Evidence map›Paper›PMID 40446046›Full record

ArticleScience advances2025

All-integrated multidimensional optical sensing with a photonic neuromorphic processor.

Zhijuan Gu, Yang Shi, Zhangming Zhu, Zuhang Li, Mingjie Zou, Changming Yang, Yang Liu, Yu Yu, Xinliang Zhang

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

9 authors.

Zhijuan GuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0009-0004-7831-8753
Yang ShiWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0000-0002-1141-6154
Zhangming ZhuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.
Zuhang LiWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0009-0002-6729-0711
Mingjie ZouWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.
Changming YangWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.
Yang LiuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0000-0002-0508-1474
Yu YuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0000-0002-8421-6794
Xinliang ZhangWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China.ORCID 0000-0001-8513-3328

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multidimensional optical sensing is crucial in information technology and modern intelligent systems. Despite advancement in optical sensing, capturing multidimensional light field information remains challenging, typically implemented using cascaded single-dimensional sensors and discrete optoelectrical components for information decoupling. Here, we present an all-integrated multidimensional sensing chip incorporating a light field sensitizer and a photonic neural network processor. The inverse-designed sensitizer projects the multidimensional input into multiple channels; each dimension is then decoupled through the reconfigurable nonlinear neural network. We experimentally achieved 91% high accuracy for single-shot, concurrent sensing of intensity, polarization, and wavelength using a well-trained five-layer neuromorphic system. The fully on-chip system eliminates optical-electrical conversion and offline digital processing, enabling low-latency and high energy efficiency. Moreover, we achieved stabilization and recovery of high-speed signals at 100 gigabytes per second under randomly perturbed polarization and wavelengths. This work shows the potential for low-latency, energy-efficient optical sensing and complex information processing using neuromorphic integrated photonics.

Identifiers

PMID40446046
PMCPMC12124386

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.