000906575 001__ 906575
000906575 005__ 20230123101910.0
000906575 0247_ $$2Handle$$a2128/33372
000906575 037__ $$aFZJ-2022-01526
000906575 041__ $$aEnglish
000906575 1001_ $$0P:(DE-Juel1)176109$$aLagemann, Hannes$$b0$$eCorresponding author
000906575 1112_ $$aJülich Quantum Computing Seminar$$cOnline$$d2022-01-18 - 2022-01-18$$wGermany
000906575 245__ $$aReal-time simulations of the quantum approximate optimisation algorithm with a circuit Hamiltonian model$$f2022-01-18 - 
000906575 260__ $$c2022
000906575 3367_ $$033$$2EndNote$$aConference Paper
000906575 3367_ $$2DataCite$$aOther
000906575 3367_ $$2BibTeX$$aINPROCEEDINGS
000906575 3367_ $$2ORCID$$aLECTURE_SPEECH
000906575 3367_ $$0PUB:(DE-HGF)31$$2PUB:(DE-HGF)$$aTalk (non-conference)$$btalk$$mtalk$$s1672834731_22540$$xOther
000906575 3367_ $$2DINI$$aOther
000906575 520__ $$aThe 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.
000906575 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
000906575 536__ $$0G:(EU-Grant)820363$$aOpenSuperQ - An Open Superconducting Quantum Computer (820363)$$c820363$$fH2020-FETFLAG-2018-03$$x1
000906575 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x2
000906575 8564_ $$uhttps://juser.fz-juelich.de/record/906575/files/main.pdf$$yOpenAccess
000906575 909CO $$ooai:juser.fz-juelich.de:906575$$pec_fundedresources$$pdriver$$pVDB$$popen_access$$popenaire
000906575 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176109$$aForschungszentrum Jülich$$b0$$kFZJ
000906575 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
000906575 9141_ $$y2022
000906575 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000906575 920__ $$lyes
000906575 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000906575 9801_ $$aFullTexts
000906575 980__ $$atalk
000906575 980__ $$aVDB
000906575 980__ $$aUNRESTRICTED
000906575 980__ $$aI:(DE-Juel1)JSC-20090406