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CERN Accelerators Beam Optimization Algorithm

In experimental physics, computer algorithms are used to make decisions to perform measurements and different types of operations. To create a useful algorithm, the optimization parameters should be based on real time data. However, parameter optimization is a time consuming task, due to the large s...

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Detalles Bibliográficos
Autores principales: Piselli, Emiliano, Akroh, Abdelouahid, Blaum, Klaus, Door, Menno, Leimbach, David, Rothe, Sebastian
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:https://dx.doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA124
http://cds.cern.ch/record/2778531
Descripción
Sumario:In experimental physics, computer algorithms are used to make decisions to perform measurements and different types of operations. To create a useful algorithm, the optimization parameters should be based on real time data. However, parameter optimization is a time consuming task, due to the large search space. In order to cut down the runtime of optimization we propose an algorithm inspired by the numerical method Nelder-Mead. This paper presents details of our method and selected experimental results from high-energy (CERN accelerators) to low-energy (Penning-trap systems) experiments as to demonstrate its efficiency. We also show simulations performed on standard test functions for optimization.