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Related Concept Videos

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This substitution...
Linear time-invariant Systems01:23

Linear time-invariant Systems

A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
Linearization and Approximation01:26

Linearization and Approximation

Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...

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Related Experiment Video

Updated: May 25, 2026

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light
09:19

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light

Published on: July 29, 2013

Anderson localization in nonlocal nonlinear media.

Viola Folli1, Claudio Conti

  • 1Department of Physics, University Sapienza, Rome, Italy. viola.folli@roma1.infn.it

Optics Letters
|February 3, 2012
PubMed
Summary

Nonlinearities stabilize Anderson localization in nonlocal media. This study develops a perturbative approach to solve the nonlocal nonlinear Schrödinger equation, revealing nonlocality

Area of Science:

  • Nonlinear optics
  • Condensed matter physics

Background:

  • Anderson localization describes wave function confinement in disordered media.
  • Nonlocal nonlinearities introduce spatial correlations in the medium's response.

Purpose of the Study:

  • Investigate the impact of focusing and defocusing nonlinearities on Anderson localization.
  • Analyze Anderson localization in highly nonlocal media.

Main Methods:

  • Theoretical analysis using a perturbative approach.
  • Numerical simulations of the nonlocal nonlinear Schrödinger equation with random potentials.

Main Results:

  • Nonlocality was found to stabilize Anderson localized states.
  • The interplay between nonlinearity and disorder was explored.

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Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells
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Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Published on: June 30, 2018

Related Experiment Videos

Last Updated: May 25, 2026

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light
09:19

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light

Published on: July 29, 2013

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells
11:06

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Published on: June 30, 2018

Conclusions:

  • Nonlocal nonlinearities offer a mechanism to enhance the stability of Anderson localization.
  • The findings have implications for controlling wave localization in complex systems.