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Cited by 87Quantum Computing Algorithms and ArchitectureQuantum Information and CryptographyQuantum many-body systems

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling

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Qi, Haoyu, Brod, Daniel J., Quesada, Nicolás, García-Patrón, Raúl·2020·Physical Review Letters
DOI 10.1103/physrevlett.124.100502
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Abstract

As a promising candidate for exhibiting quantum computational supremacy, Gaussian boson sampling (GBS) is designed to exploit the ease of experimental preparation of Gaussian states. However, sufficiently large and inevitable experimental noise might render GBS classically simulable. In this work, we formalize this intuition by establishing a sufficient condition for approximate polynomial-time classical simulation of noisy GBS-in the form of an inequality between the input squeezing parameter, the overall transmission rate, and the quality of photon detectors. Our result serves as a nonclassicality test that must be passed by any quantum computational supremacy demonstration based on GBS. We show that, for most linear-optical architectures, where photon loss increases exponentially with the circuit depth, noisy GBS loses its quantum advantage in the asymptotic limit. Our results thus delineate intermediate-sized regimes where GBS devices might considerably outperform classical computers for modest noise levels. Finally, we find that increasing the amount of input squeezing is helpful to evade our classical simulation algorithm, which suggests a potential route to mitigate photon loss.

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  • Combined with the high brightness of the source averaging r ~ 1.1, the experiment is well beyond any attempt at a now-known polynomial-time approximate classical simulation.

    “As discussed in the Methods, combined with the high brightness of our source averaging r ~ 1.1, places our experiment well beyond any attempt at a now-known polynomial-time approximate classical simulation31.”

    From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [31]

  • Other architectures either give up programmability or suffer steep losses that, in the asymptotic limit of many modes, render the sampling task roughly simulable as the loss scales exponentially with the system size.

    “This is not the case for other architectures in which one either has to give up programmability1,2 or suffer steep losses that, in the asymptotic limit of many modes, render the sampling task roughly simulable as the loss scales exponentially with the system size31.”

    From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [31]

  • If one were to target a universal and programmable interferometer with depth equal to the number of modes that covers densely the set of unitary matrices, the exponential accumulation of loss would prohibit showing a quantum advantage.

    “if one were to target a universal and programmable interferometer, with depth equal to the number of modes, that covers densely the set of unitary matrices, the exponential accumulation of loss would prohibit showing a quantum advantage.”

    From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [31]

  • The probability distribution associated with the ground truth programmed into the device cannot be well-approximated by any classical-Gaussian state.

    “To gauge this separation, and how it influences sampling, we use the results from ref. 31 to show in the section ‘Regimes of classical simulability’ that the probability distribution associated with the ground truth programmed into the device cannot be well-approximated by any classical-Gaussian state.”

    From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [31]

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Authors
Qi, H., Brod, D. J., Quesada, N., & García-Patrón, R.
Affiliations
  • Xanadu Quantum Technologies (Canada) (CA)
  • Universidade Federal Fluminense (BR)
ORCID
Venue
Physical Review Letters
Publisher
American Physical Society (APS)
Published
2020-03-13
Volume
124
Issue
10
Pages
100502-100502
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
DOI
10.1103/physrevlett.124.100502
OpenAlex
W2947931041
Cited by
87
References
60
Citations by year
2026: 10 · 2025: 15 · 2024: 11 · 2023: 18 · 2022: 16 · 2021: 12 · 2020: 5
FWCI
5.01
Type
journal article
Language
en
Open access
Licence
link.aps.org/licenses/aps-default-license (vor)
Locations
  • Physical Review Letters (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (acceptedVersion)
  • Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion)
  • PolyPublie (École Polytechnique de Montréal) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico
  • Instituto Nacional de Ciência e Tecnologia de Informação Quântica
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
Keywords
Gaussian boson sampling, classical simulability, noisy quantum circuits, squeezing, photon loss, photon detectors, linear optics

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