Deep learning control of THz QCLs
Abstract
Artificial neural networks are capable of fitting highly non-linear and complex systems. Such complicated systems can be found everywhere in nature, including the non-linear interaction between optical modes in laser resonators. In this work, we demonstrate artificial neural networks trained to model these complex interactions in the cavity of a Quantum Cascade Random Laser. The neural networks are able to predict modulation schemes for desired laser spectra in real-time. This radically novel approach makes it possible to adapt spectra to individual requirements without the need for lengthy and costly simulation and fabrication iterations.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 09, 2021
- Source ID
- 10.1364/oe.430679
Entities
People
- Aaron Maxwell Andrews
- B Limbacher
- Gottfried Strasser
- Hermann Detz
- Juraj Darmo
- Karl Unterrainer
- Martin A Kainz
- Nicolas Bachelard
- Sebastian Schoenhuber
Organizations
- Air Force Office of Scientific Research
- Austrian Research Promotion Agency
- Austrian Science Fund
- Brno University of Technology
- Horizon 2020