Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE

Author

Chenran Xu, Erik Bründermann, Anke-Susanne Müller, Michael Johannes Nasse, Andrea Santamaria Garcia, Carl Sax, Christina Widmann, Annika Eichler

Participating institute

Institut für Beschleunigerphysik und Technologie (IBPT)
Laboratorium für Applikationen der Synchrotronstrahlung (LAS)
Fakultät für Physik (PHYSIK)

Genre

Beiträge rund ums KIT

Description

FLUTE (Ferninfrarot Linac- und Test-Experiment) at KIT is a compact linacbased
test facility for novel accelerator technology and a source of intense
THz radiation. FLUTE is designed to provide a wide range of electron bunch
charges from the pC- to nC-range, high electric fields up to 1.2 GV/m, and
ultra-short THz pulses down to the fs-timescale. The electrons are generated
at the RF photoinjector, where the electron gun is driven by a commercial
titanium sapphire laser. In this kind of setup the electron beam properties are
determined by the photoinjector, but more importantly by the characteristics
of the laser pulses. Spatial light modulators can be used to transversely and
longitudinally shape the laser pulse, offering a flexible way to shape the laser
beam and subsequently the electron beam, influencing the produced THz
pulses. However, nonlinear effects inherent to the laser manipulation
(transportation, compression, third harmonic generation) can distort the
original pulse. In this paper we propose to use machine learning methods to
manipulate the laser and electron bunch, aiming to generate tailor-made THz
pulses. The method is demonstrated experimentally in a test setup.

Keywords

IBPT, LAS

Duration (hh:mm:ss)

00:04:19

Published on

17.09.2021

Subject area

Physics

License

Creative Commons Attribution 4.0 International