Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • European Conference on Optical Communication (ECOC) 2022
  • Technical Digest Series (Optica Publishing Group, 2022),
  • paper We5.14

Pre-Fabrication Performance Verification of a Topologically Optimized Mode Demultiplexer Using Deep Neural Networks

Not Accessible

Your library or personal account may give you access

Abstract

Photonics miniaturization benefits from topological inverse design that favours the use of small, difficult-to-fabricate features. We use machine learning to predict the fabrication of a topologically optimized mode demultiplexer, then re-simulate and validate its optical performance for cost-efficient pre-selection of design prior to fabrication.

© 2022 The Author(s)

PDF Article
More Like This
Deep Neural Networks for the Topological Optimization of Metasurfaces

Timo Gahlmann and Philippe Tassin
NoM3C.4 Novel Optical Materials and Applications (NOMA) 2022

Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks

Vinod Bajaj, Mathieu Chagnon, Sander Wahls, and Vahid Aref
M1H.3 Optical Fiber Communication Conference (OFC) 2022

Performance Analysis of Recurrent Neural Network-based Digital Pre-Distortion for Optical Coherent Transmission

Vinod Bajaj, Vahid Aref, and Sander Wahls
Th2C.1 European Conference and Exhibition on Optical Communication (ECOC) 2022

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.