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dc.contributor.author
Barkoutsos, Panagiotis K.
dc.contributor.author
Gkritsis, Fotios
dc.contributor.author
Ollitrault, Pauline J.
dc.contributor.author
Sokolov, Igor O.
dc.contributor.author
Woerner, Stefan
dc.contributor.author
Tavernelli, Ivano
dc.date.accessioned
2021-04-13T11:15:13Z
dc.date.available
2021-04-10T14:15:58Z
dc.date.available
2021-04-13T11:15:13Z
dc.date.issued
2021-03-28
dc.identifier.issn
2041-6520
dc.identifier.issn
2041-6539
dc.identifier.other
10.1039/d0sc05718e
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/478094
dc.identifier.doi
10.3929/ethz-b-000478094
dc.description.abstract
The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules obtainable from a set of atomic species grow exponentially with the size of the system, limiting the efficiency of classical sampling algorithms. On the other hand, quantum computers can provide an efficient solution to the sampling of the chemical compound space for the optimization of a given molecular property. In this work, we propose a quantum algorithm for addressing the material design problem with a favourable scaling. The core of this approach is the representation of the space of candidate structures as a linear superposition of all possible atomic compositions. The corresponding ‘alchemical’ Hamiltonian drives the optimization in both the atomic and electronic spaces leading to the selection of the best fitting molecule, which optimizes a given property of the system, e.g., the interaction with an external potential as in drug design. The quantum advantage resides in the efficient calculation of the electronic structure properties together with the sampling of the exponentially large chemical compound space. We demonstrate both in simulations and with IBM Quantum hardware the efficiency of our scheme and highlight the results in a few test cases. This preliminary study can serve as a basis for the development of further material design quantum algorithms for near-term quantum computers.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Royal Society of Chemistry
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc/3.0/
dc.title
Quantum algorithm for alchemical optimization in material design
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 3.0 Unported
dc.date.published
2021-01-22
ethz.journal.title
Chemical Science
ethz.journal.volume
12
en_US
ethz.journal.issue
12
en_US
ethz.journal.abbreviated
Chem. Sci.
ethz.pages.start
4345
en_US
ethz.pages.end
4352
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Cambridge
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2021-04-10T14:16:26Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-04-13T11:15:23Z
ethz.rosetta.lastUpdated
2022-03-29T06:31:53Z
ethz.rosetta.versionExported
true
ethz.COinS
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