Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Optimizing Fitting Statistics in Photon Correlation Spectroscopy

Not Accessible

Your library or personal account may give you access

Abstract

We have performed an experiment to test our understanding of the run time, T, necessary to achieve a specified precision in the value of the intensity coherence time, τc, extracted from correlation functions taken in the strong signal limit, and to test predictions for the values of some experimental parameters that optimize the precision. Using ensembles of 10 correlation functions taken at 5 different choices of sample time, we found that the ensemble estimators for the error in τc were well described by the expression δτ/τc=4.2/T/τc, in agreement with the work of Degiorgio and Lastovka (1971). The sample times used were chosen so that the number of coherence times spanned by the 128 channels of the correlator, α, covered the range 1 ≤ α ≤ 16; in this range, we found no evidence of a minimum in δτ/τc to suggest an optimum value of α. These results were independent of whether we used three-parameter or two-parameter least-squares fits to extract τc. However, we did find that the two fits gave systematically different values of τc, and both show a similar dependence on α.

© 1988 Optical Society of America

PDF Article
More Like This
Statistical Fitting Accuracy in Photon Correlation Spectroscopy

J. N. Shaumeyer, Matthew E. Briggs, and Robert W. Gammon
WA5 Photon Correlation and Scattering (PCS) 1992

On-Line Liquid Chromatography Detection by Photon Correlation Spectroscopy

R. J. G. Carr, A. G. Stansfield, J. Rarity, R. G. W. Brown, D. J. Clarke, and T. Atkinson
PCS153 Photon Correlation Techniques and Applications (PCS) 1988

Measurement of Diesel Exhaust Particles in a Dilution Tunnel by Photon Correlation Spectroscopy

N. Lhuissier, A. Nazih, and M. E. Weill
EFD84 Photon Correlation Techniques and Applications (PCS) 1988

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.