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URLhttps://doi.org/10.18429/JACoW-ICALEPCS2025-WEPD076
TitleGeoff developments in 2025
Authors
  • P. Madysa, S. Appel, L. Dingeldein, J. Fitzek
    GSI Helmholtz Centre for Heavy Ion Research
  • V. Kain, M. Schenk
    European Organization for Nuclear Research
AbstractThe complexity of the CERN and GSI/FAIR accelerator facilities requires a high degree of automation to maximize beam time and performance for physics experiments. GeOFF, the Generic Optimization Framework & Frontend, is an open-source tool developed within the EURO-LABS project by CERN and GSI to streamline access to classical and AI-based optimization methods. It provides standardized interfaces for optimization problems and utility functions to speed up implementation. Plugins are independent packages with their own dependencies, allowing scaling from simple prototypes to complex state machines that communicate with devices in different timing domains. This contribution presents GeOFF’s design, features, and current applications. At GSI, multi-objective Bayesian optimization was applied to SIS18 multi-turn injection, building a Pareto front from experimental data. At CERN, GeOFF and ML/AI contributed to a record ion beam intensity for the LHC in 2024 through LEIR and SPS optimization. In addition, GeOFF underwent major updates in 2025, aligning it with the latest developments in Python-based numerical and machine-learning software.
Paperdownload: WEPD076.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
Conference20th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'25)
Series
LocationChicago, IL, USA
Date20-26 Sep 2025
PublisherJACoW Publishing, Geneva, Switzerland
Editorial BoardKent Wootton (ANL), Jeffery Biss (FNAL), Gustavo Bruno (ANL), Jeff Kirchman (ANL), Kelly Jaje (ANL), Denise Skiadopoulos (ANL), SuYin Grass Wang (ANL)
Online ISBN978-3-95450-255-4
Online ISSN2226-0358
Received08 September 2025
Revised08 October 2025
Accepted31 October 2025
Issued25 November 2025
DOI10.18429/JACoW-ICALEPCS2025-WEPD076
Pages1219-1222