Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 35,
  • Issue 24,
  • pp. 5381-5384
  • (2017)

High-Resolution and Low-Loss All-Fiber Spectral Filters Based on Biconic Tapers

Not Accessible

Your library or personal account may give you access

Abstract

A family of narrowband spectral filters based on biconic fiber tapers is investigated. These filters were made of highly-depressed-cladding single-mode fibers by a heat-and-pulling process, and using a cylindrical-tube graphite heater. The evolution of the taper profiles during the pulling of different elongations was modeled by a coupled system of partial differential equations governing the mass and axial momentum conservation. The optical responses were modeled by using the mode coupling theory. Theoretical results, ranging from prediction of the taper profiles to optical responses of these filters—transmission losses, free spectral range, and isolation—show strong accordance with experimental ones.

PDF Article
More Like This
All-fiber wavelength filter from successive biconical tapers

Suzanne Lacroix, François Gonthier, and Jacques Bures
Opt. Lett. 11(10) 671-673 (1986)

Hydrofluoric acid flow etching of low-loss subwavelength-diameter biconical fiber tapers

Eric J. Zhang, Wesley D. Sacher, and Joyce K. S. Poon
Opt. Express 18(21) 22593-22598 (2010)

Ultra-low-loss 5-LP mode selective coupler based on fused biconical taper technique

Huiyi Guo, Liang Chen, Zekun Shi, Wenzhe Chang, Letian Gu, Zhi Wang, and Yan-ge Liu
Opt. Express 31(11) 18050-18062 (2023)

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.