Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random Error01:04

Random Error

3.9K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
3.9K
Plane Electromagnetic Waves I01:30

Plane Electromagnetic Waves I

4.4K
The existence of combined electric and magnetic fields that propagate through space as electromagnetic (EM) waves is the most significant prediction of Maxwell's equations. As Maxwell's equations hold in free space, the predicted electromagnetic waves do not require a medium for their propagation. An EM wave comprises an electric field, defined as the force per charge on a stationary charge, and a magnetic field, which is the force per charge on a moving charge.
The EM field is assumed...
4.4K
Gauss's Law: Spherical Symmetry01:26

Gauss's Law: Spherical Symmetry

8.2K
A charge distribution has spherical symmetry if the density of charge depends only on the distance from a point in space and not on the direction. In other words, if the system is rotated, it doesn't look different. For instance, if a sphere of radius R is uniformly charged with charge density ρ0, then the distribution has spherical symmetry. On the other hand, if a sphere of radius R is charged so that the top half of the sphere has a uniform charge density ρ1 and the bottom half...
8.2K
Gauss's Law in Dielectrics01:17

Gauss's Law in Dielectrics

4.7K
Consider a polar dielectric placed in an external field. In such a dielectric, opposite charges on adjacent dipoles neutralize each other, such that the net charge within the dielectric is zero. When a polar dielectric is inserted in between the capacitor plates, an electric field is generated due to the presence of net charges near the edge of the dielectric and the metal plates interface. Since the external electrical field merely aligns the dipoles, the dielectric as a whole is neutral. An...
4.7K
Gauss's Law: Cylindrical Symmetry01:20

Gauss's Law: Cylindrical Symmetry

8.4K
A charge distribution has cylindrical symmetry if the charge density depends only upon the distance from the axis of the cylinder and does not vary along the axis or with the direction about the axis. In other words, if a system varies if it is rotated around the axis or shifted along the axis, it does not have cylindrical symmetry. In real systems, we do not have infinite cylinders; however, if the cylindrical object is considerably longer than the radius from it that we are interested in,...
8.4K
Gauss's Law: Planar Symmetry01:27

Gauss's Law: Planar Symmetry

8.6K
A planar symmetry of charge density is obtained when charges are uniformly spread over a large flat surface. In planar symmetry, all points in a plane parallel to the plane of charge are identical with respect to the charges. Suppose the plane of the charge distribution is the xy-plane, and the electric field at a space point P with coordinates (x, y, z) is to be determined. Since the charge density is the same at all (x, y) - coordinates in the z = 0 plane, by symmetry, the electric field at P...
8.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Modelization theory for vectorial structured light.

Optics letters·2026
Same author

Roadmap on singular optics and its applications.

Applied physics. B, Lasers and optics·2026
Same author

Strengthening JOSA A-our new topical editors in action: editorial.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same author

Radial similarity measures for vectorial structured light.

Optics letters·2026
Same author

Orbital mode structure of random vectorial light beams.

Optics letters·2025
Same author

On the structure of the polarization-orbitalization tensor.

Optics letters·2025
Same journal

Denoising algorithm of Φ-OTDR systems based on adaptive fractional wavelet transform denoising.

Optics express·2026
Same journal

Millisecond photon-to-photon latency and high-speed volumetric projection system for optogenetics.

Optics express·2026
Same journal

Polarization-encoded coaxial structured light for high-precision 3D surface profilometry.

Optics express·2026
Same journal

Discrete freeform optical design based on collaborative optimization of point cloud and local normals.

Optics express·2026
Same journal

Ultrafast ghost imaging with 25 GHz speckle switching and wavelength-division multiplexing.

Optics express·2026
Same journal

Atomic vapor cells fabricated by femtosecond laser welding of standard-optical-quality glass.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Oct 17, 2025

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
14:58

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

Published on: June 2, 2010

9.7K

Multi-Gaussian random variables for modeling optical phenomena.

Olga Korotkova, Milo W Hyde

    Optics Express
    |October 7, 2021
    PubMed
    Summary
    This summary is machine-generated.

    Researchers introduced multi-Gaussian (MG) random variables, a flexible generalization of Gaussian distributions. These novel variables, characterized by a shape parameter M, offer flattened or cusped profiles and have applications in optics, particularly for speckle field characterization.

    More Related Videos

    The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
    12:14

    The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

    Published on: August 12, 2013

    22.0K
    Spectral and Angle-Resolved Magneto-Optical Characterization of Photonic Nanostructures
    08:01

    Spectral and Angle-Resolved Magneto-Optical Characterization of Photonic Nanostructures

    Published on: November 21, 2019

    7.3K

    Related Experiment Videos

    Last Updated: Oct 17, 2025

    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
    14:58

    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

    Published on: June 2, 2010

    9.7K
    The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
    12:14

    The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

    Published on: August 12, 2013

    22.0K
    Spectral and Angle-Resolved Magneto-Optical Characterization of Photonic Nanostructures
    08:01

    Spectral and Angle-Resolved Magneto-Optical Characterization of Photonic Nanostructures

    Published on: November 21, 2019

    7.3K

    Area of Science:

    • Probability theory
    • Statistical modeling
    • Optics

    Background:

    • The classic Gaussian random variable is a cornerstone in probability and statistics.
    • Existing models may not fully capture the complexity of certain natural phenomena, such as speckle fields.

    Purpose of the Study:

    • Introduce a generalized family of multi-Gaussian (MG) random variables.
    • Explore their mathematical properties and potential applications in scientific fields.
    • Demonstrate the utility of MG variables in characterizing novel speckle fields.

    Main Methods:

    • Defined the probability density function (PDF) of MG random variables as an alternating series of Gaussian functions.
    • Investigated the impact of the shape parameter M on the PDF's profile (flattened or cusped).
    • Developed multivariate extensions and introduced the log-multi-Gaussian random variable.
    • Applied MG variables to the theoretical and numerical simulation-based characterization of speckle fields.

    Main Results:

    • MG random variables generalize the classic Gaussian PDF, with M=1 recovering the standard Gaussian.
    • Integer M values result in finite series and flattened profiles; non-integer M values yield infinite series that can be truncated.
    • MG PDFs exhibit flattened profiles for M>1 and cusped profiles for 0
    • The study successfully applied MG variables to speckle field characterization, showing their practical relevance.

    Conclusions:

    • The multi-Gaussian (MG) random variable family offers a versatile extension to Gaussian distributions.
    • The shape parameter M allows for tunable profile characteristics (flattened or cusped), enhancing modeling capabilities.
    • MG random variables are valuable tools for advanced statistical analysis and have demonstrated utility in optical applications like speckle field analysis.