Paper | Title | Page |
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THBO01 | Machine Learning-Based Longitudinal Phase Space Prediction of Two-Bunch Operation at FACET-II | 679 |
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Funding: This work was supported by the U.S. Department of Energy under Contract No. DEAC02-76SF00515 We report on the application of machine learning (ML) methods for predicting the longitudinal phase space (LPS) distribution of particle accelerators. Our approach consists of training a ML-based virtual diagnostic to predict the LPS using only nondestructive linac and e-beam measurements as inputs. We validate this approach with a simulation study for the FACET-II linac and with an experimental demonstration conducted at LCLS. At LCLS, the e-beam LPS images are obtained with a transverse deflecting cavity and used as training data for our ML model. In both the FACET-II and LCLS cases we find good agreement between the predicted and simulated/measured LPS profiles, an important step towards showing the feasibility of implementing such a virtual diagnostic on particle accelerators in the future. References: * C. Emma, A. Edelen, M. J. Hogan, B. O¿Shea, G. White, and V. Yakimenko., PRAB 21, 112802 (2018) ** A. Scheinker, A. Edelen, D. Bohler, C. Emma, A. Lutman., PRL 121, 044801 (2018) |
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Slides THBO01 [9.917 MB] | ||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-THBO01 | |
About • | paper received ※ 04 September 2019 paper accepted ※ 10 September 2019 issue date ※ 10 November 2019 | |
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THBO02 |
Diagnostic Requirements for DLSRs (Diffraction Limited Synchrotron Radiation Sources) | |
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Synchrotron radiation sources are looking for performance upgrades by pursuing higher photon brilliance and coherence enabling innovations in various scientific and industrial fields. The trend is pushing the accelerator design to lower the beam emittance, towards the ultimate of diffraction limited condition in a short wavelength range of hard x-rays. This talk will overview the diagnostic requirements for DLSRs. For highlighted crucial diagnostic subjects, the talk will review the current performance of state-of-the-art diagnostic instruments. The talk will also show strategies to bridge the gaps achieving the diagnostic goals of the coming future light sources as well as technical challenges for the breakthrough. | ||
Slides THBO02 [4.178 MB] | ||
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