TY  - CONF
AU  - Boulton, Lewis Anthony
AU  - Beinortaite, Judita
AU  - Björklund Svensson, Jonas Halfdan
AU  - Burghart, Philipp
AU  - Cowley, James
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  - Schröder, Sarah
AU  - Pena Asmus, Felipe Lars
AU  - Thévenet, Maxence
AU  - Wesch, Stephan
AU  - Wing, Matthew
AU  - Wood, Jonathan Christopher
AU  - D'Arcy, Richard
TI  - Advanced Controls and Machine Learning at FLASHForward
PB  - DESY
M1  - PUBDB-2025-05711
PY  - 2025
AB  - Plasma-based accelerators hold the potential to achieve mulit-giga-volt-per-metre accelerating gradients, offering a promising route to more compact and cost-effective accelerators for future light sources and colliders. However, plasma wakefield acceleration (PWFA) is often a nonlinear, high-dimensional process that is sensitive to jitters in multiple input parameters, making the setup, operation and diagnosis of a PWFA stage a challenging task. To tackle some of these issues, Machine Learning techniques have gained popularity in the field of plasma acceleration. Specifically, advanced algorithms such as Bayesian Optimisation have proved useful for the setup and tuning of plasma accelerators. Moreover, neural networks trained on experimental data have enabled the shot-to-shot prediction of beam parameters based on noninvasive measurements, simultaneously providing valuable insights into the different dependencies of the acceleration process. We present progress in deploying such methods at FLASHForward, a beam-driven plasma wakefield accelerator test-bed based at DESY, Hamburg, and explore future directions for further integration of these techniques at the facility.
T2  - LPA Special Workshop on Intelligent Systems 2025
CY  - 13 Jan 2025 - 16 Jan 2025, Oxford (UK)
Y2  - 13 Jan 2025 - 16 Jan 2025
M2  - Oxford, UK
LB  - PUB:(DE-HGF)24
UR  - https://bib-pubdb1.desy.de/record/642915
ER  -