Matchgate benchmarking: Scalable benchmarking of a continuous family of many-qubit gates

Jonas Helsen; Sepehr Nezami; Matthew Reagor; Michael Walter

doi:10.22331/q-2022-02-21-657

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Matchgate benchmarking: Scalable benchmarking of a continuous family of many-qubit gates

Jonas Helsen^1,2, Sepehr Nezami³, Matthew Reagor⁴, and Michael Walter^1,5,6

¹QuSoft & Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Science Park 123, 1098 XG Amsterdam, The Netherlands
²Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG Amsterdam, The Netherlands
³Institute for Quantum Information and Matter, Caltech, Pasadena, CA 91125, USA
⁴Rigetti Computing, 775 Heinz Ave, Berkeley, CA 94710, USA
⁵Institute for Theoretical Physics & ILLC, University of Amsterdam, Science Park 123, 1098 XG Amsterdam, The Netherlands
⁶Faculty of Computer Science, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany

Published:	2022-02-21, volume 6, page 657
Eprint:	arXiv:2011.13048v2
Doi:	https://doi.org/10.22331/q-2022-02-21-657
Citation:	Quantum 6, 657 (2022).

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Abstract

We propose a method to reliably and efficiently extract the fidelity of many-qubit quantum circuits composed of continuously parametrized two-qubit gates called matchgates. This method, which we call $\textit{matchgate benchmarking}$, relies on advanced techniques from randomized benchmarking as well as insights from the representation theory of matchgate circuits. We argue the formal correctness and scalability of the protocol, and moreover deploy it to estimate the performance of matchgate circuits generated by two-qubit XY spin interactions on a quantum processor.

► BibTeX data

@article{Helsen2022matchgate,
  doi = {10.22331/q-2022-02-21-657},
  url = {https://doi.org/10.22331/q-2022-02-21-657},
  title = {Matchgate benchmarking: {S}calable benchmarking of a continuous family of many-qubit gates},
  author = {Helsen, Jonas and Nezami, Sepehr and Reagor, Matthew and Walter, Michael},
  journal = {{Quantum}},
  issn = {2521-327X},
  publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}},
  volume = {6},
  pages = {657},
  month = feb,
  year = {2022}
}

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Cited by

[1] J. Helsen, I. Roth, E. Onorati, A. H. Werner, and J. Eisert, "General Framework for Randomized Benchmarking", PRX Quantum 3 2, 020357 (2022).

[2] Michał Oszmaniec, Ninnat Dangniam, Mauro E. S. Morales, and Zoltán Zimborás, "Fermion Sampling: A Robust Quantum Computational Advantage Scheme Using Fermionic Linear Optics and Magic Input States", PRX Quantum 3 2, 020328 (2022).

[3] Yunchao Liu, Matthew Otten, Roozbeh Bassirianjahromi, Liang Jiang, and Bill Fefferman, "Benchmarking near-term quantum computers via random circuit sampling", arXiv:2105.05232, (2021).

[4] Jonas Helsen, Ingo Roth, Emilio Onorati, Albert H. Werner, and Jens Eisert, "A general framework for randomized benchmarking", arXiv:2010.07974, (2020).

[5] Ashley Montanaro and Stasja Stanisic, "Error mitigation by training with fermionic linear optics", arXiv:2102.02120, (2021).

[6] Ryotaro Suzuki, Kosuke Mitarai, and Keisuke Fujii, "Computational power of one- and two-dimensional dual-unitary quantum circuits", Quantum 6, 631 (2022).

[7] Markus Heinrich, Martin Kliesch, and Ingo Roth, "Randomized benchmarking with random quantum circuits", arXiv:2212.06181, (2022).

[8] Jahan Claes, Eleanor Rieffel, and Zhihui Wang, "Character randomized benchmarking for non-multiplicity-free groups with applications to subspace, leakage, and matchgate randomized benchmarking", arXiv:2011.00007, (2020).

The above citations are from SAO/NASA ADS (last updated successfully 2024-09-16 23:25:33). The list may be incomplete as not all publishers provide suitable and complete citation data.

On Crossref's cited-by service no data on citing works was found (last attempt 2024-09-16 23:25:32).

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Matchgate benchmarking: Scalable benchmarking of a continuous family of many-qubit gates

Abstract

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