Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 72,
  • Issue 5,
  • pp. 787-792
  • (2018)

Uncertainty of Integrated Intensity Following Line Profile Fitting of Multiline Spectra

Not Accessible

Your library or personal account may give you access

Abstract

A novel method of determining the total uncertainty in the integrated intensity of fitted emission lines in multipeaked emission spectra is presented. The proposed method does not require an assumption of the type of line profile to be specified. The absolute difference between a fit and measured spectrum defines the uncertainty of the integrated signal intensity and is subsequently decomposed to determine the uncertainty of each peak in multiline fits. Decomposition relies on tabulating a weighting factor, which describes how each peak contributes to the total integral uncertainty. Applications of this method to quantitative approaches in laser-induced breakdown spectroscopy analysis are described.

© 2018 The Author(s)

PDF Article
More Like This
Uncertainties in extracted parameters of a Gaussian emission line profile with continuum background

Serge Minin and Farzad Kamalabadi
Appl. Opt. 48(36) 6913-6922 (2009)

Development and performance evaluation of self-absorption-free laser-induced breakdown spectroscopy for directly capturing optically thin spectral line and realizing accurate chemical composition measurements

Jiajia Hou, Lei Zhang, Wangbao Yin, Shunchun Yao, Yang Zhao, Weiguang Ma, Lei Dong, Liantuan Xiao, and Suotang Jia
Opt. Express 25(19) 23024-23034 (2017)

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.