Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

Version 1 : Received: 5 January 2021 / Approved: 6 January 2021 / Online: 6 January 2021 (11:58:41 CET)

A peer-reviewed article of this Preprint also exists.

Emma, C.; Edelen, A.; Hanuka, A.; O’Shea, B.; Scheinker, A. Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II. Information 2021, 12, 61. Emma, C.; Edelen, A.; Hanuka, A.; O’Shea, B.; Scheinker, A. Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II. Information 2021, 12, 61.

Journal reference: Information 2021, 12, 61
DOI: 10.3390/info12020061

Abstract

We discuss the implementation of a suite of virtual diagnostics at the FACET-II facility currently under commissioning at SLAC National Accelerator Laboratory. The diagnostics will be used for prediction of the longitudinal phase space along the linac, spectral reconstruction of the bunch profile and non-destructive inference of transverse beam quality (emittance) using edge radiation at the injector dogleg and bunch compressor locations. These measurements will be folded in to adaptive feedbacks and ML-based reinforcement learning controls to improve the stability and optimize the performance of the machine for different experimental configurations. In this paper we describe each of these diagnostics with expected measurement results based on simulation data and discuss progress towards implementation in regular operations.

Subject Areas

machine learning; virtual diagnostics; reinforcement learning control

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