Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 14,
  • Issue 9,
  • pp. 090601-
  • (2016)

Non-linear polarization orthogonality loss in a semiconductor optical amplifier

Not Accessible

Your library or personal account may give you access

Abstract

Polarization-based optical communications are attracting more attention recently, where the crucial points are polarization features and their measurements. Based on the Müller matrix method, we obtain measurable expressions for the polarization-dependent gain (PDG) and the loss of polarization orthogonality (LPO), while give the boundary of the LPO for any PDG devices. We experimentally demonstrate that non-linear LPO can be created in a semiconductor optical amplifier and find that the LPO will slightly skim over the boundary near the threshold of the injected current. Furthermore, an empirical formula is achieved to gauge the LPO-induced power penalty, which is proven to be valid in differential polarization shift-keying transmission by executing a bit error rate measurement. Our conclusions are applicable to non-orthogonal polarization cases and valuable to polarization-related communications, even orbital angular momentum multiplexing.

© 2016 Chinese Laser Press

PDF Article
More Like This
Polarization dependence of non-linear gain compression factor in semiconductor optical amplifier

Severine Philippe, A. Louise Bradley, Ramon Maldonado-Basilio, Frederic Surre, Brendan F. Kennedy, Pascal Landais, and Horacio Soto-Ortiz
Opt. Express 16(12) 8641-8648 (2008)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

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.