论文标题
QASMBENCH：用于NISQ评估和模拟的低级QASM基准套件
QASMBench: A Low-level QASM Benchmark Suite for NISQ Evaluation and Simulation
论文作者
论文摘要
NISQ时代量子计算（QC）的快速开发急需的基准套件和有见地的评估指标，以表征原型NISQ设备的性能，QC编程编译器的效率，调度程序和组件的效率，调度程序和组件的效率，以及在经典计算机计算机计算机中的量子系统模拟器的能力。在这项工作中，我们通过提出一个基于OpenQASM组装表示的低级，易于使用的基准套件来填补这一空白。它巩固了从化学，模拟，线性代数，搜索，优化，算术，机器学习，容错，密码学等的各种领域的常用量子例程和内核，包括通用性和可用性之间的交易。为了通过NISQ设备执行分析这些内核，除了电路宽度和深度外，我们提出了四个电路指标，包括门密度，保留寿命，测量密度和纠缠差异，以提取有关执行效率，对NISQ误差的敏感性以及机器特定优化的潜在增益的更多见解。可以在包括IBM-Q，Rigetti，Ionq和Quantinuum在内的多个NISQ平台上启动和验证QASMBENCH中的应用。为了进行评估，我们通过密度矩阵状态断层扫描量表衡量了12台IBM-Q机上QASMBENCH应用程序子集的执行保真度，该密度矩阵状态层析成像包括25K电路评估。我们还比较了IBM-Q机器，IONQ QPU和Rigetti Aspen M-1系统之间执行的保真度。 QASMBENCH的发布：http：//github.com/pnnl/qasmbench。
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, etc., 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, which comprises 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.
