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Basic protocols in quantum reinforcement learning with superconducting circuits
Superconducting circuit technologies have recently achieved quantum protocols involving closed feedback loops. Quantum artificial intelligence and quantum machine learning are emerging fields inside quantum technologies which may enable quantum devices to acquire information from the outer world and...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5431677/ https://www.ncbi.nlm.nih.gov/pubmed/28487535 http://dx.doi.org/10.1038/s41598-017-01711-6 |
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author | Lamata, Lucas |
author_facet | Lamata, Lucas |
author_sort | Lamata, Lucas |
collection | PubMed |
description | Superconducting circuit technologies have recently achieved quantum protocols involving closed feedback loops. Quantum artificial intelligence and quantum machine learning are emerging fields inside quantum technologies which may enable quantum devices to acquire information from the outer world and improve themselves via a learning process. Here we propose the implementation of basic protocols in quantum reinforcement learning, with superconducting circuits employing feedback- loop control. We introduce diverse scenarios for proof-of-principle experiments with state-of-the-art superconducting circuit technologies and analyze their feasibility in presence of imperfections. The field of quantum artificial intelligence implemented with superconducting circuits paves the way for enhanced quantum control and quantum computation protocols. |
format | Online Article Text |
id | pubmed-5431677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54316772017-05-16 Basic protocols in quantum reinforcement learning with superconducting circuits Lamata, Lucas Sci Rep Article Superconducting circuit technologies have recently achieved quantum protocols involving closed feedback loops. Quantum artificial intelligence and quantum machine learning are emerging fields inside quantum technologies which may enable quantum devices to acquire information from the outer world and improve themselves via a learning process. Here we propose the implementation of basic protocols in quantum reinforcement learning, with superconducting circuits employing feedback- loop control. We introduce diverse scenarios for proof-of-principle experiments with state-of-the-art superconducting circuit technologies and analyze their feasibility in presence of imperfections. The field of quantum artificial intelligence implemented with superconducting circuits paves the way for enhanced quantum control and quantum computation protocols. Nature Publishing Group UK 2017-05-09 /pmc/articles/PMC5431677/ /pubmed/28487535 http://dx.doi.org/10.1038/s41598-017-01711-6 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lamata, Lucas Basic protocols in quantum reinforcement learning with superconducting circuits |
title | Basic protocols in quantum reinforcement learning with superconducting circuits |
title_full | Basic protocols in quantum reinforcement learning with superconducting circuits |
title_fullStr | Basic protocols in quantum reinforcement learning with superconducting circuits |
title_full_unstemmed | Basic protocols in quantum reinforcement learning with superconducting circuits |
title_short | Basic protocols in quantum reinforcement learning with superconducting circuits |
title_sort | basic protocols in quantum reinforcement learning with superconducting circuits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5431677/ https://www.ncbi.nlm.nih.gov/pubmed/28487535 http://dx.doi.org/10.1038/s41598-017-01711-6 |
work_keys_str_mv | AT lamatalucas basicprotocolsinquantumreinforcementlearningwithsuperconductingcircuits |