How Parallel Circuit Execution Can Be Useful for NISQ Computing?

• URL: http://arxiv.org/abs/2112.00387v1
• Date: Wed, 1 Dec 2021 10:12:35 GMT
• Title: How Parallel Circuit Execution Can Be Useful for NISQ Computing?
• Authors: Siyuan Niu, Aida Todri-Sanial
• Abstract summary: Quantum computing is performed on Noisy Intermediate-Scale Quantum (NISQ) hardware in the short term. Only small circuits can be executed reliably on a quantum machine due to the unavoidable noisy quantum operations on NISQ devices. A parallel circuit execution technique has been proposed to address this problem by executing multiple programs on hardware simultaneously.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum computing is performed on Noisy Intermediate-Scale Quantum (NISQ) hardware in the short term. Only small circuits can be executed reliably on a quantum machine due to the unavoidable noisy quantum operations on NISQ devices, leading to the under-utilization of hardware resources. With the growing demand to access quantum hardware, how to utilize it more efficiently while maintaining output fidelity is becoming a timely issue. A parallel circuit execution technique has been proposed to address this problem by executing multiple programs on hardware simultaneously. It can improve the hardware throughput and reduce the overall runtime. However, accumulative noises such as crosstalk can decrease the output fidelity in parallel workload execution. In this paper, we first give an in-depth overview of stateof-the-art parallel circuit execution methods. Second, we propose a Quantum Crosstalk-aware Parallel workload execution method (QuCP) without the overhead of crosstalk characterization. Third, we investigate the trade-off between hardware throughput and fidelity loss to explore the hardware limitation with parallel circuit execution. Finally, we apply parallel circuit execution to VQE and zero-noise extrapolation error mitigation method to showcase its various applications on advancing NISQ computing.

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