Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 19,
  • Issue 1,
  • pp. 54-
  • (2001)

Approximate Analytical Description for Fundamental-Mode Fields of Graded-Index Fibers: Beyond the Gaussian Approximation

Not Accessible

Your library or personal account may give you access

Abstract

An approximate analytical description for fundamental-mode fields of graded-index fibers is explicitly presented by use of the power-series expansion method, the maximum-value condition at the fiber axis, the decay properties of fundamental-mode fields at large distance from the fiber axis,and the approximate modal parameters U obtained from the Gaussian approximation. This analytical description is much more accurate than the Gaussian approximation and at the same time keep the simplicity of the latter. As two special examples,we present the approximate analytical formulas for the fundamental-mode fields of a step profile fiber and a Gaussian profile fiber, and we find that they are both highly accurate in the single-mode range by comparing them with the corresponding exact solutions.

[IEEE ]

PDF Article
More Like This
Gaussian approximation of the fundamental modes of graded-index fibers

D. Marcuse
J. Opt. Soc. Am. 68(1) 103-109 (1978)

Propagation characteristics of single-mode graded-index elliptical core linear and nonlinear fiber using super-Gaussian approximation

Sunil K. Khijwania, Veena M. Nair, and Somenath Sarkar
Appl. Opt. 48(31) G156-G162 (2009)

Scattering of the fundamental modes from graded-index fibers into semi-infinite space

T. Do-Nhat and R. H. MacPhie
J. Opt. Soc. Am. A 9(4) 569-572 (1992)

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.