Deep learning to explain and design complex nanophotonic structures

Aaswath P. Raman

doi:10.1117/12.2595477

2 August 2021 Deep learning to explain and design complex nanophotonic structures

Aaswath P. Raman

Proceedings Volume 11795, Metamaterials, Metadevices, and Metasystems 2021; 117950D (2021) https://doi.org/10.1117/12.2595477
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

A central challenge in the development of nanophotonic structures and metamaterials is identifying the optimal design for a target functionality and understanding the physical mechanisms that enable the optimized device’s capabilities. In this talk, we will describe deep learning-driven strategies to both design complex nanophotonic structures, including across multiple device categories, as well as understand their behavior. We will highlight potential pathways to making deep learning a tool for global inverse design across multiple device categories, while also opening up the 'black box' of the machine learning algorithm to understand why a particular optimized design works well.

Conference Presentation

Citation Download Citation

Aaswath P. Raman "Deep learning to explain and design complex nanophotonic structures", Proc. SPIE 11795, Metamaterials, Metadevices, and Metasystems 2021, 117950D (2 August 2021); https://doi.org/10.1117/12.2595477

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available