Self-guided quantum tomography

Ferrie, C

Self-guided quantum tomography

Ferrie, C

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Publication Type:: Journal Article
Citation:: Physical Review Letters, 2014, 113 (19)
Issue Date:: 2014-11-07

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Field	Value	Language
dc.contributor.author	Ferrie, C https://orcid.org/0000-0003-2736-9943	en_US
dc.date.issued	2014-11-07	en_US
dc.identifier.citation	Physical Review Letters, 2014, 113 (19)	en_US
dc.identifier.issn	0031-9007	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118948
dc.description.abstract	© 2014 American Physical Society. We introduce a self-learning tomographic technique in which the experiment guides itself to an estimate of its own state. Self-guided quantum tomography uses measurements to directly test hypotheses in an iterative algorithm which converges to the true state. We demonstrate through simulation on many qubits that Self-guided quantum tomography is a more efficient and robust alternative to the usual paradigm of taking a large amount of informationally complete data and solving the inverse problem of postprocessed state estimation.	en_US
dc.relation.ispartof	Physical Review Letters	en_US
dc.relation.isbasedon	10.1103/PhysRevLett.113.190404	en_US
dc.subject.classification	General Physics	en_US
dc.title	Self-guided quantum tomography	en_US
dc.type	Journal Article
utslib.citation.volume	19	en_US
utslib.citation.volume	113	en_US
utslib.for	0206 Quantum Physics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	02 Physical Sciences	en_US
utslib.for	09 Engineering	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	19	en_US
pubs.publication-status	Published	en_US
pubs.volume	113	en_US

Abstract:

© 2014 American Physical Society. We introduce a self-learning tomographic technique in which the experiment guides itself to an estimate of its own state. Self-guided quantum tomography uses measurements to directly test hypotheses in an iterative algorithm which converges to the true state. We demonstrate through simulation on many qubits that Self-guided quantum tomography is a more efficient and robust alternative to the usual paradigm of taking a large amount of informationally complete data and solving the inverse problem of postprocessed state estimation.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/118948