7–12 May 2023
Venice, Italy
Europe/Zurich timezone

Machine learning for laser pulse shaping

THPL034
11 May 2023, 16:30
2h
Sala Laguna

Sala Laguna

Poster Presentation MC6.A27: Machine Learning and Digital Twin Modelling Thursday Poster Session

Speaker

Amelia Pollard (Science and Technology Facilities Council)

Description

The temporal profile of the electron bunch is of critical importance in accelerator areas such as free-electron lasers and novel acceleration. In FELs, it strongly influences factors including efficiency and the profile of the photon pulse generated for user experiments, while in novel acceleration techniques it contributes to enhanced interaction of the witness beam with the driving electric field. Work is in progress at the CLARA facility at Daresbury Laboratory on temporal shaping of the ultraviolet photoinjector laser, using a fused-silica acousto-optic modulator. Generating a user-defined (programmable) time-domain target profile requires finding the corresponding spectral phase configuration of the shaper; this is a non-trivial problem for complex pulse shapes. Using a physically informed machine learning model, we demonstrate accurate and rapid shaping of the photo-injector laser to a wide range of arbitrary target temporal intensity profiles on the CLARA PI laser. Additionally, we discuss the utility of this expanded range of laser pulse shapes to potential applications in FELs and novel acceleration.

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Primary author

Amelia Pollard (Science and Technology Facilities Council)

Co-authors

David Dunning (Science and Technology Facilities Council) Edward Snedden (Science and Technology Facilities Council) William Okell (Science and Technology Facilities Council)

Presentation materials

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