Robust quantum computational advantage with programmable 3050-photon Gaussian boson sampling Article Swipe
Chao‐Yang Lu
,
Hua-Liang Liu
,
Hao Su
,
Si-Qiu Gong
,
Yi-Chao Gu
,
Haoyang Tang
,
Meng-Hao Jia
,
Wei Qian
,
Yu-Kun Song
,
Dongzhou Wang
,
Mingyang Zheng
,
Faxi Chen
,
Libo Li
,
Siyu Ren
,
Xi‐Cheng Zhu
,
Meihong Wang
,
Yaojian Chen
,
Yanfei Liu
,
L. S. Song
,
Pengyu Yang
,
Junshi Chen
,
Hong An
,
Lei Zhang
,
Lin Gan
,
Guangwen Yang
,
Jiamin Xu
,
Yu-Ming He
,
Hui Wang
,
Han-Sen Zhong
,
Ming-Cheng Chen
,
Xiao Jiang
,
Li Li
,
Nai-Le Liu
,
Yu-Hao Deng
,
Xiaolong Su
,
Qiang Zhang
,
Jian-Wei Pan
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-7435859/v1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-7435859/v1
The creation of large-scale, high-fidelity quantum computers is not only a fundamental scientific endeavour in itself, but also provides increasingly robust proofs of quantum computational advantage (QCA) in the presence of unavoidable noise and the dynamic competition with classical algorithm improvements. To overcome the biggest challenge of photon-based QCA experiments, photon loss, we report new Gaussian boson sampling(GBS) experiments with 1024 high-efficiency squeezed states injected into a hybrid spatial-temporal encoded, 8176-mode, programmable photonic quantum processor, Jiuzhang 4.0, which produces up to 3050 photon detection events. Our experimental results outperform all classical spoofing algorithms, particularly the matrix product state (MPS) method, which was recently proposed to utilise photon loss to reduce the classical simulation complexity of GBS. Using the state-of-the-art MPS algorithm on the most powerful supercomputer EI Capitan, it would take > 10^42 years to construct the required tensor network for simulation, while our Jiuzhang 4.0 quantum computer takes 25.6 μs to produce a sample. This work establishes a new frontier of QCA and paves the way to fault-tolerant photonic quantum computing hardware.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-7435859/v1
- https://www.researchsquare.com/article/rs-7435859/latest.pdf
- OA Status
- gold
- OpenAlex ID
- https://openalex.org/W4414352784
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4414352784Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-7435859/v1Digital Object Identifier
- Title
-
Robust quantum computational advantage with programmable 3050-photon Gaussian boson samplingWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-09-19Full publication date if available
- Authors
-
Chao‐Yang Lu, Hua-Liang Liu, Hao Su, Si-Qiu Gong, Yi-Chao Gu, Haoyang Tang, Meng-Hao Jia, Wei Qian, Yu-Kun Song, Dongzhou Wang, Mingyang Zheng, Faxi Chen, Libo Li, Siyu Ren, Xi‐Cheng Zhu, Meihong Wang, Yaojian Chen, Yanfei Liu, L. S. Song, Pengyu Yang, Junshi Chen, Hong An, Lei Zhang, Lin Gan, Guangwen Yang, Jiamin Xu, Yu-Ming He, Hui Wang, Han-Sen Zhong, Ming-Cheng Chen, Xiao Jiang, Li Li, Nai-Le Liu, Yu-Hao Deng, Xiaolong Su, Qiang Zhang, Jian-Wei PanList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-7435859/v1Publisher landing page
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https://www.researchsquare.com/article/rs-7435859/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-7435859/latest.pdfDirect OA link when available
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0Total citation count in OpenAlex
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| publication_date | 2025-09-19 |
| publication_year | 2025 |
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