Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr 7:1-20.
doi: 10.1007/s00500-022-07037-4. Online ahead of print.

A review on quantum computing and deep learning algorithms and their applications

Fevrier Valdez  1 , Patricia Melin  1
Affiliations

A review on quantum computing and deep learning algorithms and their applications

Fevrier Valdez et al. Soft comput. .

Abstract

In this paper, we describe a review concerning the Quantum Computing (QC) and Deep Learning (DL) areas and their applications in Computational Intelligence (CI). Quantum algorithms (QAs), engage the rules of quantum mechanics to solve problems using quantum information, where the quantum information is concerning the state of a quantum system, which can be manipulated using quantum information algorithms and other processing techniques. Nowadays, many QAs have been proposed, whose general conclusion is that using the effects of quantum mechanics results in a significant speedup (exponential, polynomial, super polynomial) over the traditional algorithms. This implies that some complex problems currently intractable with traditional algorithms can be solved with QA. On the other hand, DL algorithms offer what is known as machine learning techniques. DL is concerned with teaching a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of plain text, images, or sound. The inspiration for deep learning is the way that the human brain filters information. Therefore, in this research, we analyzed these two areas to observe the most relevant works and applications developed by the researchers in the world.

Keywords: Control; Deep learning; Fuzzy logic; Intelligent; Medicine; Neural networks; Quantum computing; Robotic.

PubMed Disclaimer

Conflict of interest statement

Conflict of interestAll the authors in the paper have no conflict of interest.

Figures

Fig. 1
Fig. 1
Domains of deep learning, machine learning and artificial intelligence
Fig. 2
Fig. 2
Topic ‘quantum computing’. collected data from WoS
Fig. 3
Fig. 3
Topic ‘deep learning’. collected data from WoS
Fig. 4
Fig. 4
Scopus authors working with QC and DL algorithms
Fig. 5
Fig. 5
Document types from Scopus database
Fig. 6
Fig. 6
Documents from Scopus database in the last 10 years
Fig. 7
Fig. 7
Scopus citations with the topic medicine quantum computing
Fig. 8
Fig. 8
Network with the topic medicine quantum computing
Fig. 9
Fig. 9
Network with the topic intelligent control quantum computing
Fig. 10
Fig. 10
Density with the topic intelligent control quantum computing
Fig. 11
Fig. 11
Citations from Scopus Scopus citations with the topic ‘Intelligent Control Quantum Computing’
Fig. 12
Fig. 12
Network with the topic robotic quantum computing
Fig. 13
Fig. 13
Overlay with the topic robotic quantum computing
Fig. 14
Fig. 14
Density with the topic robotic quantum computing
Fig. 15
Fig. 15
Scopus citations with the topic’Robotic Quantum Computing’
Fig. 16
Fig. 16
Network with the topic medicine deep learning algorithms
Fig. 17
Fig. 17
Density with the topic medicine deep learning algorithms
Fig. 18
Fig. 18
Scopus citations with the topic ‘Medicine Deep Learning Algorithms’
Fig. 19
Fig. 19
Network with the topic ‘intelligent control deep learning algorithms’
Fig. 20
Fig. 20
Density with the topic ‘intelligent control deep learning algorithms’
Fig. 21
Fig. 21
Scopus citations with the topic ‘Intelligent Control Deep Learning Algorithms’
Fig. 22
Fig. 22
Network with the topic ‘robotic deep learning algorithms’
Fig. 23
Fig. 23
Density with the topic ‘robotic deep learning algorithms’
Fig. 24
Fig. 24
Scopus citations with the topic ‘Robotic Deep Learning Algorithms’
See this image and copyright information in PMC

References

    1. Ajagekar A, You F. Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems. Scopus. 2021 doi: 10.1016/j.apenergy.2021.117628. - DOI
    1. Alberts GJN, Rol MA, Last T, Broer BW, Bultink CC, Rijlaarsdam MSC, Hauwermeiren AEV. Accelerating quantum computer developments. Scopus. 2021 doi: 10.1140/epjqt/s40507-021-00107-w. - DOI
    1. Alzubaidi L, Zhang J, Humaidi AJ, Al-Dujaili A, Duan Y, Al-Shamma O, Santamaría J, Fadhel MA, Al-Amidie M, Farhan L. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. Scopus. 2021 doi: 10.1186/s40537-021-00444-8. - DOI - PMC - PubMed
    1. Ankita S, Shikha A, Jitendra A, Sanjeev S. A review on application of particle swarm optimization in association rule mining. Scopus. 2013;199:405–414. doi: 10.1007/978-3-642-35314-7_46. - DOI
    1. Arulkumaran K, Deisenroth MP, Brundage M, Bharath AA. Deep reinforcement learning: a brief survey. Scopus. 2017;34(6):26–38. doi: 10.1109/MSP.2017.2743240. - DOI

LinkOut - more resources