Scalable Full-Stack Benchmarks for Quantum Computers
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 a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Transactions on Quantum Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10538040/ |
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| Summary: | 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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| ISSN: | 2689-1808 |