Nature Communications (Jul 2023)

Harnessing microcomb-based parallel chaos for random number generation and optical decision making

  • Bitao Shen,
  • Haowen Shu,
  • Weiqiang Xie,
  • Ruixuan Chen,
  • Zhi Liu,
  • Zhangfeng Ge,
  • Xuguang Zhang,
  • Yimeng Wang,
  • Yunhao Zhang,
  • Buwen Cheng,
  • Shaohua Yu,
  • Lin Chang,
  • Xingjun Wang

DOI
https://doi.org/10.1038/s41467-023-40152-w
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 10

Abstract

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Abstract 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.