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| Title | Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling | |
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| Abstract | One key aspect of accelerator optimization is to maximize the dynamic aperture (DA) of a ring. Given the number of adjustable parameters and the compute-intensity of DA simulations, this task can benefit significantly from efficient search algorithms of the available parameter space. We propose to gradually train and improve a surrogate model of the DA from SixTrack simulations while exploring the parameter space with adaptive sampling methods. Here we report on a first model of the particle stability plots using convolutional generative adversarial networks (GAN) trained on a subset of SixTrack numerical simulations for different ring configurations of the Large Hadron Collider at CERN. | |
| Funding | This work is partially funded by the Swiss Data Science Center (SDSC), project C18-07. | |
| Paper | download TUPAB216.PDF [15.019 MB / 4 pages] | |
| Export | download ※ BibTeX ※ LaTeX ※ Text/Word ※ RIS ※ EndNote | |
| Conference | IPAC2021 | |
| Series | International Particle Accelerator Conference (12th) | |
| Location | Campinas, SP, Brazil | |
| Date | 24-28 May 2021 | |
| Publisher | JACoW Publishing, Geneva, Switzerland | |
| Editorial Board | Liu Lin (LNLS, Campinas, Brazil); John M. Byrd (ANL, Lemont, IL, USA); Regis Neuenschwander (LNLS, Campinas, Brazil); Renan Picoreti (LNLS, Campinas, Brazil); Volker R. W. Schaa (GSI, Darmstadt, Germany) | |
| Online ISBN | 978-3-95450-214-1 | |
| Online ISSN | 2673-5490 | |
| Received | 19 May 2021 | |
| Accepted | 17 June 2021 | |
| Issue Date | 22 August 2021 | |
| DOI | doi:10.18429/JACoW-IPAC2021-TUPAB216 | |
| Pages | 1923-1926 | |
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