TY  - CONF
AU  - Appel, Sabrina
AU  - Oeftiger, Adrian
AU  - Kazantseva, Erika
AU  - Weick, Helmut
AU  - Madysa, Nico
AU  - Boine-Frankenheim, Oliver
AU  - Pietri, Stephane
AU  - Isensee, Victoria
A3  - Pilat, Fulvia
A3  - Fischer, Wolfram
A3  - Saethre, Robert
A3  - Anisimov, Petr
A3  - Andrian, Ivan
TI  - Automated optimization of accelerator settings at GSI
CY  - Geneva, Switzerland
PB  - JACoW Publishing
M1  - GSI-2025-00535
SP  - 882 - 885
PY  - 2024
N1  - Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license.
AB  - 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 </td><td width="150">
AB  -  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
T2  - 15th International Particle Accelerator Conference
CY  - 19 May 2024 - 24 May 2024, Nashville, Tennessee (USA)
Y2  - 19 May 2024 - 24 May 2024
M2  - Nashville, Tennessee, USA
KW  - Accelerator Physics (Other)
KW  - mc5-beam-dynamics-and-em-fields - MC5: Beam Dynamics and EM Fields (Other)
KW  - MC5.D13 - MC5.D13 Machine Learning (Other)
LB  - PUB:(DE-HGF)8
DO  - DOI:10.18429/JACOW-IPAC2024-MOPS68
UR  - https://repository.gsi.de/record/358351
ER  -