research-article

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

Authors:
Ang Li

Pacific Northwest National Laboratory, Richland, USA

Pacific Northwest National Laboratory, Richland, USA

0000-0003-3734-9137
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,
Samuel Stein

Pacific Northwest National Laboratory, Richland, USA

Pacific Northwest National Laboratory, Richland, USA

0000-0002-2655-8251
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,
Sriram Krishnamoorthy

Pacific Northwest National Laboratory, Richland, USA

Pacific Northwest National Laboratory, Richland, USA

0000-0002-8228-8890
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,
James Ang

Pacific Northwest National Laboratory, Richland, USA

Pacific Northwest National Laboratory, Richland, USA

0000-0002-7373-1889
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Authors Info & Claims

ACM Transactions on Quantum Computing Volume 4 Issue 2Article No.: 10pp 1–26https://doi.org/10.1145/3550488

Published:24 February 2023Publication History

ACM Transactions on Quantum Computing

Abstract

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. We also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system. QASMBench is released at: http://github.com/pnnl/QASMBench.

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QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

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Published in
ACM Transactions on Quantum Computing Volume 4, Issue 2
June 2023
192 pages
EISSN:2643-6817
DOI:10.1145/3584867
Editors:
Travis S. Humble
Oak Ridge National Laboratory, USA
,
Mingsheng Ying
University of Technology Sydney, Australia
Issue’s Table of Contents
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.
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Association for Computing Machinery
New York, NY, United States
Publication History
- Published: 24 February 2023
- Online AM: 30 July 2022
- Accepted: 10 July 2022
- Revised: 7 April 2022
- Received: 1 June 2021
Published in tqc Volume 4, Issue 2

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quantum metrics
NISQ
Qualifiers
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QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

ACM Transactions on Quantum Computing

Abstract

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Index Terms

Recommendations

Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices

An Algebraic Quantum Circuit Compression Algorithm for Hamiltonian Simulation

The NISQ Complexity of Collision Finding