Built on

J. Emerson, R. Alicki, and K. Życzkowski, Scalable noise estimation with random unitary operators, Journal of Optics B: Quantum and Semiclassical Optics 7
2005
Earlier work this paper cites.
L. H. Pedersen, N. M. Møller, and K. Mølmer, Fidelity of quantum operations, Physics Letters A 367
2007
Earlier work this paper cites.
E. Magesan, J. M. Gambetta, and J. Emerson, Characterizing quantum gates via randomized benchmarking, Phys. Rev. A 85
2012
Earlier work this paper cites.
J. M. Gambetta, A. D. Córcoles, S. T. Merkel, B. R. Johnson, J. A. Smolin, J. M. Chow, C. A. Ryan, C. Rigetti, S. Poletto, T. A. Ohki, M. B. Ketchen, and M. Steffen, Characterization of addressability by simultaneous randomized benchmarking, Phys. Rev. Lett. 109
2012
Earlier work this paper cites.
S. Kimmel, M. P. da Silva, C. A. Ryan, B. R. Johnson, and T. Ohki, Robust extraction of tomographic information via randomized benchmarking, Phys. Rev. X 4
2014
Earlier work this paper cites.
D. Greenbaum, Introduction to quantum gate set tomography (2015), arXiv:1509.02921 [quant-ph]
Original
2015
Earlier work this paper cites.
S. Boixo, S. V. Isakov, V. N. Smelyanskiy, R. Babbush, N. Ding, Z. Jiang, M. J. Bremner, J. M. Martinis, and H. Neven, Characterizing quantum supremacy in near-term devices, Nature Physics 14
2018
Earlier work this paper cites.
A. W. Cross, L. S. Bishop, S. Sheldon, P. D. Nation, and J. M. Gambetta, Validating quantum computers using randomized model circuits, Physical Review A 100
2019
Earlier work this paper cites.
T. J. Proctor, A. Carignan-Dugas, K. Rudinger, E. Nielsen, R. Blume-Kohout, and K. Young, Direct randomized benchmarking for multiqubit devices, Phys. Rev. Lett. 123
2019
Earlier work this paper cites.
A. Erhard, J. J. Wallman, L. Postler, M. Meth, R. Stricker, E. A. Martinez, P. Schindler, T. Monz, J. Emerson, and R. Blatt, Characterizing large-scale quantum computers via cycle benchmarking, Nat. Comm. 10
2019
Earlier work this paper cites.
J. Helsen, X. Xue, L. M. K. Vandersypen, and S. Wehner, A new class of efficient randomized benchmarking protocols, npj Quantum Inf 5
2019
Earlier work this paper cites.
P. Murali, J. M. Baker, A. Javadi-Abhari, F. T. Chong, and M. Martonosi, Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers, in Proceedings of the twenty-fourth international conference on architectural support for programming languages and operating systems (2019) pp. 1015–1029
2019
Earlier work this paper cites.
D. C. McKay, A. W. Cross, C. J. Wood, and J. M. Gambetta, Correlated randomized benchmarking (2020)
2020
Earlier work this paper cites.
R. Harper, S. Flammia, and J. Wallman, Efficient learning of quantum noise, Nat. Phys. 16
2020
Earlier work this paper cites.
A. Wack, H. Paik, A. Javadi-Abhari, P. Jurcevic, I. Faro, J. M. Gambetta, and B. R. Johnson, Quality, speed, and scale: three key attributes to measure the performance of near-term quantum computers, arXiv preprint arXiv:2110.14108 (2021)
Original
2021
Earlier work this paper cites.

Similar

T. Lubinski, S. Johri, P. Varosy, J. Coleman, L. Zhao, J. Necaise, C. H. Baldwin, K. Mayer, and T. Proctor, Application-oriented performance benchmarks for quantum computing, arXiv preprint arXiv:2110.03137 (2021)
Original
2021
Cited alongside, same era.
K. Mesman, Z. Al-Ars, and M. Möller, Qpack: Quantum approximate optimization algorithms as universal benchmark for quantum computers, arXiv preprint arXiv:2103.17193 (2021)
Original
2021
Cited alongside, same era.
B. K. Mitchell, R. K. Naik, A. Morvan, A. Hashim, J. M. Kreikebaum, B. Marinelli, W. Lavrijsen, K. Nowrouzi, D. I. Santiago, and I. Siddiqi, Hardware-efficient microwave-activated tunable coupling between superconducting qubits, Phys. Rev. Lett. 127
2021
Cited alongside, same era.
E. v. d. Berg, Z. K. Minev, A. Kandala, and K. Temme, Probabilistic error cancellation with sparse pauli-lindblad models on noisy quantum processors, arXiv preprint arXiv:2201.09866 (2022)
Original
2022
Cited alongside, same era.

Then

S. Ferracin, A. Hashim, J.-L. Ville, R. Naik, A. Carignan-Dugas, H. Qassim, A. Morvan, D. I. Santiago, I. Siddiqi, and J. J. Wallman, Efficiently improving the performance of noisy quantum computers (2022), arXiv:2201.10672 [quant-ph]
Original
2022
Later among the works it cites.
P. D. Nation and M. Treinish, Suppressing quantum circuit errors due to system variability, arXiv preprint arXiv:2209.15512 (2022)
Original
2022
Later among the works it cites.
K. X. Wei, E. Magesan, I. Lauer, S. Srinivasan, D. F. Bogorin, S. Carnevale, G. A. Keefe, Y. Kim, D. Klaus, W. Landers, N. Sundaresan, C. Wang, E. J. Zhang, M. Steffen, O. E. Dial, D. C. McKay, and A. Kandala, Hamiltonian engineering with multicolor drives for fast entangling gates and quantum crosstalk cancellation, Phys. Rev. Lett. 129
2022
Later among the works it cites.
M. A. Nielsen, A simple formula for the average gate fidelity of a quantum dynamical operation, Physics Letters A 303
Original

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Reading the bibliography…

2023

Benchmarking Quantum Processor Performance at Scale

McKay, David C., Hincks, Ian, Pritchett, Emily J. et al.

Understand

As quantum processors grow, new performance benchmarks are required to capture the full quality of the devices at scale.

While quantum volume is an excellent benchmark, it focuses on the highest quality subset of the device and so is unable to indicate the average performance over a large number of connected qubits.
Furthermore, it is a discrete pass/fail and so is not reflective of continuous improvements in hardware nor does it provide quantitative direction to large-scale algorithms.
For example, there may be value in error mitigated Hamiltonian simulation at scale with devices unable to pass strict quantum volume tests.

Built on

J. Emerson, R. Alicki, and K. Życzkowski, Scalable noise estimation with random unitary operators, Journal of Optics B: Quantum and Semiclassical Optics 7
2005
Earlier work this paper cites.
L. H. Pedersen, N. M. Møller, and K. Mølmer, Fidelity of quantum operations, Physics Letters A 367
2007
Earlier work this paper cites.
E. Magesan, J. M. Gambetta, and J. Emerson, Characterizing quantum gates via randomized benchmarking, Phys. Rev. A 85
2012
Earlier work this paper cites.
J. M. Gambetta, A. D. Córcoles, S. T. Merkel, B. R. Johnson, J. A. Smolin, J. M. Chow, C. A. Ryan, C. Rigetti, S. Poletto, T. A. Ohki, M. B. Ketchen, and M. Steffen, Characterization of addressability by simultaneous randomized benchmarking, Phys. Rev. Lett. 109
2012
Earlier work this paper cites.
S. Kimmel, M. P. da Silva, C. A. Ryan, B. R. Johnson, and T. Ohki, Robust extraction of tomographic information via randomized benchmarking, Phys. Rev. X 4
2014
Earlier work this paper cites.
D. Greenbaum, Introduction to quantum gate set tomography (2015), arXiv:1509.02921 [quant-ph]
Original
2015
Earlier work this paper cites.
S. Boixo, S. V. Isakov, V. N. Smelyanskiy, R. Babbush, N. Ding, Z. Jiang, M. J. Bremner, J. M. Martinis, and H. Neven, Characterizing quantum supremacy in near-term devices, Nature Physics 14
2018
Earlier work this paper cites.
A. W. Cross, L. S. Bishop, S. Sheldon, P. D. Nation, and J. M. Gambetta, Validating quantum computers using randomized model circuits, Physical Review A 100
2019
Earlier work this paper cites.
T. J. Proctor, A. Carignan-Dugas, K. Rudinger, E. Nielsen, R. Blume-Kohout, and K. Young, Direct randomized benchmarking for multiqubit devices, Phys. Rev. Lett. 123
2019
Earlier work this paper cites.
A. Erhard, J. J. Wallman, L. Postler, M. Meth, R. Stricker, E. A. Martinez, P. Schindler, T. Monz, J. Emerson, and R. Blatt, Characterizing large-scale quantum computers via cycle benchmarking, Nat. Comm. 10
2019
Earlier work this paper cites.
J. Helsen, X. Xue, L. M. K. Vandersypen, and S. Wehner, A new class of efficient randomized benchmarking protocols, npj Quantum Inf 5
2019
Earlier work this paper cites.
P. Murali, J. M. Baker, A. Javadi-Abhari, F. T. Chong, and M. Martonosi, Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers, in Proceedings of the twenty-fourth international conference on architectural support for programming languages and operating systems (2019) pp. 1015–1029
2019
Earlier work this paper cites.
D. C. McKay, A. W. Cross, C. J. Wood, and J. M. Gambetta, Correlated randomized benchmarking (2020)
2020
Earlier work this paper cites.
R. Harper, S. Flammia, and J. Wallman, Efficient learning of quantum noise, Nat. Phys. 16
2020
Earlier work this paper cites.
A. Wack, H. Paik, A. Javadi-Abhari, P. Jurcevic, I. Faro, J. M. Gambetta, and B. R. Johnson, Quality, speed, and scale: three key attributes to measure the performance of near-term quantum computers, arXiv preprint arXiv:2110.14108 (2021)
Original
2021
Earlier work this paper cites.

Similar

T. Lubinski, S. Johri, P. Varosy, J. Coleman, L. Zhao, J. Necaise, C. H. Baldwin, K. Mayer, and T. Proctor, Application-oriented performance benchmarks for quantum computing, arXiv preprint arXiv:2110.03137 (2021)
Original
2021
Cited alongside, same era.
K. Mesman, Z. Al-Ars, and M. Möller, Qpack: Quantum approximate optimization algorithms as universal benchmark for quantum computers, arXiv preprint arXiv:2103.17193 (2021)
Original
2021
Cited alongside, same era.
B. K. Mitchell, R. K. Naik, A. Morvan, A. Hashim, J. M. Kreikebaum, B. Marinelli, W. Lavrijsen, K. Nowrouzi, D. I. Santiago, and I. Siddiqi, Hardware-efficient microwave-activated tunable coupling between superconducting qubits, Phys. Rev. Lett. 127
2021
Cited alongside, same era.
E. v. d. Berg, Z. K. Minev, A. Kandala, and K. Temme, Probabilistic error cancellation with sparse pauli-lindblad models on noisy quantum processors, arXiv preprint arXiv:2201.09866 (2022)
Original
2022
Cited alongside, same era.

Then

S. Ferracin, A. Hashim, J.-L. Ville, R. Naik, A. Carignan-Dugas, H. Qassim, A. Morvan, D. I. Santiago, I. Siddiqi, and J. J. Wallman, Efficiently improving the performance of noisy quantum computers (2022), arXiv:2201.10672 [quant-ph]
Original
2022
Later among the works it cites.
P. D. Nation and M. Treinish, Suppressing quantum circuit errors due to system variability, arXiv preprint arXiv:2209.15512 (2022)
Original
2022
Later among the works it cites.
K. X. Wei, E. Magesan, I. Lauer, S. Srinivasan, D. F. Bogorin, S. Carnevale, G. A. Keefe, Y. Kim, D. Klaus, W. Landers, N. Sundaresan, C. Wang, E. J. Zhang, M. Steffen, O. E. Dial, D. C. McKay, and A. Kandala, Hamiltonian engineering with multicolor drives for fast entangling gates and quantum crosstalk cancellation, Phys. Rev. Lett. 129
2022
Later among the works it cites.
M. A. Nielsen, A simple formula for the average gate fidelity of a quantum dynamical operation, Physics Letters A 303
Original

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

J. Helsen, I. Roth, E. Onorati, A. Werner, and J. Eisert, General framework for randomized benchmarking, PRX Quantum 3

2022

Cited alongside, same era.

J. R. Finžgar, P. Ross, L. Hölscher, J. Klepsch, and A. Luckow, Quark: A framework for quantum computing application benchmarking, in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (IEEE, 2022) pp. 226–237

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Cited alongside, same era.

T. Tomesh, P. Gokhale, V. Omole, G. S. Ravi, K. N. Smith, J. Viszlai, X.-C. Wu, N. Hardavellas, M. R. Martonosi, and F. T. Chong, Supermarq: A scalable quantum benchmark suite, in 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA) (IEEE, 2022) pp. 587–603

2022

Cited alongside, same era.

A. Kurlej, S. Alterman, and K. M. Obenland, Benchmarking and analysis of noisy intermediate-scale trapped ion quantum computing architectures, in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (IEEE, 2022) pp. 247–258

2022

Cited alongside, same era.

M. Kordzanganeh, M. Buchberger, M. Povolotskii, W. Fischer, A. Kurkin, W. Somogyi, A. Sagingalieva, M. Pflitsch, and A. Melnikov, Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms, arXiv preprint arXiv:2211.15631 (2022)

Original

2022

Cited alongside, same era.

P. S. Mundada, A. Barbosa, S. Maity, T. Stace, T. Merkh, F. Nielson, A. R. Carvalho, M. Hush, M. J. Biercuk, and Y. Baum, Experimental benchmarking of an automated deterministic error suppression workflow for quantum algorithms, arXiv preprint arXiv:2209.06864 (2022)

Original

2022

Cited alongside, same era.

A. Li, S. Stein, S. Krishnamoorthy, and J. Ang, Qasmbench: A low-level quantum benchmark suite for nisq evaluation and simulation, ACM Transactions on Quantum Computing 10.1145/3550488 (2022)

2022

Cited alongside, same era.

T. Proctor, S. Seritan, K. Rudinger, E. Nielsen, R. Blume-Kohout, and K. Young, Scalable randomized benchmarking of quantum computers using mirror circuits, Phys. Rev. Lett. 129

2022

Cited alongside, same era.

2022

Later among the works it cites.

M. Amico, H. Zhang, P. Jurcevic, L. Bishop, P. Nation, A. Wack, and D. C. McKay, Defining standard strategies for quantum benchmarks, arXiv preprint arXiv:2303.02108 (2023)

Original

2023

Closest in time.

V. Zhang and P. D. Nation, Characterizing quantum processors using discrete time crystals, arXiv preprint arXiv:2301.07625 (2023)

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2023

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T. Lubinski, C. Coffrin, C. McGeoch, P. Sathe, J. Apanavicius, and D. E. B. Neira, Optimization applications as quantum performance benchmarks, arXiv preprint arXiv:2302.02278 (2023)

Original

2023

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J. Hines, D. Hothem, R. Blume-Kohout, B. Whaley, and T. Proctor, Fully scalable randomized benchmarking without motion reversal (2023), arXiv:2309.05147 [quant-ph]

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2023

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Quantinuum, Quantinuum h-series quantum computer accelerates through 3 more performance records for quantum volume: 2 1 7 2^{1}7 , 2 1 8 2^{1}8 , and 2 1 9 2^{1}9 (2023)

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X. Xu, S. Benjamin, J. Sun, X. Yuan, and P. Zhang, A herculean task: Classical simulation of quantum computers (2023)

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A. M. Dalzell, S. McArdle, M. Berta, P. Bienias, C.-F. Chen, A. Gilyén, C. T. Hann, M. J. Kastoryano, E. T. Khabiboulline, A. Kubica, G. Salton, S. Wang, and F. G. S. L. Brandão, Quantum algorithms: A survey of applications and end-to-end complexities (2023), arXiv:2310.03011 [quant-ph]

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M. Liepelt, T. Peduzzi, and J. R. Wootton, Enhanced repetition codes for the cross-platform comparison of progress towards fault-tolerance (2023), arXiv:2308.08909 [quant-ph]

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2023

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A. Morvan and et. al, Phase transition in random circuit sampling (2023), arXiv:2304.11119 [quant-ph]

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A. Carignan-Dugas, D. Dahlen, I. Hincks, E. Ospadov, S. J. Beale, S. Ferracin, J. Skanes-Norman, J. Emerson, and J. J. Wallman, The error reconstruction and compiled calibration of quantum computing cycles (2023)

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