Quantum Science and Technology · 2023 · 22 citations · 24 references
ComputingComputer SciencePhysicsParallel ComputingQuantum ComputingQuantum MechanicsHardware AccelerationParallel ArchitecturesParallel Performance AnalysisQuantum CircuitsQuantum ComputationQuantum Hardware ArchitecturesEnergy Landscape AnalysisError MitigationHubbard ModelQuantum Error MitigationVariational Quantum AlgorithmsVariational Quantum CircuitsVariational Quantum Simulation
Abstract Quantum computers are getting larger and larger, but device fidelities may not be able to keep up with the increase in qubit numbers. One way to make use of a large device that has a limited gate depth is to run many small circuits simultaneously. In this paper we detail our investigations into running circuits in parallel on the Rigetti Aspen-M-1 device. We run two-qubit circuits in parallel to solve a simple instance of the Hubbard model using the variational quantum eigensolver (VQE). We present results for running up to 33 circuits in parallel (66 qubits), showing that with the use of error mitigation techniques it is possible to make use of, and gain a real-time speedup from, parallelisation on current quantum hardware. We obtain a speedup by 18× for exploring the VQE energy landscape, and by more than 8× for running VQE optimisation.
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Correlated electrons in high-temperature superconductors
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Natural Sciences, Chemistry, Physics +14
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