Mapping the global design space of nanophotonic components using machine learning pattern recognition

Machine learning is increasingly used in nanophotonics for designing novel classes of complex devices but the general parameter behavior is often neglected. Here, the authors report a new methodology to discover and visualize optimal design spaces with respect to multiple performance objectives.

Guardado en:
Detalles Bibliográficos
Autores principales: Daniele Melati, Yuri Grinberg, Mohsen Kamandar Dezfouli, Siegfried Janz, Pavel Cheben, Jens H. Schmid, Alejandro Sánchez-Postigo, Dan-Xia Xu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
Materias:
Q
Acceso en línea:https://doaj.org/article/2abb231657a342b8a35368c0295add15
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!