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Quantum Algorithm Design: Techniques and Applications

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Abstract

In recent years, rapid developments of quantum computer are witnessed in both the hardware and the algorithm domains, making it necessary to have an updated review of some major techniques and applications in quantum algorithm design.

In this survey as well as tutorial article, the authors first present an overview of the development of quantum algorithms, then investigate five important techniques: Quantum phase estimation, linear combination of unitaries, quantum linear solver, Grover search, and quantum walk, together with their applications in quantum state preparation, quantum machine learning, and quantum search. In the end, the authors collect some open problems influencing the development of future quantum algorithms.

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  1. Academy of Mathematics and Systems Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, 100190, China

    Changpeng Shao, Yang Li & Hongbo Li

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This research was supported partially by the National Natural Science Foundation of China under Grant No. 11671388, CAS Project QYZDJ-SSW-SYS022, and GF S&T Innovation Special Zone Project.

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Shao, C., Li, Y. & Li, H. Quantum Algorithm Design: Techniques and Applications. J Syst Sci Complex 32, 375–452 (2019). https://doi.org/10.1007/s11424-019-9008-0

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