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001033654 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-06526
001033654 037__ $$aFZJ-2024-06526
001033654 041__ $$aEnglish
001033654 1001_ $$0P:(DE-Juel1)191568$$aVyas, Kunal$$b0$$eCorresponding author
001033654 1112_ $$aAdiabatic Quantum Computing 2024$$cGlasgow$$d2024-06-10 - 2024-06-14$$gAQC 2024$$wUK
001033654 245__ $$aInvestigating scaling properties for quantum annealing to solve the Fermi-Hubbard model using the kinetic energy part as the driving Hamiltonian
001033654 260__ $$c2024
001033654 3367_ $$033$$2EndNote$$aConference Paper
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001033654 502__ $$cRWTH Aachen
001033654 520__ $$aQuantum annealing can help in finding the ground state of Hamiltonians describing many body systems. One such Hamiltonian is the Fermi-Hubbard Hamiltonian. We investigate the scaling complexity for the quantum annealing process carried out using the kinetic energy part of the Hubbard model as driving Hamiltonian for ground state calculations. The way we do this is by studying the gaps between the ground state and the 1st relevant excited state that participates in the diabatic evolution for a 1-dimensional system. The behavior of these gaps with increasing system size could hint at polynomial scaling of required annealing time for finding the ground state of the Hubbard Hamiltonian. We also try to extend this idea to a Hubbard model ladder to learn more about the scaling behavior of gaps relevant to adiabatic evolution. Further, we discuss about initial state preparation for the quantum annealing strategy under study. Information on the complexity coupled with an efficient way of preparing the initial state could bolster our hopes for using adiabatic quantum computation for solving correlated many-body Hamiltonians.
001033654 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001033654 536__ $$0G:(GEPRIS)355031190$$aDFG project G:(GEPRIS)355031190 - FOR 2692: Fundamental Aspects of Statistical Mechanics and the Emergence of Thermodynamics in Non-Equilibrium Systems (355031190)$$c355031190$$x1
001033654 7001_ $$0P:(DE-Juel1)144355$$aJin, Fengping$$b1$$ufzj
001033654 7001_ $$0P:(DE-Juel1)138295$$aMichielsen, Kristel$$b2$$ufzj
001033654 8564_ $$uhttps://juser.fz-juelich.de/record/1033654/files/aqc_talk.pdf$$yOpenAccess
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001033654 9131_ $$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
001033654 9141_ $$y2024
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