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Harnessing microcomb-based parallel chaos for random number generation and optical decision making
Optical chaos is vital for various applications such as private communication, encryption, anti-interference sensing, and reinforcement learning. Chaotic microcombs have emerged as promising sources for generating massive optical chaos. However, their inter-channel correlation behavior remains elusi...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390475/ https://www.ncbi.nlm.nih.gov/pubmed/37524697 http://dx.doi.org/10.1038/s41467-023-40152-w |
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author | Shen, Bitao Shu, Haowen Xie, Weiqiang Chen, Ruixuan Liu, Zhi Ge, Zhangfeng Zhang, Xuguang Wang, Yimeng Zhang, Yunhao Cheng, Buwen Yu, Shaohua Chang, Lin Wang, Xingjun |
author_facet | Shen, Bitao Shu, Haowen Xie, Weiqiang Chen, Ruixuan Liu, Zhi Ge, Zhangfeng Zhang, Xuguang Wang, Yimeng Zhang, Yunhao Cheng, Buwen Yu, Shaohua Chang, Lin Wang, Xingjun |
author_sort | Shen, Bitao |
collection | PubMed |
description | Optical chaos is vital for various applications such as private communication, encryption, anti-interference sensing, and reinforcement learning. Chaotic microcombs have emerged as promising sources for generating massive optical chaos. However, their inter-channel correlation behavior remains elusive, limiting their potential for on-chip parallel chaotic systems with high throughput. In this study, we present massively parallel chaos based on chaotic microcombs and high-nonlinearity AlGaAsOI platforms. We demonstrate the feasibility of generating parallel chaotic signals with inter-channel correlation <0.04 and a high random number generation rate of 3.84 Tbps. We further show the application of our approach by demonstrating a 15-channel integrated random bit generator with a 20 Gbps channel rate using silicon photonic chips. Additionally, we achieved a scalable decision-making accelerator for up to 256-armed bandit problems. Our work opens new possibilities for chaos-based information processing systems using integrated photonics, and potentially can revolutionize the current architecture of communication, sensing and computations. |
format | Online Article Text |
id | pubmed-10390475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103904752023-08-02 Harnessing microcomb-based parallel chaos for random number generation and optical decision making Shen, Bitao Shu, Haowen Xie, Weiqiang Chen, Ruixuan Liu, Zhi Ge, Zhangfeng Zhang, Xuguang Wang, Yimeng Zhang, Yunhao Cheng, Buwen Yu, Shaohua Chang, Lin Wang, Xingjun Nat Commun Article Optical chaos is vital for various applications such as private communication, encryption, anti-interference sensing, and reinforcement learning. Chaotic microcombs have emerged as promising sources for generating massive optical chaos. However, their inter-channel correlation behavior remains elusive, limiting their potential for on-chip parallel chaotic systems with high throughput. In this study, we present massively parallel chaos based on chaotic microcombs and high-nonlinearity AlGaAsOI platforms. We demonstrate the feasibility of generating parallel chaotic signals with inter-channel correlation <0.04 and a high random number generation rate of 3.84 Tbps. We further show the application of our approach by demonstrating a 15-channel integrated random bit generator with a 20 Gbps channel rate using silicon photonic chips. Additionally, we achieved a scalable decision-making accelerator for up to 256-armed bandit problems. Our work opens new possibilities for chaos-based information processing systems using integrated photonics, and potentially can revolutionize the current architecture of communication, sensing and computations. Nature Publishing Group UK 2023-07-31 /pmc/articles/PMC10390475/ /pubmed/37524697 http://dx.doi.org/10.1038/s41467-023-40152-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shen, Bitao Shu, Haowen Xie, Weiqiang Chen, Ruixuan Liu, Zhi Ge, Zhangfeng Zhang, Xuguang Wang, Yimeng Zhang, Yunhao Cheng, Buwen Yu, Shaohua Chang, Lin Wang, Xingjun Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title | Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title_full | Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title_fullStr | Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title_full_unstemmed | Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title_short | Harnessing microcomb-based parallel chaos for random number generation and optical decision making |
title_sort | harnessing microcomb-based parallel chaos for random number generation and optical decision making |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390475/ https://www.ncbi.nlm.nih.gov/pubmed/37524697 http://dx.doi.org/10.1038/s41467-023-40152-w |
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