| Paper |
Title |
Page |
| MOPGW024 |
Measurements of the GSI Transfer Beam Lines Ion Optics |
131 |
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- M. Sapinski, O. Geithner, S. Reimann, P. Schütt, M. Vossberg, B. Walasek-Höhne
GSI, Darmstadt, Germany
- C. Heßler
CERN, Meyrin, Switzerland
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GSI High Energy Beam Transfer lines (HEST) link the SIS18 synchrotron with two storage rings (Experimental Storage Ring and Cryring) and six experimental caves. The recent upgrades to HEST beam instrumentation enables precise measurements of beam properties along the lines and allow for faster and more precise beams setup on targets. Preliminary results of some of the measurements performed during runs in 2018 and 2019 are presented here. The focus is on response matrix measurements and quadrupole scans performed on HADES beam line. The errors and future improvements are discussed.
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| DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2019-MOPGW024
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| About • |
paper received ※ 15 May 2019 paper accepted ※ 19 May 2019 issue date ※ 21 June 2019 |
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| WEPMP005 |
Beam Line Optimization Using Derivative-Free Algorithms |
2307 |
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- S. Appel, S. Reimann
GSI, Darmstadt, Germany
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The present study focuses on the beam line optimization from the heavy-ion synchrotron SIS18 to the HADES experiment. BOBYQA (Bound Optimization BY Quadratic Approximation) solves bound constrained optimization problems without using derivatives of the objective function. The Bayesian optimization is an other strategy for global optimization of costly, noisy functions without using derivatives. A python programming interface to MADX allow the use of the python implementation of BOBYQA and Bayesian method. This gave the possibility to use tracking simulation with MADX to determine the loss budget for each lattice setting during the optimization and compare both optimization methods.
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| DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2019-WEPMP005
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| About • |
paper received ※ 29 April 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019 |
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| MOPGW023 |
An Algorithm for Automated Lattice Design of Transfer Lines |
127 |
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- S. Reimann, M. Droba, O. Meusel, H. Podlech
IAP, Frankfurt am Main, Germany
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Since the last 20 years, modern heuristic algorithms and machine learning have been increasingly used for several purposes in accelerator technology and physics. Since computing power has become less and less of a limiting factor, these tools have become part of the physicist community’s standard toolkit. This paper describes the construction of an algorithm that can be used to generate an optimised lattice design for transfer lines under the consideration of restrictions that usually limit design options in reality. The developed algorithm has been applied to the existing SIS18 to HADES transfer line in GSI.
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| DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2019-MOPGW023
|
|
| About • |
paper received ※ 28 April 2019 paper accepted ※ 18 May 2019 issue date ※ 21 June 2019 |
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