Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • OSA Optical Design and Fabrication 2021 (Flat Optics, Freeform, IODC, OFT)
  • OSA Technical Digest (Optica Publishing Group, 2021),
  • paper 120781B
  • https://doi.org/10.1117/12.2603658

Robustness Estimation of Simple Lens Systems by Machine Learning

Not Accessible

Your library or personal account may give you access

Abstract

Tolerance analysis and tolerance sensitivity optimization (desensitization) are important and necessary for manufacturability. However, compared to the optimization of optical performance, tolerance analysis is still time- consuming. A machine learning approach for the fast robustness estimation of lens systems is proposed. The results of the machine learning estimation and the other four different methods are compared with the results of the Monte Carlo analysis. The proposed model is added to the merit function in commercial software for optimization to reduce the sensitivity.

© 2021 SPIE

PDF Article  |   Presentation Video
More Like This
Comparison of Different Methods for Robustness Estimation of Simple Lens Systems

Hans-Georg König, Chia-Wei Chen, Martin Holters, Jochen Stollenwerk, and Peter Loosen
IM3A.6 International Optical Design Conference (IODC) 2017

Machine Learning-based Fiber-Wireless Channel Estimation

Luiz Augusto Melo Pereira, Luciano Leonel Mendes, and Arismar Cerqueira Sodré Junior
JTu1A.32 Frontiers in Optics (FiO) 2021

On the Use of Deep Learning for Lens Design

Geoffroi Côté, Jean-François Lalonde, and Simon Thibault
120781A International Optical Design Conference (IODC) 2021

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
Comparison of Different Methods for Robustness Estimation of Simple Lens Systems

Hans-Georg König, Chia-Wei Chen, Martin Holters, Jochen Stollenwerk, and Peter Loosen
IM3A.6 International Optical Design Conference (IODC) 2017

Machine Learning-based Fiber-Wireless Channel Estimation

Luiz Augusto Melo Pereira, Luciano Leonel Mendes, and Arismar Cerqueira Sodré Junior
JTu1A.32 Frontiers in Optics (FiO) 2021

On the Use of Deep Learning for Lens Design

Geoffroi Côté, Jean-François Lalonde, and Simon Thibault
120781A International Optical Design Conference (IODC) 2021

Machine learning Assisted Accurate Estimation of QoT Impairments of Photonics Switching System on 400ZR

Ihtesham Khan, Lorenzo Tunesi, M Umar Masood, Enrico Ghillino, Paolo Bardella, Andrea Carena, and Vittorio Curri
T2B.2 Asia Communications and Photonics Conference (ACP) 2021

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.