Gaussian Process Regression for the Modeling of Metalenses

A. Al-Zawqari; G. Vandersteen; F. Ferranti

doi:10.1109/PIERS59004.2023.10221545

Gaussian Process Regression for the Modeling of Metalenses

A. Al-Zawqari, G. Vandersteen, F. Ferranti

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

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Abstract

Metasurfaces have attracted a lot of attention due to their exceptional capability to manipulate the amplitude, phase, and polarization of light. In the domain of imaging, metasurface-based lenses, also called metalenses have become a very promising technology for multifunctional and compact imaging devices. In this work, Gaussian process regression (GPR) models are investigated to model quantities of interest to describe the electromagnetic behavior of metalenses. Single output and multitask (multioutput) GPR models are explored. Pertinent numerical results will be presented to validate the proposed GPR modeling for metalenses.

Original language	English
Title of host publication	2023 Photonics & Electromagnetics Research Symposium (PIERS)
Publisher	IEEE
Pages	49-53
Number of pages	5
ISBN (Print)	979-835031284-3
DOIs	https://doi.org/10.1109/PIERS59004.2023.10221545
Publication status	Published - 3 Jul 2023
Event	2023 Photonics & Electromagnetics Research Symposium (PIERS) - Duration: 3 Jul 2023 → 6 Jul 2023

Publication series

Name	2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings

Conference

Conference	2023 Photonics & Electromagnetics Research Symposium (PIERS)
Period	3/07/23 → 6/07/23

Bibliographical note

Funding Information:
This work was supported by the Methusalem and Hercules foundations, the OZR of the Vrije Universiteit Brussel (VUB), and the Strategic Research Program of the VUB (SRP19 and SRP78).

Publisher Copyright:
© 2023 IEEE.

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10.1109/PIERS59004.2023.10221545

PIERS 2023 GPRAccepted author manuscript, 1.08 MB

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@inproceedings{3fce910300a74d32bbd29c4aba863032,

title = "Gaussian Process Regression for the Modeling of Metalenses",

abstract = "Metasurfaces have attracted a lot of attention due to their exceptional capability to manipulate the amplitude, phase, and polarization of light. In the domain of imaging, metasurface-based lenses, also called metalenses have become a very promising technology for multifunctional and compact imaging devices. In this work, Gaussian process regression (GPR) models are investigated to model quantities of interest to describe the electromagnetic behavior of metalenses. Single output and multitask (multioutput) GPR models are explored. Pertinent numerical results will be presented to validate the proposed GPR modeling for metalenses. ",

author = "A. Al-Zawqari and G. Vandersteen and F. Ferranti",

note = "Funding Information: This work was supported by the Methusalem and Hercules foundations, the OZR of the Vrije Universiteit Brussel (VUB), and the Strategic Research Program of the VUB (SRP19 and SRP78). Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Photonics & Electromagnetics Research Symposium (PIERS) ; Conference date: 03-07-2023 Through 06-07-2023",

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month = jul,

day = "3",

doi = "10.1109/PIERS59004.2023.10221545",

language = "English",

isbn = "979-835031284-3",

series = "2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings",

publisher = "IEEE",

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Al-Zawqari, A , Vandersteen, G & Ferranti, F 2023, Gaussian Process Regression for the Modeling of Metalenses. in 2023 Photonics & Electromagnetics Research Symposium (PIERS). 2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings, IEEE, pp. 49-53, 2023 Photonics & Electromagnetics Research Symposium (PIERS), 3/07/23. https://doi.org/10.1109/PIERS59004.2023.10221545

TY - GEN

T1 - Gaussian Process Regression for the Modeling of Metalenses

AU - Al-Zawqari, A.

AU - Vandersteen, G.

AU - Ferranti, F.

N1 - Funding Information: This work was supported by the Methusalem and Hercules foundations, the OZR of the Vrije Universiteit Brussel (VUB), and the Strategic Research Program of the VUB (SRP19 and SRP78). Publisher Copyright: © 2023 IEEE.

PY - 2023/7/3

Y1 - 2023/7/3

N2 - Metasurfaces have attracted a lot of attention due to their exceptional capability to manipulate the amplitude, phase, and polarization of light. In the domain of imaging, metasurface-based lenses, also called metalenses have become a very promising technology for multifunctional and compact imaging devices. In this work, Gaussian process regression (GPR) models are investigated to model quantities of interest to describe the electromagnetic behavior of metalenses. Single output and multitask (multioutput) GPR models are explored. Pertinent numerical results will be presented to validate the proposed GPR modeling for metalenses.

AB - Metasurfaces have attracted a lot of attention due to their exceptional capability to manipulate the amplitude, phase, and polarization of light. In the domain of imaging, metasurface-based lenses, also called metalenses have become a very promising technology for multifunctional and compact imaging devices. In this work, Gaussian process regression (GPR) models are investigated to model quantities of interest to describe the electromagnetic behavior of metalenses. Single output and multitask (multioutput) GPR models are explored. Pertinent numerical results will be presented to validate the proposed GPR modeling for metalenses.

UR - http://dx.doi.org/10.1109/piers59004.2023.10221545

UR - http://www.scopus.com/inward/record.url?scp=85171980252&partnerID=8YFLogxK

U2 - 10.1109/PIERS59004.2023.10221545

DO - 10.1109/PIERS59004.2023.10221545

M3 - Conference paper

SN - 979-835031284-3

T3 - 2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings

SP - 49

EP - 53

BT - 2023 Photonics & Electromagnetics Research Symposium (PIERS)

PB - IEEE

T2 - 2023 Photonics & Electromagnetics Research Symposium (PIERS)

Y2 - 3 July 2023 through 6 July 2023

ER -

Gaussian Process Regression for the Modeling of Metalenses

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SRP78: SRP-Onderzoekszwaartepunt: Center for model-based system improvement - From Computer-Aided Engineering to Model Aided Engineering

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Gaussian Process Regression for the Modeling of Metalenses

Abstract

Publication series

Conference

Bibliographical note

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Projects

SRP78: SRP-Onderzoekszwaartepunt: Center for model-based system improvement - From Computer-Aided Engineering to Model Aided Engineering

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