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000916765 005__ 20250401102815.0
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000916765 037__ $$aFZJ-2023-00089
000916765 041__ $$aEnglish
000916765 1001_ $$0P:(DE-Juel1)167543$$aWillsch, Madita$$b0$$eCorresponding author$$ufzj
000916765 1112_ $$aML4Q Conference$$cOberlahr$$d2022-08-31 - 2022-09-02$$wGermany
000916765 245__ $$aSimulating Quantum Computers on Supercomputers
000916765 260__ $$c2022
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000916765 520__ $$aSimulating quantum systems is a hard computational problem as resource requirements grow exponentially with the system size. The simulation of quantum computers is important for benchmarks of real quantum computing hardware as well as for studies of quantum algorithms for which currently available quantum computing hardware is still too small or too error-prone to test the performance and/or scalability reliably. By using efficient, GPU-accelerated simulation software suitable for distributed memory architectures, we can simulate a quantum computer with up to 42 qubits using the supercomputer JUWELS Booster located at Forschungszentrum Jülich. Our Jülich Universal Quantum Computer Simulator (JUQCS) emulates an (ideal) gate-based quantum computer where each gate is implemented as an "instantaneous'" update of the state vector. Optionally, a depolarizing channel can be emulated by random insertion of Pauli X, Y and Z errors in the execution of the algorithm. Our JUelich Quantum Annealing Simulator (JUQAS) emulates a quantum annealer operating at zero temperature by solving the time-dependent Schrödinger equation via time stepping. A quantum annealer (or adiabatic quantum computer) theoretically solves an optimization problem by adiabatic evolution from the known ground state of an initial Hamiltonian to the ground state of a final Hamiltonian which encodes the optimization problem, i.e., the final ground state encodes the solution to the problem. In practice, however, the evolution is not always adiabatic and what happens instead can only be determined numerically except for very few simple, special cases like the Landau-Zener transition of a single spin in a time-dependent external magnetic field. We outline some of the most important steps required for the implementation of large-scale quantum computer simulations and report on some benchmarks as well as applications using JUQCS and JUQAS.
000916765 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
000916765 536__ $$0G:(DE-Juel-1)aidas_20200731$$aAIDAS - Joint Virtual Laboratory for AI, Data Analytics and Scalable Simulation (aidas_20200731)$$caidas_20200731$$x1
000916765 7001_ $$0P:(DE-Juel1)167542$$aWillsch, Dennis$$b1$$ufzj
000916765 7001_ $$0P:(DE-Juel1)144355$$aJin, Fengping$$b2$$ufzj
000916765 7001_ $$0P:(DE-Juel1)179169$$aDe Raedt, Hans$$b3$$ufzj
000916765 7001_ $$0P:(DE-Juel1)138295$$aMichielsen, Kristel$$b4$$ufzj
000916765 8564_ $$uhttps://juser.fz-juelich.de/record/916765/files/ML4Q_poster.pdf$$yOpenAccess
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000916765 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138295$$aForschungszentrum Jülich$$b4$$kFZJ
000916765 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$$x0
000916765 9141_ $$y2022
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