Demonstration of quantum advantage in machine learning

Large advantage in small quantum computers Quantum computing promises to revolutionize all fields of science by solving problems that are too complex for conventional computers. However, the realization of a full-fledged, universal quantum computer is still far ahead, requiring millions of quantum b...

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Autores principales:	Diego Ristè, Marcus P. da Silva, Colm A. Ryan, Andrew W. Cross, Antonio D. Córcoles, John A. Smolin, Jay M. Gambetta, Jerry M. Chow, Blake R. Johnson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/b5566ab8f0a84a03ad96e12cf550175d
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spelling	oai:doaj.org-article:b5566ab8f0a84a03ad96e12cf550175d2021-12-02T12:33:55ZDemonstration of quantum advantage in machine learning10.1038/s41534-017-0017-32056-6387https://doaj.org/article/b5566ab8f0a84a03ad96e12cf550175d2017-04-01T00:00:00Zhttps://doi.org/10.1038/s41534-017-0017-3https://doaj.org/toc/2056-6387Large advantage in small quantum computers Quantum computing promises to revolutionize all fields of science by solving problems that are too complex for conventional computers. However, the realization of a full-fledged, universal quantum computer is still far ahead, requiring millions of quantum bits and very low error rates. Despite this, D. Ristè and colleagues at Raytheon BBN Technologies, with collaborators at IBM, have demonstrated that a quantum advantage already appears with only a few quantum bits and a highly noisy system. The team solved a particular problem, known as learning parity with noise, using a five-qubit superconducting quantum processor. Counting the number of times that the processor runs, they demonstrate that the implemented quantum algorithm finds the solution much faster than by classical methodsDiego RistèMarcus P. da SilvaColm A. RyanAndrew W. CrossAntonio D. CórcolesJohn A. SmolinJay M. GambettaJerry M. ChowBlake R. JohnsonNature PortfolioarticlePhysicsQC1-999Electronic computers. Computer scienceQA75.5-76.95ENnpj Quantum Information, Vol 3, Iss 1, Pp 1-5 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95 Diego Ristè Marcus P. da Silva Colm A. Ryan Andrew W. Cross Antonio D. Córcoles John A. Smolin Jay M. Gambetta Jerry M. Chow Blake R. Johnson Demonstration of quantum advantage in machine learning
description	Large advantage in small quantum computers Quantum computing promises to revolutionize all fields of science by solving problems that are too complex for conventional computers. However, the realization of a full-fledged, universal quantum computer is still far ahead, requiring millions of quantum bits and very low error rates. Despite this, D. Ristè and colleagues at Raytheon BBN Technologies, with collaborators at IBM, have demonstrated that a quantum advantage already appears with only a few quantum bits and a highly noisy system. The team solved a particular problem, known as learning parity with noise, using a five-qubit superconducting quantum processor. Counting the number of times that the processor runs, they demonstrate that the implemented quantum algorithm finds the solution much faster than by classical methods
format	article
author	Diego Ristè Marcus P. da Silva Colm A. Ryan Andrew W. Cross Antonio D. Córcoles John A. Smolin Jay M. Gambetta Jerry M. Chow Blake R. Johnson
author_facet	Diego Ristè Marcus P. da Silva Colm A. Ryan Andrew W. Cross Antonio D. Córcoles John A. Smolin Jay M. Gambetta Jerry M. Chow Blake R. Johnson
author_sort	Diego Ristè
title	Demonstration of quantum advantage in machine learning
title_short	Demonstration of quantum advantage in machine learning
title_full	Demonstration of quantum advantage in machine learning
title_fullStr	Demonstration of quantum advantage in machine learning
title_full_unstemmed	Demonstration of quantum advantage in machine learning
title_sort	demonstration of quantum advantage in machine learning
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/b5566ab8f0a84a03ad96e12cf550175d
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Demonstration of quantum advantage in machine learning

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