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arXiv · 1908.04171

Depth optimization of quantum search algorithms beyond Grover's algorithm

Kun Zhang·Vladimir E. Korepin
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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 new depth optimization method for quantum search algorithms. 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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Kun Zhang, Vladimir E. Korepin. 2020-03-27. Depth optimization of quantum search algorithms beyond Grover's algorithm. https://doi.org/10.1103/physreva.101.032346

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