Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning

In this paper, we introduce a novel approach to model bending phenomena on holographic volume gratings based on Rigorous Coupled Wave Analysis (RCWA), in which the bending as a phase in the dielectric permittivity expansion is introduced, and the Shooting Method (SM) is employed to solve the resulting system of equations. Further validation of our model is conducted by comparing its predictions to those obtained from reference Finite-Difference Time-Domain (FDTD) simulations and Coupled Wave Theory (CWT, referring to Kubota’s model that includes the bending phenomenon). Furthermore, we propose a methodology for estimating the bending from the diffraction efficiency curves in transmission volume gratings based on deep learning models, with a subsequent study of their accuracy and applicability.

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Publication Details

Journal
Applied Sciences
Published
2024-11-11
DOI
https://doi.org/10.3390/app142210356
Citations
1
Primary Topic
Optical Coatings and Gratings
Type
article
Field-Weighted Citation Impact
0.18

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article

Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning

Augusto Beléndez, Cristian Neipp, Jaume Colomina-Martínez, Jorge Francés et al.
1 citations
Applied Sciences
Optical Coatings and Gratings
0.18
article

Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning

Augusto Beléndez, Cristian Neipp, Jaume Colomina-Martínez, Jorge Francés, Joan Josep Sirvent-Verdú, Juan Carlos Bravo, Adrián Moya
article en
1 citations

Abstract

In this paper, we introduce a novel approach to model bending phenomena on holographic volume gratings based on Rigorous Coupled Wave Analysis (RCWA), in which the bending as a phase in the dielectric permittivity expansion is introduced, and the Shooting Method (SM) is employed to solve the resulting system of equations. Further validation of our model is conducted by comparing its predictions to those obtained from reference Finite-Difference Time-Domain (FDTD) simulations and Coupled Wave Theory (CWT, referring to Kubota’s model that includes the bending phenomenon). Furthermore, we propose a methodology for estimating the bending from the diffraction efficiency curves in transmission volume gratings based on deep learning models, with a subsequent study of their accuracy and applicability.

Applied SciencesVol. 14(22)
University of Alicante (ES)
Ministerio de Ciencia, Innovación y Universidades, Generalitat Valenciana
Openalex Percentile: Top 51%
Optical Coatings and Gratings
0.18
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Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning — Augusto Beléndez, Cristian Neipp, et al. · Applied Sciences (2024) | TGRS Research Map | TGRS