Evidence map›Paper›PMID 40314979›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Metasurface-assisted multimodal quantum imaging.

Yifan Zhou, Xiaoshu Zhu, Tianyue Li, Zhou Zhou, Qianhui Bi, Jun Liu, Jian Chen, Boyan Fu, Juanzi He, Xiaojing Feng and 7 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

17 authors.

Yifan Zhou *National Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Xiaoshu Zhu *National Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Tianyue LiNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.ORCID 0000-0001-7682-7483
Zhou ZhouDepartment of Electrical and Computer Engineering, National University of Singapore, Kent Ridge 117583, Singapore.ORCID 0009-0000-8405-541X
Qianhui BiNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Jun LiuNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Jian ChenDepartment of Electrical and Computer Engineering, National University of Singapore, Kent Ridge 117583, Singapore.
Boyan FuNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Juanzi HeNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Xiaojing FengNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Xinyang FengNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Xingyu LiuNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Qianjin WangNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Shuming WangNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Zhenlin WangNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.
Cheng-Wei QiuDepartment of Electrical and Computer Engineering, National University of Singapore, Kent Ridge 117583, Singapore.ORCID 0000-0002-6605-500X
Shining ZhuNational Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China.ORCID 0000-0002-3472-6497

Funding

A*STAR MTC IRG M22K2c0088 with A-8001322-00-00JST | Jiangsu Provincial Key Research and Development Program (Key Technologies R&D Program of Jiangsu Province) BG2024029JST | Natural Science Foundation of Jiangsu Province (Jiangsu Natural Science Foundation) BK20233001MOST | National Natural Science Foundation of China (NSFC) 12325411 62288101 11774162National program on key basic research project of China 2022YFA1404300PMO | National Research Foundation Singapore (NRF) NRF-CRP22-2019-0006PMO | National Research Foundation Singapore (NRF) NRF-CRP26-2021-0004PMO | National Research Foundation Singapore (NRF) NRF-CRP30-2023-0003
6 · The paper itself

Abstract

Traditional quantum imaging is featured by remarkable sensitivity and signal-to-noise ratio, but limited by bulkiness and static function (either phase contrast imaging or edge detection). Our report synergizes a polarization-entangled source with a metasurface consisting of various sophisticatedly engineered spatial frequency segments. By tuning polarization, we demonstrate multiple "on"-state quantum imaging modes, enabling flexible switching between phase contrast, edge, and arbitrary superimposed imaging mode. Furthermore, the "off"-state, which characterizes the background noise, enables self-calibration of the system by subtracting this noise in "on"-state modes, resulting in self-enhanced edge detection. Our approach performs phase contrast imaging with a phase difference of π/4 present in the target object, and edge imaging capable of detecting tiny (radius about 2 μm) defects, maintaining high image contrast (phase contrast of 0.726, and enhanced edge contrast of 0.902). Our results provide insights into constructive duet between quantum imaging and metaoptics.

Indexed as

metasurfacemultimodal imagingquantum imagingquantum optics

Identifiers

PMID40314979
PMCPMC12067218

What OpenQuestion holds

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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.