Publication detail

Deep learning control of THz QCLs

LIMBACHER, B. SCHÖNHUBER, S. KAINZ, M. BACHELARD, N. ANDREWS, A. DETZ, H. STRASSER, G. DARMO, J. UNTERRAINER, K.

Original Title

Deep learning control of THz QCLs

Type

journal article in Web of Science

Language

English

Original 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. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License.

Keywords

QUANTUM CASCADE LASERS; TERAHERTZ; BAND; IMAGE; LIGHT

Authors

LIMBACHER, B.; SCHÖNHUBER, S.; KAINZ, M.; BACHELARD, N.; ANDREWS, A.; DETZ, H.; STRASSER, G.; DARMO, J.; UNTERRAINER, K.

Released

19. 7. 2021

Publisher

Optica Publishing Group

Location

WASHINGTON

ISBN

1094-4087

Periodical

OPTICS EXPRESS

Year of study

29

Number

15

State

United States of America

Pages from

23611

Pages to

23621

Pages count

11

URL

Full text in the Digital Library

BibTex

@article{BUT172324,
  author="Benedikt {Limbacher} and Sebastian {Schönhuber} and Martin A. {Kainz} and Nicolas {Bachelard} and Aaron Maxwell {Andrews} and Hermann {Detz} and Gottfried {Strasser} and Juraj {Darmo} and Karl {Unterrainer}",
  title="Deep learning control of THz QCLs",
  journal="OPTICS EXPRESS",
  year="2021",
  volume="29",
  number="15",
  pages="23611--23621",
  doi="10.1364/OE.430679",
  issn="1094-4087",
  url="https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-29-15-23611&id=453190"
}