Titill: | Polarimetry with Disordered Photonic Structures |
Höfundur: |
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Útgáfa: | 2019-12-20 |
Tungumál: | Enska |
Umfang: | 203-211 |
Háskóli/Stofnun: | Háskóli Íslands University of Iceland |
Svið: | Verkfræði- og náttúruvísindasvið (HÍ) School of Engineering and Natural Sciences (UI) |
Deild: | Raunvísindastofnun (HÍ) Science Institute (UI) |
Birtist í: | ACS Photonics;7(1) |
ISSN: | 2330-4022 (eISSN) |
DOI: | 10.1021/acsphotonics.9b01420 |
Efnisorð: | Skautun (rafsegulfræði); Vélrænt nám; Polarimetry; Polarization selective devices; Nanophotonics; Nanótækni; Deep neural networks; Machine learning |
URI: | https://hdl.handle.net/20.500.11815/3297 |
Tilvitnun:Michael Juhl, Kristjan Leosson (2020). Polarimetry with Disordered Photonic Structures. ACS Photonics, 7(1), 203-211. doi: 10.1021/acsphotonics.9b01420
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Útdráttur:In conventional Stokes polarimetry, where the polarimetric information is obtained
from a series of intensity measurements, stable and accurate measurements typically
require the optical elements to be carefully designed. Here, we propose a paradigm
shift where deep neural network assisted polarimeters based on disordered photonic
structures perform high quality polarimetric measurements while completely removing
the need for specially designed polarization analyzers, demonstrating how disordered
photonic structures fabricated without the use of any nanolithography techniques can
enable accurate analysis of optical signals. We implement this concept with disorder-
engineered nano-scatterers that allow for analyzing varying degrees of disorder and cellophane film that demonstrate the cost-saving potential of the concept. We demonstrate
polarimetric performances, calibrated using deep neural networks, that are comparable
to commercial polarimeters, does not require prior knowledge of the input wavelength
and show a high degree of mechanical stability.
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Athugasemdir:Post-print (lokagerð höfundar)
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