Demonstration of topological data analysis on a quantum processor

Huang, HL; Wang, XL; Rohde, PP; Luo, YH; Zhao, YW; Liu, C; Li, L; Liu, NL; Lu, CY; Pan, JW

Demonstration of topological data analysis on a quantum processor

Huang, HL Wang, XL Rohde, PP

Luo, YH Zhao, YW Liu, C Li, L Liu, NL Lu, CY Pan, JW

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Publication Type:: Journal Article
Citation:: Optica, 2018, 5 (2), pp. 193 - 198
Issue Date:: 2018-02-20

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Field	Value	Language
dc.contributor.author	Huang, HL	en_US
dc.contributor.author	Wang, XL	en_US
dc.contributor.author	Rohde, PP https://orcid.org/0000-0002-5814-7289	en_US
dc.contributor.author	Luo, YH	en_US
dc.contributor.author	Zhao, YW	en_US
dc.contributor.author	Liu, C	en_US
dc.contributor.author	Li, L	en_US
dc.contributor.author	Liu, NL	en_US
dc.contributor.author	Lu, CY	en_US
dc.contributor.author	Pan, JW	en_US
dc.date.issued	2018-02-20	en_US
dc.identifier.citation	Optica, 2018, 5 (2), pp. 193 - 198	en_US
dc.identifier.issn	2334-2536	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131377
dc.description.abstract	© 2018 Optical Society of America. Topological data analysis offers a robust way to extract useful information from noisy, unstructured data by identifying its underlying structure. Recently, an efficient quantum algorithm was proposed [Nat. Commun. 7, 10138 (2016)] for calculating Betti numbers of data points—topological features that count the number of topological holes of various dimensions in a scatterplot. Here, we implement a proof-of-principle demonstration of this quantum algorithm by employing a six-photon quantum processor to successfully analyze the topological features of Betti numbers of a network including three data points, providing new insights into data analysis in the era of quantum computing.	en_US
dc.relation	http://purl.org/au-research/grants/arc/FT160100397
dc.relation.ispartof	Optica	en_US
dc.relation.isbasedon	10.1364/OPTICA.5.000193	en_US
dc.rights	© 2018 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.	en_US
dc.title	Demonstration of topological data analysis on a quantum processor	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	5	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0205 Optical Physics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	5	en_US

Abstract:

© 2018 Optical Society of America. Topological data analysis offers a robust way to extract useful information from noisy, unstructured data by identifying its underlying structure. Recently, an efficient quantum algorithm was proposed [Nat. Commun. 7, 10138 (2016)] for calculating Betti numbers of data points—topological features that count the number of topological holes of various dimensions in a scatterplot. Here, we implement a proof-of-principle demonstration of this quantum algorithm by employing a six-photon quantum processor to successfully analyze the topological features of Betti numbers of a network including three data points, providing new insights into data analysis in the era of quantum computing.

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http://hdl.handle.net/10453/131377