CERN Accelerators Beam Optimization Algorithm

Autor: Piselli, Emiliano, Akroh, Abdelouahid, Blaum, Klaus, Door, Menno, Leimbach, David, Rothe, Sebastian
Jazyk: angličtina
Rok vydání: 2020
Předmět:
DOI: 10.18429/jacow-icalepcs2019-wepha124
Popis: 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.
Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems, ICALEPCS2019, New York, NY, USA
Databáze: OpenAIRE