Evidence map›Paper›PMID 42285961›Full record

ArticleNature communications2026

Large-scale integrated optoelectronic chaos for machine learning acceleration.

Zhouyang Pan, Zhekai Zheng, Ping Li, Hao Wang, Jiacheng Guo, Ding Cui, Zhihui Li, Jiaqi Shen, Lihan Wang, Mengya Zong and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Zhouyang Pan *National Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Zhekai Zheng *National Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Ping LiNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Hao WangDepartment of Precision Instrument, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0003-0210-3372
Jiacheng GuoNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Ding CuiNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Zhihui LiUnited Microelectronics Center, Chongqing, China.
Jiaqi ShenNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Lihan WangNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Mengya ZongNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Simin LiNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Zhe KangNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Yue YuanDepartment of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Jianqi HuDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.ORCID http://orcid.org/0000-0002-2018-253X
Jijun HeNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China. jijun.he@nuaa.edu.cn.ORCID http://orcid.org/0000-0001-7011-4386
Yuxin LiangUnited Microelectronics Center, Chongqing, China. yuxin.liang@cumec.cn.
Dan ZhuNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China. danzhu@nuaa.edu.cn.
Shilong PanNational Key Laboratory of Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing, China. pans@nuaa.edu.cn.ORCID http://orcid.org/0000-0003-2620-7272

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62271249National Natural Science Foundation of China (National Science Foundation of China) 62571238Natural Science Foundation of Jiangsu Province (Jiangsu Provincial Natural Science Foundation) BK20220076Natural Science Foundation of Jiangsu Province (Jiangsu Provincial Natural Science Foundation) BK20232033
6 · The paper itself

Abstract

Chaos has emerged as a useful resource for machine learning, yet traditional nonlinear circuits face speed bottlenecks. Optical chaos sources offer an attractive alternative with ultra-wideband operation and massive parallelism, but existing schemes must trade single-channel throughput against multi-channel scalability. Here, we demonstrate an integrated microcomb-optoelectronic chaos engine (iMOCE). By driving an optoelectronic nonlinear cavity with a chaotic microcomb, the iMOCE generates massively parallel chaos with a 6-dB bandwidth of 25 GHz per channel, representing a two-order-of-magnitude improvement over previous microcomb-based approaches. The system delivers a total random-bit generation rate of 32.768 Tbps and accelerates four representative tasks. Compared with MCU/GPU baselines, it reduces per-inference time by about two orders of magnitude. These results establish iMOCE as a scalable, massively parallel chaos primitive for machine learning acceleration.

Identifiers

PMID42285961
PMCPMC13408576

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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.