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Evaluating the performance of quantum devices is an important step towards scaling quantum devices and eventually using them in practice.
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2021
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E. Farhi, J. Goldstone, and S. Gutmann, “A quantum approximate optimization algorithm,” 2014
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2018
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QuTech, “Quantum inspire starmon-5 fact sheet,” https://www.quantum-inspire.com/backends/starmon-5/ , 6 2020
2020
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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,” 2022
2022
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K. Mesman, Z. Al-Ars, and M. Möller, “Qpack: Quantum approximate optimization algorithms as universal benchmark for quantum computers,” 2022
2022
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W. van der Schoot, D. Leermakers, R. Wezeman, N. Neumann, and F. Phillipson, “Evaluating the q-score of quantum annealers,” in 2022 IEEE International Conference on Quantum Software (QSW) , 2022, pp. 9–16
2022
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M. Langione, J.-F. Bobier, L. Krayer, H. Park, and A. Kumar, “The race to quantum advantage depends on benchmarking,” Boston Consulting Group, Tech. Rep., Feb 2022
2022
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J. Weidenfeller, L. C. Valor, J. Gacon, C. Tornow, L. Bello, S. Woerner, and D. J. Egger, “Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware,” Quantum , vol. 6, p. 870, dec 2022
2022
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J. Tilly, H. Chen, S. Cao, D. Picozzi, K. Setia, Y. Li, E. Grant, L. Wossnig, I. Rungger, G. H. Booth, and J. Tennyson, “The variational quantum eigensolver: A review of methods and best practices,” Physics Reports , vol. 986, p. 1–128, Nov. 2022. [Online]. Available: http://dx.doi.org/10.1016/j.physrep.2022.08.003
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W. van der Schoot, R. Wezeman, P. T. Eendebak, N. M. P. Neumann, and F. Phillipson, “Evaluating three levels of quantum metrics on quantum-inspire hardware,” Quantum Information Processing , vol. 22, no. 12, Dec. 2023. [Online]. Available: http://dx.doi.org/10.1007/s11128-023-04184-x
2023
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K. Blekos, D. Brand, A. Ceschini, C.-H. Chou, R.-H. Li, K. Pandya, and A. Summer, “A review on quantum approximate optimization algorithm and its variants,” Physics Reports , vol. 1068, pp. 1–66, 2024, a review on Quantum Approximate Optimization Algorithm and its variants
2024
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F. Barbaresco, L. Rioux, C. Labreuche, M. Nowak, N. Olivier, D. Nicolazic, O. Hess, A.-L. Guilmin, R. Wang, T. Sassolas, S. Louise, K. Snizhko, G. Misguich, A. Auffèves, R. Whitney, E. Vergnaud, and F. Schopfer, “Bacq – application-oriented benchmarks for quantum computing,” 2024
2024
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