Exploring 400 Gbps/λ and beyond with AI-accelerated silicon photonic slow-light technology
Silicon photonics is a promising platform for the extensive deployment of optical interconnections, with the feasibility of low-cost and large-scale production at the wafer level. However, the intrinsic efficiency-bandwidth trade-off and nonlinear distortions of pure silicon modulators result in the transmission limits, which raises concerns about the prospects of silicon photonics for ultrahigh-speed scenarios. Here, we propose an artificial intelligence (AI)-accelerated silicon photonic slow-light technology to explore 400 Gbps/λ and beyond transmission. By utilizing the artificial neural network, we achieve a data capacity of 3.2 Tbps based on an 8-channel wavelength-division-multiplexed silicon slow-light modulator chip with a thermal-insensitive structure, leading to an on-chip data-rate density of 1.6 Tb/s/mm<sup>2</sup>. The demonstration of single-lane 400 Gbps PAM-4 transmission reveals the great potential of standard silicon photonic platforms for next-generation optical interfaces. Our approach increases the transmission rate of silicon photonics significantly and is expected to construct a self-optimizing positive feedback loop with computing centers through AI technology.
Authors
- Zhixue He (ORCID: https://orcid.org/0000-0001-8533-2247)
- Chao Peng (ORCID: https://orcid.org/0000-0002-0200-0798)
- Zhangfeng Ge
- Yunhao Zhang (ORCID: https://orcid.org/0009-0001-5851-750X)
- Jun Qin (ORCID: https://orcid.org/0000-0002-5456-0850)
- Changhao Han (ORCID: https://orcid.org/0000-0001-9315-011X)
- Qipeng Yang
- Yu Sun (ORCID: https://orcid.org/0000-0003-2066-5053)
- Zhao Zheng (ORCID: https://orcid.org/0009-0005-3856-7488)
- Haoren Wang (ORCID: https://orcid.org/0000-0002-0841-4422)
- Lei Wang (ORCID: https://orcid.org/0000-0003-2184-7190)
- Yimeng Wang (ORCID: https://orcid.org/0000-0001-6553-9988)
- Xingjun Wang (ORCID: https://orcid.org/0000-0001-8206-2544)
- Haowen Shu (ORCID: https://orcid.org/0000-0002-5429-8661)
- Yan Zhou (ORCID: https://orcid.org/0000-0002-1743-891X)
- John E. Bowers (ORCID: https://orcid.org/0000-0003-4270-8296)
- Yichen Wu (ORCID: https://orcid.org/0009-0005-8083-6848)
- Shaohua Yu
- Junde Lu (ORCID: https://orcid.org/0009-0003-3072-6195)
- Weiwei Hu
Institutions
- King University (US)
- University of California, Santa Barbara (US)
- Peking University (CN)
- Peng Cheng Laboratory (CN)
- Beijing Information Science & Technology University (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1038/s41467-025-61933-5
- Citations
- 4
- Primary Topic
- Photonic and Optical Devices
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- National Natural Science Foundation of China
- Beijing Municipal Science and Technology Commission
- National Key Research and Development Program of China