Integrated silicon-photonic reservoir computing with an on-chip Si3N4 microcavity
We propose an integrated silicon photonic reservoir computing (RC) scheme using a silicon nitride (Si3N4) microcavity hybrid coupled with a semiconductor laser chip. The device is more than 10 times smaller than existing analogs, owing to the highly integrated Si3N4 microcavity. The device is chaoti...
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| Published in | Optics communications Vol. 591; p. 132133 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.10.2025
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| Online Access | Get full text |
| ISSN | 0030-4018 |
| DOI | 10.1016/j.optcom.2025.132133 |
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| Abstract | We propose an integrated silicon photonic reservoir computing (RC) scheme using a silicon nitride (Si3N4) microcavity hybrid coupled with a semiconductor laser chip. The device is more than 10 times smaller than existing analogs, owing to the highly integrated Si3N4 microcavity. The device is chaotic in a radio-frequency range exceeding 20 GHz, with subnanosecond-scale nonlinear temporal fluctuations. An RC system is constructed and tested on time-series prediction and handwritten-digit recognition tasks. The normalized mean square error is 0.014 on the Santa Fe test with 109 samples/s, while the error rate on the MNIST handwritten-digit dataset is approximately 5.3 %. These results are promising for highly compact RC schemes with complementary metal-oxide semiconductor compatibility. |
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| AbstractList | We propose an integrated silicon photonic reservoir computing (RC) scheme using a silicon nitride (Si3N4) microcavity hybrid coupled with a semiconductor laser chip. The device is more than 10 times smaller than existing analogs, owing to the highly integrated Si3N4 microcavity. The device is chaotic in a radio-frequency range exceeding 20 GHz, with subnanosecond-scale nonlinear temporal fluctuations. An RC system is constructed and tested on time-series prediction and handwritten-digit recognition tasks. The normalized mean square error is 0.014 on the Santa Fe test with 109 samples/s, while the error rate on the MNIST handwritten-digit dataset is approximately 5.3 %. These results are promising for highly compact RC schemes with complementary metal-oxide semiconductor compatibility. |
| ArticleNumber | 132133 |
| Author | Bai, Qingsong Wu, Zhengmao Wu, Mingjie Zhao, Lehan Deng, Changmao Wu, Jiagui Ran, Chongchong Zeng, Yongcan Yang, Wenyan |
| Author_xml | – sequence: 1 givenname: Lehan surname: Zhao fullname: Zhao, Lehan organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 2 givenname: Qingsong surname: Bai fullname: Bai, Qingsong organization: Chengdu Spaceon Electronics Corporation Ltd., Chengdu, 610037, China – sequence: 3 givenname: Mingjie surname: Wu fullname: Wu, Mingjie organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 4 givenname: Chongchong surname: Ran fullname: Ran, Chongchong organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 5 givenname: Yongcan surname: Zeng fullname: Zeng, Yongcan organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 6 givenname: Changmao surname: Deng fullname: Deng, Changmao organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 7 givenname: Zhengmao surname: Wu fullname: Wu, Zhengmao organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China – sequence: 8 givenname: Wenyan surname: Yang fullname: Yang, Wenyan email: yangwy@cqust.edu.cn organization: School of Physics, Chongqing University of Science and Technology, Chongqing, 401331, China – sequence: 9 givenname: Jiagui orcidid: 0000-0003-2743-5162 surname: Wu fullname: Wu, Jiagui email: mgh@swu.edu.cn organization: School of Physical Science and Technology, Southwest University, Chongqing, 400715, China |
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| Title | Integrated silicon-photonic reservoir computing with an on-chip Si3N4 microcavity |
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