Open AccessOptimization of microwave emission from laser filamentation with a machine learning algorithm
Author(s) -
Alexander Englesbe,
Jinpu Lin,
John Nees,
Adrian Lucero,
K. Krushelnick,
Andreas Schmitt-Sody
Publication year - 2021
Publication title -
applied optics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.668
H-Index - 197
eISSN - 2155-3165
pISSN - 1559-128X
DOI - 10.1364/ao.426240
Subject(s) - filamentation , wavefront , laser , optics , microwave , wavefront sensor , deformable mirror , brightness , adaptive optics , physics , plasma , materials science , quantum mechanics
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.