001     906575
005     20230123101910.0
024 7 _ |a 2128/33372
|2 Handle
037 _ _ |a FZJ-2022-01526
041 _ _ |a English
100 1 _ |a Lagemann, Hannes
|0 P:(DE-Juel1)176109
|b 0
|e Corresponding author
111 2 _ |a Jülich Quantum Computing Seminar
|c Online
|d 2022-01-18 - 2022-01-18
|w Germany
245 _ _ |a Real-time simulations of the quantum approximate optimisation algorithm with a circuit Hamiltonian model
|f 2022-01-18 -
260 _ _ |c 2022
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a Other
|2 DataCite
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a LECTURE_SPEECH
|2 ORCID
336 7 _ |a Talk (non-conference)
|b talk
|m talk
|0 PUB:(DE-HGF)31
|s 1672834731_22540
|2 PUB:(DE-HGF)
|x Other
336 7 _ |a Other
|2 DINI
520 _ _ |a The quantum approximate optimisation algorithm (or QAOA) is a variational algorithm. The algorithm consists of two parts. A quantum step which evaluates a cost function and a classical step which performs the optimisation. The hope is that the classical optimisation step can mitigate errors which appear in state-of-the-art quantum processors.We investigate this idea by simulating the time evolution of superconducting quantum processors with two and three qubits. The model which generates the dynamics of the system is a lumped-element circuit Hamiltonian model. We find that in this model the classical optimisation step can mitigate some of the gate errors which are caused by imperfect two-qubit gates.
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
536 _ _ |a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)
|0 G:(DE-Juel1)PHD-NO-GRANT-20170405
|c PHD-NO-GRANT-20170405
|x 2
856 4 _ |u https://juser.fz-juelich.de/record/906575/files/main.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:906575
|p openaire
|p open_access
|p VDB
|p driver
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910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)176109
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 OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
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 talk
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406


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