000865583 001__ 865583
000865583 005__ 20210130003059.0
000865583 037__ $$aFZJ-2019-04948
000865583 041__ $$aEnglish
000865583 1001_ $$0P:(DE-Juel1)176997$$aMehta, Vrinda$$b0$$ufzj
000865583 1112_ $$aFundamental aspects of statistical mechanics and the emergence of thermodynamics in non-equilbrium systems$$cDelmenhorst$$d2019-09-23 - 2019-09-26$$wGermany
000865583 245__ $$aQuantum annealing with anneal path control and catalyst Hamiltonian
000865583 260__ $$c2019
000865583 3367_ $$033$$2EndNote$$aConference Paper
000865583 3367_ $$2BibTeX$$aINPROCEEDINGS
000865583 3367_ $$2DRIVER$$aconferenceObject
000865583 3367_ $$2ORCID$$aCONFERENCE_POSTER
000865583 3367_ $$2DataCite$$aOutput Types/Conference Poster
000865583 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1571051878_13206$$xOther
000865583 520__ $$aQuantum annealing is a quantum version of classical simulated annealing, but using quantum fluctuations instead of thermal fluctuations, to explore the energy landscape of an optimization problem. This approach has received enormous interest in the last two decades, and is regarded as a second model of quantum computing, which is quite distinct to the gate-based model.The standard form of quantum annealer, such as the one that D-Wave Systems Inc. uses, can be described by a transverse-field Ising model. This type of quantum annealer is designed for solving quadratic unconstrained binary optimization problems. While researches on the universality and hypothetical quantum speed up for this type of quantum annealer are still ongoing, here we investigate two different variations of qantum annealer, namely, adding anneal path control and catalyst Hamiltonian to the standard form, respectively.
000865583 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000865583 7001_ $$0P:(DE-Juel1)144355$$aJin, Fengping$$b1$$eCorresponding author$$ufzj
000865583 7001_ $$0P:(DE-HGF)0$$aDe Raedt, Hans$$b2
000865583 7001_ $$0P:(DE-Juel1)138295$$aMichielsen, Kristel$$b3$$ufzj
000865583 909CO $$ooai:juser.fz-juelich.de:865583$$pVDB
000865583 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176997$$aForschungszentrum Jülich$$b0$$kFZJ
000865583 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144355$$aForschungszentrum Jülich$$b1$$kFZJ
000865583 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138295$$aForschungszentrum Jülich$$b3$$kFZJ
000865583 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0
000865583 9141_ $$y2019
000865583 920__ $$lyes
000865583 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000865583 980__ $$aposter
000865583 980__ $$aVDB
000865583 980__ $$aI:(DE-Juel1)JSC-20090406
000865583 980__ $$aUNRESTRICTED