A strategy for quantum algorithm design assisted by machine learning

A strategy for quantum algorithm design assisted by machine learning

10.1088/1367-2630/16/7/073017

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Bibliographic Details
Main Authors: Bang, J, Ryu, J, Yoo, S, Pawlowski, M, Lee, J
Other Authors: CENTRE FOR QUANTUM TECHNOLOGIES
Format: Article
Published: Institute of Physics Publishing 2020
Subjects:
Automation
Control
Learning systems
Monte Carlo methods
Problem solving
Quantum theory
Decision problems
Deutsch-Jozsa problems
Exponential dependence
Hybrid simulators
Learning-based methods
Quantum algorithms
Quantum learning
Quantum-classical
Algorithms
Online Access:https://scholarbank.nus.edu.sg/handle/10635/180175
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Institution: National University of Singapore
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spelling sg-nus-scholar.10635-1801752023-08-29T09:17:22Z A strategy for quantum algorithm design assisted by machine learning Bang, J Ryu, J Yoo, S Pawlowski, M Lee, J CENTRE FOR QUANTUM TECHNOLOGIES Automation Control Learning systems Monte Carlo methods Problem solving Quantum theory Decision problems Deutsch-Jozsa problems Exponential dependence Hybrid simulators Learning-based methods Quantum algorithms Quantum learning Quantum-classical Algorithms 10.1088/1367-2630/16/7/073017 New Journal of Physics 16 73017 2020-10-26T07:21:55Z 2020-10-26T07:21:55Z 2014 Article Bang, J, Ryu, J, Yoo, S, Pawlowski, M, Lee, J (2014). A strategy for quantum algorithm design assisted by machine learning. New Journal of Physics 16 : 73017. ScholarBank@NUS Repository. https://doi.org/10.1088/1367-2630/16/7/073017 1367-2630 https://scholarbank.nus.edu.sg/handle/10635/180175 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Institute of Physics Publishing Unpaywall 20201031
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
topic Automation
Control
Learning systems
Monte Carlo methods
Problem solving
Quantum theory
Decision problems
Deutsch-Jozsa problems
Exponential dependence
Hybrid simulators
Learning-based methods
Quantum algorithms
Quantum learning
Quantum-classical
Algorithms
spellingShingle Automation
Control
Learning systems
Monte Carlo methods
Problem solving
Quantum theory
Decision problems
Deutsch-Jozsa problems
Exponential dependence
Hybrid simulators
Learning-based methods
Quantum algorithms
Quantum learning
Quantum-classical
Algorithms
Bang, J
Ryu, J
Yoo, S
Pawlowski, M
Lee, J
A strategy for quantum algorithm design assisted by machine learning
description 10.1088/1367-2630/16/7/073017
author2 CENTRE FOR QUANTUM TECHNOLOGIES
author_facet CENTRE FOR QUANTUM TECHNOLOGIES
Bang, J
Ryu, J
Yoo, S
Pawlowski, M
Lee, J
format Article
author Bang, J
Ryu, J
Yoo, S
Pawlowski, M
Lee, J
author_sort Bang, J
title A strategy for quantum algorithm design assisted by machine learning
title_short A strategy for quantum algorithm design assisted by machine learning
title_full A strategy for quantum algorithm design assisted by machine learning
title_fullStr A strategy for quantum algorithm design assisted by machine learning
title_full_unstemmed A strategy for quantum algorithm design assisted by machine learning
title_sort strategy for quantum algorithm design assisted by machine learning
publisher Institute of Physics Publishing
publishDate 2020
url https://scholarbank.nus.edu.sg/handle/10635/180175
_version_ 1779152651282284544

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