Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Machine Learning aided characterization of multi-stage integrated ring resonator filters

Not Accessible

Your library or personal account may give you access

Abstract

Modern optical transmission standards require steep band-pass filters enabling spectrally efficient channels spacing. For this aim, we propose a machine-learning agent to assist in the characterization of complex ring resonator filters to fulfill the transmission requirements.

© 2022 The Author(s)

PDF Article  |   Presentation Video
More Like This
Machine Learning Aided Prediction of Fabrication Uncertainties in Integrated Multi-Ring Filters

Lorenzo Tunesi, Ihtesham Khan, Muhammad Umar Masood, Andrea Marchisio, Enrico Ghillino, Vittorio Curri, Andrea Carena, and Paolo Bardella
STh4H.2 CLEO: Science and Innovations (CLEO:S&I) 2023

Machine-Learning-Aided Service Provisioning in Multi-Domain Optical Networks

Roberto Proietti, Xiaoliang Chen, Gengchen Liu, Hongbo Lu, and S.J. Ben Yoo
NeT1D.4 Photonic Networks and Devices (Networks) 2019

Tutorial: Evolution of Machine Learning in Optical Access Networks

Elaine Wong, Lihua Ruan, and Sourav Mondal
W3G.1 Optical Fiber Communication Conference (OFC) 2022

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads


More Like This
Machine Learning Aided Prediction of Fabrication Uncertainties in Integrated Multi-Ring Filters

Lorenzo Tunesi, Ihtesham Khan, Muhammad Umar Masood, Andrea Marchisio, Enrico Ghillino, Vittorio Curri, Andrea Carena, and Paolo Bardella
STh4H.2 CLEO: Science and Innovations (CLEO:S&I) 2023

Machine-Learning-Aided Service Provisioning in Multi-Domain Optical Networks

Roberto Proietti, Xiaoliang Chen, Gengchen Liu, Hongbo Lu, and S.J. Ben Yoo
NeT1D.4 Photonic Networks and Devices (Networks) 2019

Tutorial: Evolution of Machine Learning in Optical Access Networks

Elaine Wong, Lihua Ruan, and Sourav Mondal
W3G.1 Optical Fiber Communication Conference (OFC) 2022

Silicon Photonics for Machine Learning: Training and Inference

B. J. Shastri, M. J. Filipovich, Z. Guo, P. R. Prucnal, C. Huang, A. N. Tait, S. Shekhar, and V. J. Sorger
Tu4G.1 European Conference and Exhibition on Optical Communication (ECOC) 2022

Experimental Demonstration of Learned Pulse Shaping Filter for Superchannels

Zonglong He, Jinxiang Song, Christian Häger, Alexandre Graell i Amat, Henk Wymeersch, Peter A. Andrekson, Magnus Karlsson, and Jochen Schröder
W2A.33 Optical Fiber Communication Conference (OFC) 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.