A Deep Mixture Density Network for On-Demand Inverse Design of Thin Film Reflectors

Rohit Unni; Rohit Unni; Kan Yao; Kan Yao; Yuebing Zheng; Yuebing Zheng

doi:10.1364/CLEO_AT.2021.JTu3A.120

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2021),
paper JTu3A.120
•https://doi.org/10.1364/CLEO_AT.2021.JTu3A.120

A Deep Mixture Density Network for On-Demand Inverse Design of Thin Film Reflectors

Rohit Unni, Kan Yao, and Yuebing Zheng

CLEO: Applications and Technology 2021

San Jose, California United States
9–14 May 2021
ISBN: 978-1-943580-91-0

From the session
Joint Poster Session I (JTu3A)

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
R. Unni, K. Yao, and Y. Zheng, "A Deep Mixture Density Network for On-Demand Inverse Design of Thin Film Reflectors," in Conference on Lasers and Electro-Optics, J. Kang, S. Tomasulo, I. Ilev, D. Müller, N. Litchinitser, S. Polyakov, V. Podolskiy, J. Nunn, C. Dorrer, T. Fortier, Q. Gan, and C. Saraceno, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JTu3A.120.

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Get Video
Citation alert
Save article

Abstract

We report a mixture density neural network trained for on-demand inverse design of thin film reflectors, able to retrieve accurate designs and independently reproduce conventional design methods based on physical principles.

PDF Article | Presentation Video

More Like This

Inverse design for integrated photonics using deep neural network

Keisuke Kojima, Toshiaki Koike-Akino, Yingheng Tang, and Ye Wang
IF3A.6 Integrated Photonics Research, Silicon and Nanophotonics (IPR) 2021

Deep Convolutional Neural Network for the Inverse Design of Layered Photonic Structures

Rohit Unni, Kan Yao, and Yuebing Zheng
JW2D.14 CLEO: Applications and Technology (CLEO:A&T) 2020

OTF Gym: A Set of Reinforcement Learning Environment of Layered Optical Thin Film Inverse Design

Anqing Jiang, Liangyao Chen, and Osamu Yoshie
SM1Q.7 CLEO: Science and Innovations (CLEO:S&I) 2021

Previous Article Next Article

Poster Presentation

Media 1: PDF (4812 KB)

Presentation Video

Presentation video access is available to:

Optica Publishing Group subscribers
Technical meeting attendees
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