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    Depth optimization of quantum search algorithms beyond Grover's algorithm

    Kun Zhang1 and Vladimir E. Korepin2,3

    • 1Department of Chemistry, State University of New York at Stony Brook, Stony Brook, New York 11794, USA
    • 2C.N. Yang Institute for Theoretical Physics, State University of New York at Stony Brook, Stony Brook, New York 11794-3840, USA
    • 3Institute for Advanced Computational Science, State University of New York at Stony Brook, Stony Brook, New York 11794-5250, USA

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    Phys. Rev. A 101, 032346 – Published 26 March, 2020

    DOI: https://doi.org/10.1103/PhysRevA.101.032346

    Abstract

    Grover's quantum search algorithm provides a quadratic speedup over the classical one. The computational complexity is based on the number of queries to the oracle. However, depth is a more modern metric for noisy intermediate-scale quantum computers. We propose a depth optimization method for the quantum search algorithm. We show that Grover's algorithm is not optimal in depth. We propose a quantum search algorithm, which can be divided into several stages. Each stage has a new initialization, which is a rescaling of the database. This decreases errors. The multistage design is natural for parallel running of the quantum search algorithm.

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    Phys. Rev. A 101, 032346– Published 26 March, 2020
    • Received 13 August 2019
    • Accepted 27 February 2020
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