TY  - CONF
AU  - Boulton, Lewis Anthony
AU  - Beinortaite, Judita
AU  - Björklund Svensson, Jonas Halfdan
AU  - Burghart, Philipp
AU  - D'Arcy, Richard
AU  - Ferran Pousa, Angel
AU  - Foster, Brian
AU  - Gonzalez Caminal, Pau
AU  - Huck, Maryam
AU  - Jones, Harry
AU  - Kanekar, Advait
AU  - Lindstroem, Carl Andreas
AU  - Loisch, Gregor
AU  - Long, Tianyun
AU  - Maier, Andreas
AU  - Mewes, Steven Mathis
AU  - Osterhoff, Jens
AU  - Pena Asmus, Felipe Lars
AU  - Schröder, Sarah
AU  - Thévenet, Maxence
AU  - Wesch, Stephan
AU  - Wing, Matthew
AU  - Wood, Jonathan Christopher
TI  - Advanced Controls and Machine Learning at FLASHForward
PB  - DESY
M1  - PUBDB-2025-05726
PY  - 2025
AB  - Plasma accelerators often constitute a high-noise environment with multiple, non-linear dependencies that make the setup and operation of such devices a difficult task. To address these challenges, Machine Learning methods have gained popularity in the field of plasma acceleration. In this contribution, we summarise the application of such techniques to the beam-driven plasma acceleration experiment FLASHForward at DESY, Hamburg. Examples include the automated tuning of the plasma stage via Bayesian Optimisation and the development of non-destructive, neural-network-based predictions of the resulting accelerated trailing-bunch spectra.
T2  - 7th European Advanced Accelerator Conference
CY  - 21 Sep 2025 - 27 Sep 2025, Elba (Italy)
Y2  - 21 Sep 2025 - 27 Sep 2025
M2  - Elba, Italy
LB  - PUB:(DE-HGF)6
UR  - https://bib-pubdb1.desy.de/record/642930
ER  -