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@INPROCEEDINGS{Appel:358351,
author = {Appel, Sabrina and Oeftiger, Adrian and Kazantseva, Erika
and Weick, Helmut and Madysa, Nico and Boine-Frankenheim,
Oliver and Pietri, Stephane and Isensee, Victoria},
editor = {Pilat, Fulvia and Fischer, Wolfram and Saethre, Robert and
Anisimov, Petr and Andrian, Ivan},
title = {{A}utomated optimization of accelerator settings at {GSI}},
address = {Geneva, Switzerland},
publisher = {JACoW Publishing},
reportid = {GSI-2025-00535},
pages = {882 - 885},
year = {2024},
note = {Published by JACoW Publishing under the terms of the
Creative Commons Attribution 4.0 license.},
abstract = {The complexity of the GSI/FAIR accelerator facility demands
a high level of automation in order to maximize time for
physics experiments. Accelerator laboratories world-wide are
exploring a large variety of techniques to achieve this,
from classical optimization to reinforcement learning. This
paper reports on the first results of using Geoff at GSI for
automatic optimization of various beam manipulations. Geoff
(Generic Optimization Framework $\&$ Frontend) is an
open-source framework that harmonizes access to the above
automation techniques and simplifies the transition towards
and between them. It is maintained as part of the EURO-LABS
project in cooperation between CERN and GSI. In dedicated
beam experiments, the beam loss of the multi-turn injection
into the SIS18 synchrotron has been reduced from $40\%$ to
$10\%$ in about 15 minutes, where manual adjustment can take
up to 2 hours. Geoff has also been used successfully at the
GSI Fragment Separator (FRS) for beam steering. Further
experimental activities include closed orbit correction for
specific broken-symmetry high-transition-energy SIS18 optics
with Bayesian optimization in comparison to traditional
SVD-based correction.},
month = {May},
date = {2024-05-19},
organization = {15th International Particle
Accelerator Conference, Nashville,
Tennessee (USA), 19 May 2024 - 24 May
2024},
keywords = {Accelerator Physics (Other) /
mc5-beam-dynamics-and-em-fields - MC5: Beam Dynamics and EM
Fields (Other) / MC5.D13 - MC5.D13 Machine Learning (Other)},
cin = {APH},
cid = {I:(DE-Ds200)APH-20060809OR090},
pnm = {899 - ohne Topic (POF4-899)},
pid = {G:(DE-HGF)POF4-899},
experiment = {$EXP:(DE-Ds200)no_experiment-20200803$},
typ = {PUB:(DE-HGF)8},
doi = {10.18429/JACOW-IPAC2024-MOPS68},
url = {https://repository.gsi.de/record/358351},
}