Real-time intensity domain characterization of fibre lasers using spatio-temporal dynamics

Srikanth Sugavanam*, Nikita Tarasov, Dmitry V. Churkin

*Corresponding author for this work

Research output: Contribution to journalSpecial issue

Abstract

Fibre lasers are light sources that are synonymous with stability. They can give rise to highly coherent continuous-wave radiation, or a stable train of mode locked pulses with well-defined characteristics. However, they can also exhibit an exceedingly diverse range of nonlinear operational regimes spanning a multi-dimensional parameter space. The complex nature of the dynamics poses significant challenges in the theoretical and experimental studies of such systems. Here, we demonstrate how the real-time experimental methodology of spatio-temporal dynamics can be used to unambiguously identify and discern between such highly complex lasing regimes. This two-dimensional representation of laser intensity allows the identification and tracking of individual features embedded in the radiation as they make round-trip circulations inside the cavity. The salient features of this methodology are highlighted by its application to the case of Raman fibre lasers and a partially mode locked ring fibre laser operating in the normal dispersion regime.
Original languageEnglish
Article number65
Number of pages15
JournalApplied Sciences
Volume6
Issue number3
DOIs
Publication statusPublished - 25 Feb 2016

Bibliographical note

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

ERC project ULTRALASER, H2020 project CARDIALLY, Russian Ministry of Science and Education (14.584.21.0014); Russian Foundation for Basic Research (projects 16-32-60153, 15-02-07925).

Keywords

  • fibre lasers
  • real-time characterization
  • nonlinear dynamics
  • spatio-temporal dynamics
  • self-organization
  • pattern formation

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