|WEPOW055||Bayesian Optimization of FEL Performance at LCLS||2972|
Funding: Research is supported by the U.S. Department of Energy under Contract No. DE-AC02-76SF00515.
The LCLS free-electron laser at SLAC is tuned via a huge number of parameters such as energy and magnet settings. Much of this tuning, including quadrupole magnet settings, is typically done by hand by the LCLS operators. In this paper we introduce an automated tuning system using Bayesian optimization, and describe its application to the optimization of noisy objectives such as FEL performance. We demonstrate with preliminary results from our implementation at LCLS that this system can improve both the speed of tuning procedures as well as the quality of the resulting solution.
|DOI •||reference for this paper ※ DOI:10.18429/JACoW-IPAC2016-WEPOW055|
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