides a super-exponential reduction in query complexity.
Keywords
Cite
@article{arxiv.1710.10790,
title = {Super-exponential query complexity reduction via noise-resistant quantum search},
author = {Daniel Z. Zanger},
journal= {arXiv preprint arXiv:1710.10790},
year = {2017}
}