Download pdf
Quantum computing and its revolutionary potential
- 1 Capitol Technology University
* Author to whom correspondence should be addressed.
Abstract
The rapid emergence of quantum computing offers the potential to revolutionize numerous domains, promising computational advantages over classical counterparts. This study aimed to evaluate the performance, efficiency, and robustness of selected quantum algorithms—Quantum Variational Eigensolver (VQE), Quantum Fourier Transform (QFT), and Quantum Phase Estimation (QPE)—on near-term quantum devices. Our benchmarking revealed that, despite promising theoretical benefits, the practical deployment of these algorithms remains challenged by noise, error rates, and hardware limitations. The VQE showed promise in molecular modeling, while the utility of QFT and QPE in cryptography and optimization became evident. Nevertheless, their practical efficiency is contingent upon specific quantum hardware and employed error mitigation techniques. The findings underscore the transformative potential of quantum computing, but also emphasize the ongoing challenges that need addressing to make quantum computing practically advantageous.
Keywords
quantum computing, quantum algorithms, near-term quantum devices, error mitigation, quantum benchmarking
[1]. Arute, F., Arya, K., Babbush, R., et al. (2019). Quantum supremacy using a programmable superconducting processor. Nature, 574(7779), 505–510.
[2]. Bravyi, S., Gosset, D., & König, R. (2018). Quantum advantage with shallow circuits. Science, 362(6412), 308-311.
[3]. McArdle, S., Endo, S., Aspuru-Guzik, A., Benjamin, S. C., & Yuan, X. (2020). Quantum computational chemistry. Reviews of Modern Physics, 92(1), 015003.
[4]. Pednault, E., Gunnels, J. A., Nannicini, G., Horesh, L., & Wisnieff, R. (2019). On “Quantum Supremacy”. IBM Research Blog.
[5]. Schuld, M., Sinayskiy, I., & Petruccione, F. (2021). An introduction to quantum machine learning. Contemporary Physics, 56(2), 172-185.
[6]. Terhal, B. M. (2020). Quantum error correction for quantum memories. Reviews of Modern Physics, 87(2), 307.
[7]. Yin, J., Cao, Y., Li, Y. H., et al. (2020). Entanglement-based secure quantum cryptography over 1,120 kilometres. Nature, 582(7813), 501–505.
[8]. Arute, F., et al. (2019). Quantum supremacy using a programmable superconducting processor. Nature, 574(7779), 505–510.
[9]. Endo, S., Benjamin, S. C., & Li, Y. (2021). Practical quantum error mitigation for near-future applications. Physical Review X, 8(3), 031027.
[10]. IBM Q Experience. (2021). Quantum Computing Documentation.
[11]. Kitaev, A. Y. (1995). Quantum measurements and the Abelian Stabilizer Problem. arXiv preprint quant-ph/9511026.
[12]. Nielsen, M. A., & Chuang, I. L. (2010). Quantum computation and quantum information. Cambridge University Press.
[13]. Peruzzo, A., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213.
[14]. Preskill, J. (2018). Quantum Computing in the NISQ era and beyond. Quantum, 2, 79.
[15]. Qiskit. (2020). Qiskit Documentation.
[16]. Arute, F., et al. (2019). Quantum supremacy using a programmable superconducting processor. Nature, 574(7779), 505–510.
[17]. Endo, S., Benjamin, S. C., & Li, Y. (2021). Practical quantum error mitigation for near-future applications. Physical Review X, 8(3), 031027.
[18]. IBM Q Experience. (2021). Quantum Computing Documentation.
[19]. Kitaev, A. Y. (1995). Quantum measurements and the Abelian Stabilizer Problem. arXiv preprint quant-ph/9511026.
[20]. Nielsen, M. A., & Chuang, I. L. (2010). Quantum computation and quantum information. Cambridge University Press.
[21]. Peruzzo, A., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213.
[22]. Preskill, J. (2018). Quantum Computing in the NISQ era and beyond. Quantum, 2, 79.
[23]. Qiskit. (2020). Qiskit Documentation.
Cite this article
Chia,H.L.B. (2023). Quantum computing and its revolutionary potential. Advances in Engineering Innovation,4,26-32.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Journal：Advances in Engineering Innovation
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).