Song, Jialin and Tokpanov, Yury S. and Chen, Yuxin and Fleischman, Dagny and Fountaine, Kate T. and Atwater, Harry A. and Yue, Yisong (2018) Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes. . (Submitted) https://resolver.caltech.edu/CaltechAUTHORS:20190205-101105728
![]() |
PDF
- Submitted Version
See Usage Policy. 824kB |
Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20190205-101105728
Abstract
We apply numerical methods in combination with finite-difference-time-domain (FDTD) simulations to optimize transmission properties of plasmonic mirror color filters using a multi-objective figure of merit over a five-dimensional parameter space by utilizing novel multi-fidelity Gaussian processes approach. We compare these results with conventional derivative-free global search algorithms, such as (single-fidelity) Gaussian Processes optimization scheme, and Particle Swarm Optimization---a commonly used method in nanophotonics community, which is implemented in Lumerical commercial photonics software. We demonstrate the performance of various numerical optimization approaches on several pre-collected real-world datasets and show that by properly trading off expensive information sources with cheap simulations, one can more effectively optimize the transmission properties with a fixed budget.
Item Type: | Report or Paper (Discussion Paper) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Related URLs: |
| ||||||||
ORCID: |
| ||||||||
Record Number: | CaltechAUTHORS:20190205-101105728 | ||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190205-101105728 | ||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||
ID Code: | 92659 | ||||||||
Collection: | CaltechAUTHORS | ||||||||
Deposited By: | Tony Diaz | ||||||||
Deposited On: | 05 Feb 2019 19:09 | ||||||||
Last Modified: | 09 Mar 2020 13:19 |
Repository Staff Only: item control page