Published May 2020
| Published
Book Section - Chapter
Open
Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models
Abstract
We designed mirrored plasmonic filters using an advanced active machine learning algorithm that efficiently explores multiple physical models with different approximation fidelities and costs. This method is applicable to a variety of nanophotonics optimization problems.
Additional Information
© 2020 The Author(s).Attached Files
Published - 09192854.pdf
Files
09192854.pdf
Files
(570.8 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:d611a502c8bdd2587599985377864173
|
570.8 kB | Preview Download |
Additional details
- Eprint ID
- 105497
- Resolver ID
- CaltechAUTHORS:20200923-131223809
- Created
-
2020-09-23Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field