Evidence map›Paper›PMID 40835822›Full record

ArticleNature communications2025

Disordered-guiding photonic chip enabled high-dimensional light field detection.

Zhijuan Gu, Weilun Zhang, Yu Yu, Xinliang Zhang

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Zhijuan GuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074, Wuhan, China.ORCID http://orcid.org/0009-0004-7831-8753
Weilun ZhangWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074, Wuhan, China.
Yu YuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074, Wuhan, China. yuyu@mail.hust.edu.cn.ORCID http://orcid.org/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 http://orcid.org/0000-0001-8513-3328

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62135004
6 · The paper itself

Abstract

Full characterization of light intensity, polarization, and spectrum is essential for applications in sensing, communication and imaging. However, existing schemes rely on discrete, bulky components to capture polarization and spectrum separately, and suffer from detecting only a few values in each dimension. Here, we implement a compact disordered-guiding photonic chip with a neural network for single-shot high-dimensional light field detection. The disordered region introduces complex interference and scattering among polarized components, while the guiding region efficiently collects the outputs to on-chip photodetectors. This design encodes high-dimensional input into multi-channel intensities with high sensitivity, subsequently decoded by the neural network. Experimentally, the accurate detection of broad spectrum with mixed full-Stokes polarization states is realized with a polarization error of 1.2° and spectral resolution as high as 400 pm. Furthermore, the device demonstrates high-dimensional imaging with superior recognition performance over single-dimensional methods. This innovation offers a compact and high-resolution solution for high-dimensional detection.

Identifiers

PMID40835822
PMCPMC12367990

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.