The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
TY - CONF AU - Appel, S. AU - Geithner, W. AU - Reimann, S. AU - Sapinski, M. AU - Singh, R. AU - Vilsmeier, D.M. ED - Schaa, Volker RW ED - Makino, Kyoko ED - Snopok, Pavel ED - Berz, Martin TI - Optimization of Heavy-Ion Synchrotrons Using Nature-Inspired Algorithms and Machine Learning J2 - Proc. of ICAP2018, Key West, FL, USA, 20-24 October 2018 CY - Key West, FL, USA T2 - International Computational Accelerator Physics Conference T3 - 13 LA - english AB - The application of machine learning and nature-inspired optimization methods, like for example genetic algorithms (GA) and particle swarm optimization (PSO) can be found in various scientific/technical areas. In recent years, those approaches are finding application in accelerator physics to a greater extent. In this report, nature-inspired optimization as well as the machine learning will be shortly introduced and their application to the accelerator facility at GSI/FAIR will be presented. For the heavy-ion synchrotron SIS18 at GSI, the multi-objective GA/PSO optimization resulted in a significant improvement of multi-turn injection performance and subsequent transmission for intense beams. An automated injection optimization with genetic algorithms at the CRYRING@ESR ion storage ring has been performed. The usage of machine learning for a beam diagnostic application, where reconstruction of space-charge distorted beam profiles from ionization profile monitors is performed, will also be shown. First results and the experience gained will be presented. PB - JACoW Publishing CP - Geneva, Switzerland SP - 15 EP - 21 KW - injection KW - emittance KW - simulation KW - synchrotron KW - space-charge DA - 2019/01 PY - 2019 SN - 978-3-95450-200-4 DO - DOI: 10.18429/JACoW-ICAP2018-SAPAF02 UR - http://jacow.org/icap2018/papers/sapaf02.pdf ER -