Measuring the capabilities of quantum computers

Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure c...

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Published in:	Nature physics Vol. 18; no. 1; pp. 75 - 79
Main Authors:	Proctor, Timothy, Rudinger, Kenneth, Young, Kevin, Nielsen, Erik, Blume-Kohout, Robin
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 01.01.2022 Nature Publishing Group Nature Publishing Group (NPG)
Subjects:	639/705/1042 639/766/259 639/766/483 Algorithms Atomic Benchmarks Circuits Classical and Continuum Physics Complex Systems Computational science Condensed Matter Physics Hardware Information theory and computation Mathematical and Computational Physics MATHEMATICS AND COMPUTING Microprocessors Molecular Optical and Plasma Physics Physics Physics and Astronomy Processors Quantum computers Quantum computing Quantum physics Qubits (quantum computing) Standard error Theoretical
ISSN:	1745-2473, 1745-2481
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Abstract	Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. We show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we construct two flexible, scalable volumetric benchmarks based on randomized and periodically ordered programs. We use these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today’s hardware, and that current processors vary widely in their sensitivity to program structure. Evaluations of quantum computers across architectures need reliable benchmarks. A class of benchmarks that can directly reflect the structure of any algorithm shows that different quantum computers have considerable variations in performance.
AbstractList	Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. We show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we construct two flexible, scalable volumetric benchmarks based on randomized and periodically ordered programs. We use these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today’s hardware, and that current processors vary widely in their sensitivity to program structure. Evaluations of quantum computers across architectures need reliable benchmarks. A class of benchmarks that can directly reflect the structure of any algorithm shows that different quantum computers have considerable variations in performance. Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. We show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we construct two flexible, scalable volumetric benchmarks based on randomized and periodically ordered programs. We use these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today’s hardware, and that current processors vary widely in their sensitivity to program structure. Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. We show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we construct two flexible, scalable volumetric benchmarks based on randomized and periodically ordered programs. We use these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today’s hardware, and that current processors vary widely in their sensitivity to program structure.Evaluations of quantum computers across architectures need reliable benchmarks. A class of benchmarks that can directly reflect the structure of any algorithm shows that different quantum computers have considerable variations in performance.
Author	Rudinger, Kenneth Blume-Kohout, Robin Proctor, Timothy Young, Kevin Nielsen, Erik
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Snippet	Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware...
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SubjectTerms	639/705/1042 639/766/259 639/766/483 Algorithms Atomic Benchmarks Circuits Classical and Continuum Physics Complex Systems Computational science Condensed Matter Physics Hardware Information theory and computation Mathematical and Computational Physics MATHEMATICS AND COMPUTING Microprocessors Molecular Optical and Plasma Physics Physics Physics and Astronomy Processors Quantum computers Quantum computing Quantum physics Qubits (quantum computing) Standard error Theoretical
Title	Measuring the capabilities of quantum computers
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