Scalable Full-Stack Benchmarks for Quantum Computers

Jordan Hines;Timothy Proctor
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引用次数: 0

Abstract

Quantum processors are now able to run quantum circuits that are infeasible to simulate classically, creating a need for benchmarks that assess a quantum processor's rate of errors when running these circuits. Here, we introduce a general technique for creating efficient benchmarks from any set of quantum computations, specified by unitary circuits. Our benchmarks assess the integrated performance of a quantum processor's classical compilation algorithms and its low-level quantum operations. Unlike existing “full-stack benchmarks,” our benchmarks do not require classical simulations of quantum circuits, and they use only efficient classical computations. We use our method to create random circuit benchmarks, including a computationally efficient version of the quantum volume benchmark, and an algorithm-based benchmark that uses Hamiltonian simulation circuits. We perform these benchmarks on IBM Q devices and in simulations, and we compare their results to the results of the existing benchmarking methods.
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量子计算机的可扩展全栈基准
量子处理器现在能够运行经典模拟不可行的量子电路,因此需要能评估量子处理器运行这些电路时出错率的基准。在这里,我们介绍了一种通用技术,用于从由单元电路指定的任何量子计算集合中创建高效基准。我们的基准可评估量子处理器的经典编译算法及其低级量子操作的综合性能。与现有的 "全栈基准 "不同,我们的基准不需要对量子电路进行经典模拟,而且只使用高效的经典计算。我们使用我们的方法创建随机电路基准,包括量子体积基准的高效计算版本,以及使用哈密尔顿模拟电路的基于算法的基准。我们在 IBM Q 设备和模拟中执行了这些基准,并将其结果与现有基准测试方法的结果进行了比较。
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