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dc.contributor.authorKyriienko, O
dc.date.accessioned2020-01-23T14:24:10Z
dc.date.issued2020-01-17
dc.description.abstractWe propose a quantum inverse iteration algorithm which can be used to estimate the ground state properties of a programmable quantum device. The method relies on the inverse power iteration technique, where the sequential application of the Hamiltonian inverse to an initial state prepares an approximate groundstate. To apply the inverse Hamiltonian operation, we write it as a sum of unitary evolution operators using the Fourier approximation approach. This allows to reformulate the protocol as separate measurements for the overlap of initial and propagated wavefunction. The algorithm thus crucially depends on the ability to run Hamiltonian dynamics with an available quantum device. We benchmark the performance using paradigmatic examples of quantum chemistry, corresponding to molecular hydrogen and beryllium hydride. Finally, we show its use for studying the ground state properties of relevant material science models which can be simulated with existing devices, considering an example of the Bose-Hubbard atomic simulator.en_GB
dc.identifier.citationVol. 6, article 7en_GB
dc.identifier.doi10.1038/s41534-019-0239-7
dc.identifier.urihttp://hdl.handle.net/10871/40549
dc.language.isoenen_GB
dc.publisherNature Researchen_GB
dc.rights© The Author(s) 2020. 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/.en_GB
dc.titleQuantum inverse iteration algorithm for programmable quantum simulatorsen_GB
dc.typeArticleen_GB
dc.date.available2020-01-23T14:24:10Z
dc.descriptionThis is the final version. Available on open access from Nature Research via the DOI in this recorden_GB
dc.descriptionData availability: The author declares that the data supporting the findings of this study are available within the paper and its supplementary information file.en_GB
dc.identifier.eissn2056-6387
dc.identifier.journalnpj Quantum Informationen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-12-20
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-01-17
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-01-23T14:22:16Z
refterms.versionFCDVoR
refterms.dateFOA2020-01-23T14:24:24Z
refterms.panelBen_GB


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© The Author(s) 2020. 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/.
Except where otherwise noted, this item's licence is described as © The Author(s) 2020. 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/.