Deep learning assisted design of high reflectivity metamirrors
- authored by
- L. Shelling Neto, J. Dickmann, S. Kroker
- Abstract
The advent of optical metasurfaces, i.e. carefully designed two-dimensional nanostructures, allows unique control of electromagnetic waves. To unlock the full potential of optical metasurfaces to match even complex optical functionalities, machine learning provides elegant solutions. However, these methods struggle to meet the tight requirements when it comes to metasurface devices for the optical performance, as it is the case, for instance, in applications for high-precision optical metrology. Here, we utilize a tandem neural network framework to render a focusing metamirror with high mean and maximum reflectivity of Rmean = 99.993% and Rmax = 99.9998 %, respectively, and a minimal phase mismatch of Δφ = 0.016% that is comparable to state-of-art dielectric mirrors.
- External Organisation(s)
-
Technische Universität Braunschweig
Laboratory for Emerging Nanometrology Braunschweig (LENA)
Physikalisch-Technische Bundesanstalt PTB
- Type
- Article
- Journal
- Optics express
- Volume
- 30
- Pages
- 986-994
- No. of pages
- 9
- ISSN
- 1094-4087
- Publication date
- 03.01.2022
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic version(s)
-
https://doi.org/10.1364/OE.446442 (Access:
Open)