JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{schirmer:icalepcs2023-tupdp020,
author = {D. Schirmer and S. Khan and A. Radha Krishnan},
title = {{Summary Report on Machine Learning-Based Applications at the Synchrotron Light Source Delta}},
% booktitle = {Proc. ICALEPCS'23},
booktitle = {Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'23)},
eventdate = {2023-10-09/2023-10-13},
pages = {537--541},
paper = {TUPDP020},
language = {english},
keywords = {injection, laser, controls, synchrotron, storage-ring},
venue = {Cape Town, South Africa},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {19},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {02},
year = {2024},
issn = {2226-0358},
isbn = {978-3-95450-238-7},
doi = {10.18429/JACoW-ICALEPCS2023-TUPDP020},
url = {https://jacow.org/icalepcs2023/papers/tupdp020.pdf},
abstract = {{In recent years, several control system applications using machine learning (ML) techniques have been developed and tested to automate the control and optimization of the 1.5 GeV synchrotron radiation source DELTA. These applications cover a wide range of tasks, including electron beam position correction, working point control, chromaticity adjustment, injection process optimization, as well as CHG-spectra (coherent harmonic generation) analysis. Various machine learning techniques have been used to implement these projects. This report provides an overview of these projects, summarizes the current results, and indicates ideas for future improvements. }},
}