A Machine Learning based Study of Vertically Loaded Diamond Microdisk Resonator
We present a machine-learning-driven design, fabrication, and testing pipeline for vertically loaded diamond microdisk resonators. This system achieves a 80% agreement between simulated and measured quality factors and far-field emission profiles, addressing photonic device performance and predictions discrepancies.
Authors
- Kevin C. Chen (ORCID: https://orcid.org/0000-0003-0983-192X)
- Dirk Englund (ORCID: https://orcid.org/0000-0002-1043-3489)
- Yong Hu (ORCID: https://orcid.org/0000-0002-5841-1350)
- Yuqin Duan (ORCID: https://orcid.org/0000-0002-4106-3783)
- Matthew E. Trusheim (ORCID: https://orcid.org/0000-0003-3197-5989)
- Hanfeng Wang (ORCID: https://orcid.org/0000-0003-1456-9882)
- Christopher Espitia-Alvarez
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/cleo_fs.2025.ff106_7
- Primary Topic
- Photonic and Optical Devices
- Type
- article
- Field-Weighted Citation Impact
- 0.00