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Supercomputing leverages quantum machine learning and Grover’s algorithm

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Abstract

The complexity of searching algorithms in classical computing is a classic problem and a research area. Quantum computers and quantum algorithms can efficiently compute some classically hard problems. In addition, quantum machine learning algorithms could be an important avenue to boost existing and new quantum-based technology, reducing the supercomputing requirements for executing such problems. This paper reviews and explores topics such as variational quantum algorithms, kernel methods, and Grover’s algorithm (GA). GA is a quantum search algorithm that achieves a quadratic speed improvement as a quantum classifier. We exploit GA or amplitude amplification to simulate rudimentary classical logical gates into quantum circuits considering AND, XOR, and OR gates. Our experiments in our review suggest that the algorithms discussed can be implemented and verified with relative ease, suggesting that researchers can investigate problems in the areas discussed related to quantum machine learning and more.

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Acknowledgements

We would like to thank the Department of Computer Science and Baylor.AI laboratory at Baylor University for their support. We acknowledge the use of IBM Quantum services for this work. The views expressed are those of the authors and do not reflect the official policy or position of IBM or the IBM Quantum team. J. O. executed most of this work while at Baylor University.

Funding

This work was supported in part by the National Science Foundation under grants CNS-2136961, and CNS-2210091.

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Authors and Affiliations

  1. Department of Computer Science, Baylor University, One Bear Place #97141, Waco, Texas, 76712-7141, USA

    Bikram Khanal, Pablo Rivas & Erich Baker

  2. Department of Mathematics and Computer Science, Earlham College, 801 W Nat’l Rd, Richmond, IN, 47374, USA

    Javier Orduz

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  1. Bikram Khanal
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Correspondence to Pablo Rivas.

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Khanal, B., Orduz, J., Rivas, P. et al. Supercomputing leverages quantum machine learning and Grover’s algorithm. J Supercomput 79, 6918–6940 (2023). https://doi.org/10.1007/s11227-022-04923-4

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