Nonlinear Computational Edge Detection Metalens. (15th June 2022)
- Record Type:
- Journal Article
- Title:
- Nonlinear Computational Edge Detection Metalens. (15th June 2022)
- Main Title:
- Nonlinear Computational Edge Detection Metalens
- Authors:
- Zhou, Junxiao
Zhao, Junxiang
Wu, Qianyi
Chen, Ching‐Fu
Lei, Ming
Chen, Guanghao
Tian, Fanglin
Liu, Zhaowei - Abstract:
- Abstract: Optical image processing and computing systems provide supreme information processing rates by utilizing parallel optical architectures. Existing optical analog processing techniques require multiple devices for projecting images and executing computations. In addition, those devices are typically limited to linear operations due to the time‐invariant optical responses of the building materials. In this work, a single metalens with an illumination intensity dependent coherent transfer function (CTF) is proposed and experimentally demonstrated, which performs varying computed imaging without requiring any additional optical components. The metalens consisting of nanoantenna structures with a static geometric phase and a nonlinear metallic quantum well layer offering an intensity‐dependent dynamic phase results in a continuously tunable CTF. The approach allows for a weighted summation of two designed functions based on the metalens design, which potentially enables all optical computations of complex functions. The nonlinear metalens may lead to important applications in optical neural networks and parallel analog computing. Abstract : In this work, a single metalens with an illumination intensity dependent coherent transfer function (CTF) is demonstrated, which performs varying computed imaging without requiring any additional optical components. The metalens consists of nanoantenna structures providing a static geometric phase and an extreme nonlinear metallicAbstract: Optical image processing and computing systems provide supreme information processing rates by utilizing parallel optical architectures. Existing optical analog processing techniques require multiple devices for projecting images and executing computations. In addition, those devices are typically limited to linear operations due to the time‐invariant optical responses of the building materials. In this work, a single metalens with an illumination intensity dependent coherent transfer function (CTF) is proposed and experimentally demonstrated, which performs varying computed imaging without requiring any additional optical components. The metalens consisting of nanoantenna structures with a static geometric phase and a nonlinear metallic quantum well layer offering an intensity‐dependent dynamic phase results in a continuously tunable CTF. The approach allows for a weighted summation of two designed functions based on the metalens design, which potentially enables all optical computations of complex functions. The nonlinear metalens may lead to important applications in optical neural networks and parallel analog computing. Abstract : In this work, a single metalens with an illumination intensity dependent coherent transfer function (CTF) is demonstrated, which performs varying computed imaging without requiring any additional optical components. The metalens consists of nanoantenna structures providing a static geometric phase and an extreme nonlinear metallic quantum well layer offering intensity‐dependent dynamic phase, resulting in a continuously tunable CTF. … (more)
- Is Part Of:
- Advanced functional materials. Volume 32:Number 34(2022)
- Journal:
- Advanced functional materials
- Issue:
- Volume 32:Number 34(2022)
- Issue Display:
- Volume 32, Issue 34 (2022)
- Year:
- 2022
- Volume:
- 32
- Issue:
- 34
- Issue Sort Value:
- 2022-0032-0034-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-06-15
- Subjects:
- edge detection -- metalens -- nonlinear
Materials -- Periodicals
Chemical vapor deposition -- Periodicals
620.11 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1616-3028 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adfm.202204734 ↗
- Languages:
- English
- ISSNs:
- 1616-301X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.853900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23427.xml