Optimization of Microwave Emission from Laser Filamentation with a Machine Learning Algorithm in Air

Abstract

We demonstrate that is it possible to optimize the yield of microwave radiation from plasmas generated by laser filamentation in atmosphere through manipulation of the laser wavefront. A genetic algorithm controls a deformable mirror that reconfigures the wavefront using the microwave waveform amplitude as feedback. Optimization runs performed as a function of air pressure show that the genetic algorithm can double the microwave field strength relative to when the mirror surface is flat. An increase in the volume and brightness of the plasma fluorescence accompanies the increase in microwave radiation, implying an improvement in the laser beam intensity profile through the filamentation region due to the optimized wavefront.

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Document Details

Document Type
Technical Report
Publication Date
Jul 08, 2021
Accession Number
AD1142577

Entities

People

  • Adrian Lucero
  • Alexander C Englesbe
  • Andreas Schmitt-Sody
  • Jinpu Lin
  • John Nees
  • Karl Krushelnick

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Research Laboratories
  • Air Pressure
  • Algorithms
  • Amplitude
  • Barometric Pressure
  • Coaxial Cables
  • Deformable Mirrors
  • Electric Fields
  • Electrons
  • Frequency
  • Genetic Algorithms
  • Laser Pulses
  • Laser Science
  • Lasers
  • Machine Learning
  • Metamaterial Absorbers
  • Military Research
  • Optical Properties
  • Optics
  • Physics
  • Radiation
  • Repetition Rate
  • Terahertz Radiation

Fields of Study

  • Physics

Readers

  • Optical Physics and Photonics.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology
  • Directed Energy