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@INPROCEEDINGS{Willsch:916765,
      author       = {Willsch, Madita and Willsch, Dennis and Jin, Fengping and
                      De Raedt, Hans and Michielsen, Kristel},
      title        = {{S}imulating {Q}uantum {C}omputers on {S}upercomputers},
      reportid     = {FZJ-2023-00089},
      year         = {2022},
      abstract     = {Simulating 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.},
      month         = {Aug},
      date          = {2022-08-31},
      organization  = {ML4Q Conference, Oberlahr (Germany),
                       31 Aug 2022 - 2 Sep 2022},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / AIDAS - Joint
                      Virtual Laboratory for AI, Data Analytics and Scalable
                      Simulation $(aidas_20200731)$},
      pid          = {G:(DE-HGF)POF4-5111 / $G:(DE-Juel-1)aidas_20200731$},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/916765},
}