| Lien | Lien vers l’ensemble de données |
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| Auteur | Rechercher : Conseil national de recherches Canada. Technologies numériques. Intelligence artificielle au service de la conception |
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| Format | Texte, Ensemble de données |
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| Sujet | artificial neural networks; machine learning; metamaterials; optimization algorithms |
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| Résumé | This repository provides Python code accompanying the tutorial paper on inverse photonic design using neural networks, as described in the associated manuscript.
This tutorial is structured into clear steps corresponding to the sections of the paper, covering:
Forward Model: Training a neural network model to predict TE coupling coefficients from geometry parameters.
Simple forward model (N_MODELS = 1, AUGMENT_DATA = False)
Simple forward model with data augmentation (N_MODELS = 1, AUGMENT_DATA = True)
Ensemble forward model (N_MODELS > 1, AUGMENT_DATA = True recommended)
Inverse Model: Predicting geometry parameters from specified TE coupling coefficients.
Simple inverse neural network (without tandem)
Tandem inverse neural network (with pre-trained forward network)
The provided Python script allows you to reproduce these examples directly, using simple flags and parameters. Additionally, the folder ./Simulations_setup contains example code and needed scripts to run Ansys Lumerical simulations for data generation. |
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| Date de publication | 2025 |
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| Maison d’édition | National Research Council Canada |
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| Licence | |
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| Publication connexe | |
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| Langue | anglais |
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| Exporter la notice | Exporter en format RIS |
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| Collection | Données de recherche du CNRC |
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| Identificateur de l’enregistrement | fa8351c4-8d49-405e-b0a7-37cf288caa5b |
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| Enregistrement créé | 2025-10-28 |
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| Enregistrement modifié | 2025-11-21 |
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