arXiv:quant-ph/9807052

A Quantum Computational Learning Algorithm

Dan A. Ventura, Tony R. Martinez

Published Jul 18, 1998• 7 citations

Abstract

An interesting classical result due to Jackson allows polynomial-time learning of the function class DNF using membership queries. Since in most practical learning situations access to a membership oracle is unrealistic, this paper explores the possibility that quantum computation might allow a learning algorithm for DNF that relies only on example queries. A natural extension of Fourier-based learning into the quantum domain is presented. The algorithm requires only an example oracle, and it runs in O(sqrt(2^n)) time, a result that appears to be classically impossible. The algorithm is unique among quantum algorithms in that it does not assume a priori knowledge of a function and does not operate on a superposition that includes all possible states.

DOI: 10.48550/arxiv.quant-ph/9807052

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