000904648 001__ 904648
000904648 005__ 20230123101913.0
000904648 0247_ $$2arXiv$$aarXiv:2104.07687
000904648 0247_ $$2Handle$$a2128/30735
000904648 0247_ $$2altmetric$$aaltmetric:104212561
000904648 037__ $$aFZJ-2021-06217
000904648 1001_ $$0P:(DE-Juel1)178646$$aMüller, Matthias$$b0$$eCorresponding author$$ufzj
000904648 245__ $$aOne decade of quantum optimal control in the chopped random basis
000904648 260__ $$c2021
000904648 3367_ $$0PUB:(DE-HGF)25$$2PUB:(DE-HGF)$$aPreprint$$bpreprint$$mpreprint$$s1645168491_1343
000904648 3367_ $$2ORCID$$aWORKING_PAPER
000904648 3367_ $$028$$2EndNote$$aElectronic Article
000904648 3367_ $$2DRIVER$$apreprint
000904648 3367_ $$2BibTeX$$aARTICLE
000904648 3367_ $$2DataCite$$aOutput Types/Working Paper
000904648 520__ $$aThe Chopped RAndom Basis (CRAB) ansatz for quantum optimal control has been proven to be a versatile tool to enable quantum technology applications, quantum computing, quantum simulation, quantum sensing, and quantum communication. Its capability to encompass experimental constraints -- while maintaining an access to the usually trap-free control landscape -- and to switch from open-loop to closed-loop optimization (including with remote access -- or RedCRAB) is contributing to the development of quantum technology on many different physical platforms. In this review article we present the development, the theoretical basis and the toolbox for this optimization algorithm, as well as an overview of the broad range of different theoretical and experimental applications that exploit this powerful technique.
000904648 536__ $$0G:(DE-HGF)POF4-5221$$a5221 - Advanced Solid-State Qubits and Qubit Systems (POF4-522)$$cPOF4-522$$fPOF IV$$x0
000904648 588__ $$aDataset connected to arXivarXiv
000904648 7001_ $$0P:(DE-HGF)0$$aSaid, Ressa S.$$b1
000904648 7001_ $$0P:(DE-HGF)0$$aJelezko, Fedor$$b2
000904648 7001_ $$0P:(DE-Juel1)176280$$aCalarco, Tommaso$$b3$$ufzj
000904648 7001_ $$0P:(DE-Juel1)187073$$aMontangero, Simone$$b4
000904648 8564_ $$uhttps://juser.fz-juelich.de/record/904648/files/2104.07687.pdf$$yOpenAccess
000904648 909CO $$ooai:juser.fz-juelich.de:904648$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000904648 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178646$$aForschungszentrum Jülich$$b0$$kFZJ
000904648 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176280$$aForschungszentrum Jülich$$b3$$kFZJ
000904648 9131_ $$0G:(DE-HGF)POF4-522$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5221$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vQuantum Computing$$x0
000904648 9141_ $$y2022
000904648 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000904648 9201_ $$0I:(DE-Juel1)PGI-8-20190808$$kPGI-8$$lQuantum Control$$x0
000904648 9801_ $$aFullTexts
000904648 980__ $$apreprint
000904648 980__ $$aVDB
000904648 980__ $$aUNRESTRICTED
000904648 980__ $$aI:(DE-Juel1)PGI-8-20190808