Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • CLEO/Europe and EQEC 2009 Conference Digest
  • (Optica Publishing Group, 2009),
  • paper EA_P5

Resonator Modes beyond the Paraxial Approximation: Spin-Orbit Coupling of Light

Not Accessible

Your library or personal account may give you access

Abstract

Fabry-Perot Resonators are of fundamental interest in physics. Resonator inodes have generally been described based on the paraxial equation, which neglects a term from the Helmholtz equation using the assumption of near-axial beams. One can therefore expect the paraxial equation to be insufficient for a complete description of near-concentric resonators due to the large beam divergence, as well as for high-finesse resonators due to the high frequency resolution. Repeated effort has been undertaken to calculate corrections to the eigenmodes and eigenfrequencies of Fabry-Perot resonators predicted by the paraxial approximation [1,2,3]. None of these have taken into account all the considerations necessary to calculate the first order correction to the resonator eigenfrequencies, which include using a three-dimensional model, calculating modes using the vector (rather than scalar) wave equation, and correctly modeling the spherical mirror surface.

© 2009 IEEE

PDF Article
More Like This
The Role of Berry's Geometric Phase in the Mode Spectrum of a Fabry-Pérot Resonator

P.W.H. Pinkse, M. Koch, B. Hagemann, M. Motsch, M. Zeppenfeld, and G. Rempe
EE_P2 European Quantum Electronics Conference (EQEC) 2011

Classical spin-orbit coupling of light in micro-dome cavities with Bragg mirrors

D. H. Foster and J. U. Nöckel
JTuC99 Conference on Lasers and Electro-Optics (CLEO:S&I) 2005

The correction to the paraxial approximation for the laser cavity modes

D. V. Skryabin and A. M. Radin
CTuK33 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 1994

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.