001     908454
005     20230404095008.0
024 7 _ |a 10.3389/fphy.2022.907160
|2 doi
024 7 _ |a 2128/31432
|2 Handle
024 7 _ |a altmetric:129845206
|2 altmetric
024 7 _ |a WOS:000819201900001
|2 WOS
037 _ _ |a FZJ-2022-02613
082 _ _ |a 530
100 1 _ |a Jattana, Manpreet Singh
|0 P:(DE-Juel1)174485
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Assessment of the Variational Quantum Eigensolver: Application to the Heisenberg Model
260 _ _ |a Lausanne
|c 2022
|b Frontiers Media
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1657097052_11497
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a massively parallel universal quantum computer simulator, we observe that a low-depth-circuit ansatz advantageously exploits the efficiently preparable Néel initial state, avoids potential barren plateaus, and works for both one- and two-dimensional lattices. The analysis reflects the decisive ingredients required for a simulation by comparing different ansätze, initial parameters, and gradient-based versus gradient-free optimizers. Extrapolation to the thermodynamic limit accurately yields the analytical value for the ground state energy, given by the Bethe ansatz. We predict that a fully functional quantum computer with 100 qubits can calculate the ground state energy with a relatively small error.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 0
536 _ _ |a OpenSuperQ - An Open Superconducting Quantum Computer (820363)
|0 G:(EU-Grant)820363
|c 820363
|f H2020-FETFLAG-2018-03
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Jin, Fengping
|0 P:(DE-Juel1)144355
|b 1
|u fzj
700 1 _ |a De Raedt, Hans
|0 P:(DE-Juel1)179169
|b 2
|u fzj
700 1 _ |a Michielsen, Kristel
|0 P:(DE-Juel1)138295
|b 3
|u fzj
773 _ _ |a 10.3389/fphy.2022.907160
|g Vol. 10, p. 907160
|0 PERI:(DE-600)2721033-9
|p 907160
|t Frontiers in physics
|v 10
|y 2022
|x 2296-424X
856 4 _ |u https://juser.fz-juelich.de/record/908454/files/fphy-10-907160.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:908454
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p ec_fundedresources
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)174485
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)144355
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)179169
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)138295
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 0
914 1 _ |y 2022
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-02-03
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-02-03
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2021-02-03
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2021-02-03
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b FRONT PHYS-LAUSANNE : 2021
|d 2022-11-15
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-15
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-15
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2021-05-12T10:34:55Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2021-05-12T10:34:55Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2021-05-12T10:34:55Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-15
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-15
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2022-11-15
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2022-11-15
915 p c |a Local Funding
|2 APC
|0 PC:(DE-HGF)0001
915 p c |a DFG OA Publikationskosten
|2 APC
|0 PC:(DE-HGF)0002
915 p c |a DOAJ Journal
|2 APC
|0 PC:(DE-HGF)0003
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a APC


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21