Poster (Other) FZJ-2023-00089

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Simulating Quantum Computers on Supercomputers

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2022

ML4Q Conference, OberlahrOberlahr, Germany, 31 Aug 2022 - 2 Sep 20222022-08-312022-09-02

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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.


Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
  2. AIDAS - Joint Virtual Laboratory for AI, Data Analytics and Scalable Simulation (aidas_20200731) (aidas_20200731)

Appears in the scientific report 2022
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 Record created 2023-01-04, last modified 2025-04-01


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