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@ARTICLE{Madysa:361895,
author = {Madysa, Penelope Johanna Nico and Appel, Sabrina},
collaboration = {Kain, V. and Schenk, M.},
title = {{G}eoff: {T}he generic optimization framework $\&$ frontend
for particle accelerator controls},
journal = {SoftwareX},
volume = {32},
issn = {2352-7110},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {GSI-2025-01038},
pages = {102335},
year = {2025},
note = {This is an open access article under the CC BY license (
http://creativecommons.org/licenses/by/4.0/)},
abstract = {Geoff is a collection of Python packages that form a
framework for automation of particle accelerator controls.
With particle accelerator laboratories around the world
researching machine learning techniques to improve
accelerator performance and uptime, a multitude of
approaches and algorithms have emerged. The purpose of Geoff
is to harmonize these approaches and to minimize friction
when comparing or migrating between them. It provides
standardized interfaces for optimization problems, utility
functions to speed up development, and a reference GUI
application that ties everything together. Geoff is an
open-source library developed at CERN and maintained and
updated in collaboration between CERN and GSI as part of the
EURO-LABS project. This paper gives an overview over
Geoff’s design, features, and current usage.},
cin = {APH},
ddc = {004},
cid = {I:(DE-Ds200)APH-20060809OR090},
pnm = {621 - Accelerator Research and Development (POF4-621) /
EURO-LABS - EUROpean Laboratories for Accelerator Based
Science (101057511)},
pid = {G:(DE-HGF)POF4-621 / G:(EU-Grant)101057511},
experiment = {EXP:(DE-Ds200)FAIR-Facility},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001576933100001},
doi = {10.1016/j.softx.2025.102335},
url = {https://repository.gsi.de/record/361895},
}