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 ef_5_6

Brightness enhancement in Non-Hermitian VCSELs

Not Accessible

Your library or personal account may give you access

Abstract

Vertical Cavity Surface Emitting lasers (VCSELs) are compact and efficient light sources useful for a variety of applications. However, due to lack of a transverse mode control mechanism, such lasers suffer from poor spatial beam quality, intrinsic spatiotemporal instabilities and nonlinear destabilizing effects such as filamentation and spatial hole burning [1]. Therefore, there is a need for new strategies to manipulate the light wave dynamics to enhance the stability of VCSELs. Recently, non-Hermitian media have become a flexible platform for new functionalities such as asymmetric coupling, unidirectional invisibility, single mode lasing [2-3]. In this presentation, we propose a novel stabilization mechanism for VCSLEs to obtain bright and narrow beams. The mechanism relies on non-Hermitian configuration of the laser potential, achieved by simultaneous spatial modulation of the refractive index and gain-loss profiles.

© 2019 IEEE

PDF Article
More Like This
Non-Hermitian Engineered TCC VCSEL for LIDAR Remote Sensing Technologies

Mohammad H. Teimourpour, Hamed Dalir, Elham Heidari, Volker J. Sorger, and Ray T. Chen
FTu3B.7 CLEO: QELS_Fundamental Science (CLEO:FS) 2019

Non-Hermitian-enhanced photonic zero mode

Mingsen Pan, Han Zhao, Pei Miao, Stefano Longhi, and Liang Feng
FM1B.3 CLEO: QELS_Fundamental Science (CLEO:FS) 2019

Non-Hermitian Topologically Enhanced Sensing

Midya Parto, Christian Leefmans, James Williams, and Alireza Marandi
FM4B.4 CLEO: Fundamental Science (CLEO:FS) 2023

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.