Deep learning control of THz QCLs

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dc.contributor.authorLimbacher, Benediktcs
dc.contributor.authorSchönhuber, Sebastiancs
dc.contributor.authorKainz, Martin A.cs
dc.contributor.authorBachelard, Nicolascs
dc.contributor.authorAndrews, Aaron Maxwellcs
dc.contributor.authorDetz, Hermanncs
dc.contributor.authorStrasser, Gottfriedcs
dc.contributor.authorDarmo, Jurajcs
dc.contributor.authorUnterrainer, Karlcs
dc.coverage.issue15cs
dc.coverage.volume29cs
dc.date.accessioned2021-12-01T15:56:46Z
dc.date.available2021-12-01T15:56:46Z
dc.date.issued2021-07-19cs
dc.description.abstractArtificial 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.en
dc.formattextcs
dc.format.extent23611-23621cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationOPTICS EXPRESS. 2021, vol. 29, issue 15, p. 23611-23621.en
dc.identifier.doi10.1364/OE.430679cs
dc.identifier.issn1094-4087cs
dc.identifier.other172324cs
dc.identifier.urihttp://hdl.handle.net/11012/203035
dc.language.isoencs
dc.publisherOptica Publishing Groupcs
dc.relation.ispartofOPTICS EXPRESScs
dc.relation.urihttps://www.osapublishing.org/oe/fulltext.cfm?uri=oe-29-15-23611&id=453190cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1094-4087/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectQUANTUM CASCADE LASERSen
dc.subjectTERAHERTZen
dc.subjectBANDen
dc.subjectIMAGEen
dc.subjectLIGHTen
dc.titleDeep learning control of THz QCLsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-172324en
sync.item.dbtypeVAVen
sync.item.insts2021.12.01 16:56:46en
sync.item.modts2021.12.01 16:15:53en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Epitaxní materiály a nanostrukturycs
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Epitaxní materiály a nanostruktury