Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
  • OSA Technical Digest (Optica Publishing Group, 2019),
  • paper pd_1_5

Fully Phase Stabilized Quantum Cascade Laser Frequency Comb

Not Accessible

Your library or personal account may give you access

Abstract

The road towards the realization of quantum cascade laser (QCL) frequency combs [1,2] has undoubtedly attracted ubiquitous attention from the scientific community. These devices promise to deliver an all-in-one (i.e. a single, miniature, active device) frequency comb synthesizer in a range as wide as the QCL spectral coverage itself (from about 4 microns to the THz range), with the unique possibility to tailor their spectral emission by band structure engineering. For these reasons, vigorous efforts have been spent to characterize the emission of four-wave-mixing (FWM) multi-frequency QCLs, aiming to seize their comb-like mode-locked operation [3-6].

© 2019 IEEE

PDF Article
More Like This
Optical-feedback-stabilized quantum cascade laser frequency combs

Chu C. Teng, Jonas Westberg, and Gerard Wysocki
STu4N.3 CLEO: Science and Innovations (CLEO:S&I) 2019

Fully stabilized dual-comb spectrometer based on a mid-IR quantum-cascade-laser frequency comb

G. Villares, A. Hugi, S. Blaser, H. C. Liu, and J. Faist
CH_1_2 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 2013

Retrieving the phase relation of a quantum cascade laser frequency comb and reconstructing its emission profile

Francesco Cappelli, Luigi Consolino, Giulio Campo, Iacopo Galli, Davide Mazzotti, Annamaria Campa, Mario Siciliani de Cumis, Pablo Cancio Pastor, Roberto Eramo, Markus Rösch, Mattias Beck, Giacomo Scalari, Jérôme Faist, Paolo De Natale, and Saverio Bartalini
ed_5_4 European Quantum Electronics Conference (EQEC) 2019

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.