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

Single-interval statistics of non-Gaussian light in the presence of number fluctuations

Not Accessible

Your library or personal account may give you access

Abstract

By using the basic particle-scattering theory, the high-order moments of non-Gaussian light, including number fluctuations that are due to independent particles, have been deduced for a sampling interval that is much smaller than the characteristic time of the number fluctuations but comparable with that of the interference fluctuations. The results have been compared with experiment by measuring the second- and third-factorial moments.

© 1982 Optical Society of America

Full Article  |  PDF Article
More Like This
Speckle statistics of doubly scattered light

K. A. O’Donnell
J. Opt. Soc. Am. 72(11) 1459-1463 (1982)

Universal statistical model for irradiance fluctuations in a turbulent medium

Ronald L. Phillips and Larry C. Andrews
J. Opt. Soc. Am. 72(7) 864-870 (1982)

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

Figures (4)

You do not have subscription access to this journal. Figure files 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

Equations (88)

You do not have subscription access to this journal. Equations 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.