Evidence map›Paper›PMID 37524697›Full record

ArticleNature communications2023

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 and 3 more

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. A ScNature materials · 2026
    Article
  2. Article
  3. Miniaturized chaos-assisted Spectrometer.Light, science & applications · 2025
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Bitao Shen *State Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Haowen Shu *State Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China. haowenshu@pku.edu.cn.
Weiqiang XieDepartment of Electronic Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China.
Ruixuan ChenState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Zhi LiuState Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083, Beijing, China.
Zhangfeng GePeking University Yangtze Delta Institute of Optoelectronics, 226010, Nantong, China.
Xuguang ZhangState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Yimeng WangState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Yunhao ZhangState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Buwen ChengState Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083, Beijing, China.
Shaohua YuState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China.
Lin ChangState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China. linchang@pku.edu.cn.
Xingjun WangState Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, 100871, Beijing, China. xjwang@pku.edu.cn.ORCID http://orcid.org/0000-0001-8206-2544

Funding

Beijing Municipal Science and Technology Commission Z221100006722003Nantong Science and Technology Bureau JC2021002National Natural Science Foundation of China (National Science Foundation of China) 12204021National Natural Science Foundation of China (National Science Foundation of China) 62235002
6 · The paper itself

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.

Identifiers

PMID37524697
PMCPMC10390475

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.