Controlling the minimal feature sizes in adjoint optimization of nanophotonic devices using b-spline surfaces

Abstract

Adjoint optimization is an effective method in the inverse design of nanophotonic devices. In order to ensure the manufacturability, one would like to have control over the minimal feature sizes. Here we propose utilizing a level-set method based on b-spline surfaces in order to control the feature sizes. This approach is first used to design a wavelength demultiplexer. It is also used to implement a nanophotonic structure for artificial neural computing. In both cases, we show that the minimal feature sizes can be easily parameterized and controlled.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 25, 2020
Source ID
10.1364/oe.384438

Entities

People

  • Erfan Khoram
  • Ming Yuan
  • Xiaoping Qian
  • Zongfu Yu

Organizations

  • Defense Advanced Research Projects Agency
  • National Science Foundation

Tags

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Nanoscale Plasmonic Nanotechnology
  • Neural Network Machine Learning.