Evidence map›Paper›PMID 42669732›Full record

ArticleNature communications2026

65 TOPS optoelectronic multi-core computing unlocking multi-feature fusion enhancement.

Xiangyan Meng, Junshen Li, Menghan Yang, Kangwei Fei, Yanzhen Li, Wei Li, Jianping Yao, Ninghua Zhu, Nuannuan Shi, Ming Li

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

10 authors.

Xiangyan MengState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0009-0009-1824-6635
Junshen LiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.
Menghan YangState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.
Kangwei FeiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.
Yanzhen LiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.
Wei LiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.
Jianping YaoMicrowave Photonic Research Laboratory, School of Electrical Engineering and Computer Science, University of Ottawa, 25 Templeton Street, Ottawa, Canada.
Ninghua ZhuState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-1824-8317
Nuannuan ShiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China. nnshi@semi.ac.cn.ORCID http://orcid.org/0000-0003-2557-1734
Ming LiState Key Laboratory of Optoelectronic Materials and Devices, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China. ml@semi.ac.cn.ORCID http://orcid.org/0000-0002-0145-486X

Funding

Beijing Nova Program 20230484321China Postdoctoral Science Foundation 2025M770825, 2025T180231National Natural Science Foundation of China (National Science Foundation of China) 62505309, 62535015National Natural Science Foundation of China (National Science Foundation of China) 92573205, 62235011
6 · The paper itself

Abstract

The rapid progress of artificial intelligence demands scalable, energy-efficient hardware with massive parallelism and high throughput. Although optical computing offers a promising post-Moore solution, current implementations face speed limitations and multi-core integration challenges. Here, we propose a high-throughput optical processing unit (OPU) that simultaneously exploits coherent interference, wavelength-division multiplexing, and spatial parallelism to achieve revolutionary performance gains. Integrating four optical analog cores on a monolithic chip, the OPU supports 124-channel parallel task processing, achieving 65.04 trillion operations per second (TOPS) computational speed and 5.16 TOPS/mm

Identifiers

PMID42669732
PMCPMC13526862

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.