Physics-based predictive modeling of atmospheric optical turbulence layers: Solution of paraxial wave equation for inhomogeneous media in linear and quadratic approximation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

I review physics-based predictive modeling and novel multi-nesting computational techniques that resolve physical processes in shear-stratified atmospheric layers. Results on oscillating laser beams, spiral light beams and refractivity path bending for directed energy beams are predicted by solutions of the inhomogeneous paraxial wave equation in quadratic approximation. The effects of super-focusing and optical mirage phenomena induced by strong spatial variations of the mean-field refractive index are analyzed.

Original languageEnglish (US)
Title of host publicationPropagation Through and Characterization of Distributed Volume Turbulence, pcDVT 2013
StatePublished - Dec 1 2013
EventPropagation Through and Characterization of Distributed Volume Turbulence, pcDVT 2013 - Arlington, VA, United States
Duration: Jun 23 2013Jun 27 2013

Publication series

NameOptics InfoBase Conference Papers
ISSN (Electronic)2162-2701

Other

OtherPropagation Through and Characterization of Distributed Volume Turbulence, pcDVT 2013
CountryUnited States
CityArlington, VA
Period6/23/136/27/13

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

Fingerprint Dive into the research topics of 'Physics-based predictive modeling of atmospheric optical turbulence layers: Solution of paraxial wave equation for inhomogeneous media in linear and quadratic approximation'. Together they form a unique fingerprint.

  • Cite this

    Mahalov, A. (2013). Physics-based predictive modeling of atmospheric optical turbulence layers: Solution of paraxial wave equation for inhomogeneous media in linear and quadratic approximation. In Propagation Through and Characterization of Distributed Volume Turbulence, pcDVT 2013 (Optics InfoBase Conference Papers).