IBIC2019 - Table of Session: THBO (Closing session)

Paper	Title	Page
THBO01	Machine Learning-Based Longitudinal Phase Space Prediction of Two-Bunch Operation at FACET-II	679
	C. Emma, M.D. Alverson, A.L. Edelen, M.J. Hogan, B.D. O’Shea, D.W. Storey, G.R. White, V. Yakimenko SLAC, Menlo Park, California, USA A. Hanuka Technion, Haifa, Israel
	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)
	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
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THBO02	Diagnostic Requirements for DLSRs (Diffraction Limited Synchrotron Radiation Sources)
	S. Takano JASRI, Hyogo, Japan S. Takano, H. Tanaka RIKEN SPring-8 Center, Hyogo, Japan
	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]
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Machine Learning-Based Longitudinal Phase Space Prediction of Two-Bunch Operation at FACET-II

679

C. Emma, M.D. Alverson, A.L. Edelen, M.J. Hogan, B.D. O’Shea, D.W. Storey, G.R. White, V. Yakimenko
SLAC, Menlo Park, California, USA
A. Hanuka
Technion, Haifa, Israel

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)

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

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THBO02

Diagnostic Requirements for DLSRs (Diffraction Limited Synchrotron Radiation Sources)

S. Takano
JASRI, Hyogo, Japan
S. Takano, H. Tanaka
RIKEN SPring-8 Center, Hyogo, Japan

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]

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)