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  4. Advanced beam shaping for laser materials processing based on diffractive neural networks
 
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2022
Journal Article
Title

Advanced beam shaping for laser materials processing based on diffractive neural networks

Abstract
We propose a method based on neural network training algorithms for the design of diffractive neural networks - with the aim to perform advanced laser beam shaping in the NIR/VIS spectrum for laser materials processing. The method enables the efficient design of systems including multiple cascaded diffractive optical elements (DOEs) and allows the simultaneous optimization for complex (intensity and phase) target field distributions in multiple target planes. The multi-target boundary condition in the optimization method offers great potential for advanced laser beam shaping.
Author(s)
Buske, Paul  
RWTH Aachen University TOS - Chair for Technology of Optical Systems
Völl, Annika
RWTH Aachen University TOS - Chair for Technology of Optical Systems
Eisebitt, Moritz
RWTH Aachen University TOS - Chair for Technology of Optical Systems
Stollenwerk, Jochen  
Fraunhofer-Institut für Lasertechnik ILT  
Holly, Carlo  
RWTH Aachen University TOS - Chair for Technology of Optical Systems
Journal
Optics Express  
Open Access
DOI
10.1364/OE.459460
Additional link
Full text
Language
English
Fraunhofer-Institut für Lasertechnik ILT  
Keyword(s)
  • Beam shaping

  • Diffractive optical elements

  • Laser beam shaping

  • Laser materials processing

  • Neural networks

  • Optical systems

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