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Neural-Network Based Reflector Design for Finite 2D Sources in Far-Field Illumination

Title: Neural-Network Based Reflector Design for Finite 2D Sources in Far-Field Illumination
Authors: Hacking, Roel; Kusch, Lisa; Mitra, Koondanibha; Anthonissen, Martijn; IJzerman, Wilbert
Source: Hacking, R, Kusch, L, Mitra, K, Anthonissen, M & IJzerman, W 2025, Neural-Network Based Reflector Design for Finite 2D Sources in Far-Field Illumination. in Optica Design and Fabrication Congress 2025 (FlatOptics, Freeform, OFT)., FrW4A.4, Optica Publishing Group, 2025 Freeform Optics, Freeform 2025, Denver, United States, 16/06/25. https://doi.org/10.1364/FREEFORM.2025.FrW4A.4
Publisher Information: Optica Publishing Group
Publication Year: 2025
Description: A novel computational approach for designing reflectors for finite two-dimensional light sources in far-field illumination is proposed. The reflector is parameterized as a multilayer perceptron, and an energy-conserving loss function is optimized, outperforming deconvolution methods.
Document Type: conference object
File Description: application/pdf
Language: English
Relation: info:eu-repo/semantics/altIdentifier/isbn/978-1-957171-45-6
DOI: 10.1364/FREEFORM.2025.FrW4A.4
Availability: https://research.tue.nl/en/publications/52ca64be-2f36-40a9-88e8-ce32b7907569; https://doi.org/10.1364/FREEFORM.2025.FrW4A.4; https://pure.tue.nl/ws/files/383825640/freeform-2025-frw4a.4.pdf; https://www.scopus.com/pages/publications/105032385853
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.57FF3F41
Database: BASE