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Noise characterization of lasers and frequency combs using machine learning
Heebøll, Holger Ribergaard
(PhD Student)
Zibar, Darko
(Main Supervisor)
Da Ros, Francesco
(Supervisor)
Galili, Michael
(Supervisor)
Karlsson, Lars Magnus Ingemar
(Examiner)
Batagelj, Bostjan
(Examiner)
Machine Learning in Photonic Systems
Centre of Excellence for Silicon Photonics for Optical Communications
Department of Electrical and Photonics Engineering
High-Speed Optical Communications
Overview
Fingerprint
Research output
(1)
Project Details
Status
Finished
Effective start/end date
01/10/2021
→
14/01/2025
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Phase Noise
Engineering
100%
Learning System
Engineering
100%
Noise Characterization
Engineering
100%
Frequency Comb
Physics
100%
Machine Learning
Physics
100%
Detection Scheme
Engineering
33%
Measurement Noise
Engineering
33%
Line Spectra
Engineering
33%
Research output
Research output per year
2024
2024
2024
1
Ph.D. thesis
Research output per year
Research output per year
Noise characterization of lasers and frequency combs using machine learning: A PhD Thesis.
Heebøll, H. R.,
2024
,
Technical University of Denmark
.
133 p.
Research output
:
Book/Report
›
Ph.D. thesis
Open Access
File
Phase Noise
100%
Noise Characterization
100%
Learning System
100%
Machine Learning
100%
Frequency Comb
100%
37
Downloads (Pure)