## Abstract

We use a Bayesian approach to optimally solve problems innoisy binary search. We deal with two variants:1. Each comparison is erroneous with independent probability 1-p.2. At each stage k comparisons can be performed in parallel and a noisy answer is returned.We present a (classical) algorithm which solves bothvariants optimally (with respect to p and k), up to an additive term of loglog n, and prove matching information-theoretic lower bounds. We use the algorithm to improve the results of Farhi et al. [FGGS99], presenting an exact quantum search algorithm in an ordered list of expected complexity less than log n / 3.

Original language | American English |
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Title of host publication | Foundations of Computer Science, 2008. FOCS'08. IEEE 49th Annual IEEE Symposium on |

Publisher | IEEE |

State | Published - 2008 |