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

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...

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Autores principales: Valdez, Fevrier, Melin, Patricia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988117/
https://www.ncbi.nlm.nih.gov/pubmed/35411203
http://dx.doi.org/10.1007/s00500-022-07037-4
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author Valdez, Fevrier
Melin, Patricia
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Melin, Patricia
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description 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.
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spelling pubmed-89881172022-04-07 A review on quantum computing and deep learning algorithms and their applications Valdez, Fevrier Melin, Patricia Soft comput Focus 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. Springer Berlin Heidelberg 2022-04-07 /pmc/articles/PMC8988117/ /pubmed/35411203 http://dx.doi.org/10.1007/s00500-022-07037-4 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Focus
Valdez, Fevrier
Melin, Patricia
A review on quantum computing and deep learning algorithms and their applications
title A review on quantum computing and deep learning algorithms and their applications
title_full A review on quantum computing and deep learning algorithms and their applications
title_fullStr A review on quantum computing and deep learning algorithms and their applications
title_full_unstemmed A review on quantum computing and deep learning algorithms and their applications
title_short A review on quantum computing and deep learning algorithms and their applications
title_sort review on quantum computing and deep learning algorithms and their applications
topic Focus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988117/
https://www.ncbi.nlm.nih.gov/pubmed/35411203
http://dx.doi.org/10.1007/s00500-022-07037-4
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