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Gaussian boson sampling using threshold detectors
Open accessAbstract
We study what is arguably the most experimentally appealing boson sampling architecture: Gaussian states sampled with threshold detectors. We show that, in this setting, the probability of observing a given outcome is related to a matrix function that we name the Torontonian, which plays an analogous role to the permanent or the Hafnian in other models. We also prove that, provided that the probability of observing two or more photons in a single output mode is sufficiently small, our model remains intractable to simulate classically under standard complexity-theoretic conjectures. Finally, we leverage the mathematical simplicity of the model to introduce a physically motivated, exact sampling algorithm for all boson sampling models that employ Gaussian states and threshold detectors.
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“A simpler form of the experiment where instead of counting the number of photons in each mode, we only detect if there are photons or not in each mode, can be used to sample from the so-called Torontonian function of a matrix (Quesada et al. , 2018).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as Quesada et al., 2018
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Truong, T., Arenz, C., & Lukens, J. M. (2025) · Physical Review A · doi:10.1103/64lg-dwnm · Cited by 2
Noise reduction of multimode Gaussian-boson-sampling circuits via unitary averaging
Swain, S. N., Marshman, R. J., Solntsev, A. S., & Ralph, T. C. (2025) · Physical Review A · doi:10.1103/n9nc-xcmr · Cited by 1
Bianchi, L., Marconi, C., Ares, L., Bacco, D., & Sperling, J. (2025) · Physical Review Research · doi:10.1103/8hy1-m5gg · Cited by 2
Employing Integrated Quantum Photonic Computers for Gaussian Boson Sampling
Ghasemi, M., Kaatuzian, H., Noshad, H., Hassani, M., Motaharifar, M., & NoroozOliaei, M. (2024) · doi:10.1109/icee63041.2024.10667961 · Cited by 1
Conti, C. (2023) · Quantum science and technology · doi:10.1007/978-3-031-44226-1_12 · Cited by 1
Metadata
- Authors
- Quesada, N., Arrazola, J. M., & Killoran, N.
- Venue
- Physical Review A
- Publisher
- American Physical Society (APS)
- Published
- 2018-12-18
- Volume
- 98
- Issue
- 6
- ISSN
- 0556-2791 (ISSN-L)
- 2469-9926
- 2469-9934
- OpenAlex
- W2810513857
- Cited by
- 120
- References
- 33
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 21 · 2023: 22 · 2022: 21 · 2021: 14 · 2020: 12 · 2019: 7
- FWCI
- 4.62
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Physical Review A (publishedVersion)
- arXiv (Cornell University) (publishedVersion)
- PolyPublie (École Polytechnique de Montréal) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
- Keywords
- Gaussian boson sampling, threshold detectors, permanent, hafnian, Gaussian states, photon number statistics
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