The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light
Open accessAbstract
We report phase-programmable Gaussian boson sampling (GBS) which produces up to 113 photon detection events out of a 144-mode photonic circuit. A new high-brightness and scalable quantum light source is developed, exploring the idea of stimulated emission of squeezed photons, which has simultaneously near-unity purity and efficiency. This GBS is programmable by tuning the phase of the input squeezed states. The obtained samples are efficiently validated by inferring from computationally friendly subsystems, which rules out hypotheses including distinguishable photons and thermal states. We show that our GBS experiment passes a nonclassicality test based on inequality constraints, and we reveal nontrivial genuine high-order correlations in the GBS samples, which are evidence of robustness against possible classical simulation schemes. This photonic quantum computer, Jiuzhang 2.0, yields a Hilbert space dimension up to ∼10^{43}, and a sampling rate ∼10^{24} faster than using brute-force simulation on classical supercomputers.
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“There are then two ways around this no-go result: one can either give up programmability and build an ultralow loss fixed static interferometer, as implemented in refs. 1,2, or give up universality while maintaining a high degree of multimode entanglement using long-ranged gates.”
From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [2]
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“Thus, the fact that significant third- and fourth-order cumulants are observed in refs. 1,2 is simply a reflection of the fact that most of their inputs are vacuum and that their experiment lacks photon-number resolution.”
From Quantum computational advantage with a programmable photonic processor (2022) · cites this paper as [2]
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“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.”
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“we estimate that Fugaku would require 1.5 h, on average, to generate one sample from the experiment in ref. 2”
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“or 8,500 years for the 50 million generated in their experiment.”
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Citations
Cites
Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?
Einstein, A., Podolsky, B., & Rosen, N. (1935) · Physical Review · doi:10.1103/physrev.47.777 · Cited by 16,654
Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
Nishita, M., Park, S.-Y., Nishio, T., Kamizaki, K., Wang, Z., Tamada, K., Takumi, T., Hashimoto, R., Otani, H., Pazour, G. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-016-0028-x · Cited by 15,947
Self-citationOn the Einstein Podolsky Rosen paradox
Bell, J. S. (1964) · Physics Physique Fizika · doi:10.1103/physicsphysiquefizika.1.195 · Cited by 12,252
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830
Quantum supremacy using a programmable superconducting processor
Arute, F., Arya, K., Babbush, R., Bacon, D., Bardin, J. C., Barends, R., Biswas, R., Boixo, S., Brandao, F. G. S. L., Buell, D. A., et al. (2019) · Nature · doi:10.1038/s41586-019-1666-5 · Cited by 7,720 · cited 2×
“32(1), which is significantly larger than the statistical fluctuation, thus successfully distinguishing the data of the 30 different groups.”
BackgroundA scheme for efficient quantum computation with linear optics
Knill, E., Laflamme, R., & Milburn, G. J. (2001) · Nature · doi:10.1038/35051009 · Cited by 5,880
Linear optical quantum computing with photonic qubits
Kok, P., Munro, W. J., Nemoto, K., Ralph, T. C., Dowling, J. P., & Milburn, G. J. (2007) · Reviews of Modern Physics · doi:10.1103/revmodphys.79.135 · Cited by 2,904
Quantum computational advantage using photons
Zhong, H.-S., Wang, H., Deng, Y.-H., Chen, M.-C., Peng, L.-C., Luo, Y.-H., Qin, J., Wu, D., Ding, X., Hu, Y., et al. (2020) · Science · doi:10.1126/science.abe8770 · Cited by 2,405
Self-citationQuantum Machine Learning in Feature Hilbert Spaces
Schuld, M., & Killoran, N. (2019) · Physical Review Letters · doi:10.1103/physrevlett.122.040504 · Cited by 1,840
Encoding a qubit in an oscillator
Gottesman, D., Kitaev, A., & Preskill, J. (2001) · Physical Review A · doi:10.1103/physreva.64.012310 · Cited by 1,532
Cited by
Sorted by citations
Strong Quantum Computational Advantage Using a Superconducting Quantum Processor
Wu, Y., Bao, W.-S., Cao, S., Chen, F., Chen, M.-C., Chen, X., Chung, T.-H., Deng, H., Du, Y., Fan, D., et al. (2021) · Physical Review Letters · doi:10.1103/physrevlett.127.180501 · Cited by 1,059
Self-citationQuantum computational advantage with a programmable photonic processor
Madsen, L. S., Laudenbach, F., Askarani, M. F., Rortais, F., Vincent, T., Bulmer, J. F. F., Miatto, F. M., Neuhaus, L., Helt, L. G., Collins, M. J., et al. (2022) · Nature · doi:10.1038/s41586-022-04725-x · Cited by 1,101
“Only a handful of experiments have used quantum devices to carry out computational tasks that are outside the reach of present-day classical computers 1,2,6,7 .”
BackgroundMethodInfluentialThe potential and global outlook of integrated photonics for quantum technologies
Pelucchi, E., Fagas, G., Aharonovich, I., Englund, D. R., Figueroa, E. V., Gong, Q., Hübel, H., Liu, J., Lu, C., Matsuda, N., et al. (2021) · Nature Reviews Physics · doi:10.1038/s42254-021-00398-z · Cited by 578
Self-citationA programmable qudit-based quantum processor
Chi, Y., Huang, J., Zhang, Z., Mao, J., Zhou, Z., Chen, X., Zhai, C., Bao, J., Dai, T., Yuan, H., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28767-x · Cited by 273
Self-citationQuantum computational advantage via 60-qubit 24-cycle random circuit sampling
Zhu, Q., Cao, S., Chen, F., Chen, M.-C., Chen, X., Chung, T.-H., Deng, H., Du, Y., Fan, D., Gong, M., et al. (2022) · Science Bulletin · doi:10.1016/j.scib.2021.10.017 · Cited by 263
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Metadata
- Authors
- Zhong, H.-S., Deng, Y.-H., Qin, J., Wang, H., Chen, M.-C., Peng, L.-C., Luo, Y.-H., Wu, D., Gong, S.-Q., Su, H., Hu, Y., Hu, P., Yang, X.-Y., Zhang, W.-J., Li, H., Li, Y., Jiang, X., Gan, L., Yang, G., You, L., Wang, Z., Li, L., Liu, N.-L., Renema, J. J., Lu, C.-Y., & Pan, J.-W.
- Affiliations
- University of Science and Technology of China (CN)
- Chinese Academy of Sciences (CN)
- Beijing National Research Center for Information Science and Technology (CN)
- University of Twente (NL)
- ORCID
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2021-10-25
- Volume
- 127
- Issue
- 18
- Pages
- 180502-180502
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W3176603110
- Cited by
- 434
- References
- 79
- Citations by year
- 2026: 45 · 2025: 87 · 2024: 91 · 2023: 113 · 2022: 85 · 2021: 13
- FWCI
- 26.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Physical Review Letters (publishedVersion)
- PubMed (publishedVersion)
- University of Twente Research Information (publishedVersion, other-oa)
- University of Twente Research Information (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- University of Twente Research Information (submittedVersion)
- University of Twente Research Information (submittedVersion, other-oa)
- arXiv (Cornell University) (cc-by)
- Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China (2019YFA0308700)
- Chinese Academy of Sciences
- Science and Technology Commission of Shanghai Municipality (2019SHZDZX01)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Anhui Initiative in Quantum Information Technologies
- 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, photonic quantum computing, quantum advantage, Hilbert space dimension
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