Femtosecond X-ray spectroscopy of haem proteins

Absolute and non-invasive determination of the electron bunch length in a free electron laser using a bunch compressor monitor

In a linac driven Free Electron Laser (FEL), the shot-to-shot and non-invasive monitoring of the electron bunch length is normally ensured by Bunch Compressor Monitors (BCMs). The bunch-length dependent signal of a BCM results from the detection and integration-over a given frequency band-of the temporal coherent enhancement of the radiation spectral energy emitted by the electron beam while experiencing a longitudinal compression. In this work, we present a method that permits to express the relative variation of the bunch length as a function of the relative statistical fluctuations of the BCM and charge signals. Furthermore, in the case of a BCM equipped with two detectors simultaneously operating in two distinct wavelength bands, the method permits an absolute determination of the electron bunch length. The proposed method is beneficial to a FEL. Thanks to it, the machine compression feedback can be tuned against the absolute measurement of the bunch length rather than a bunch-length dependent signal. In a CW-superconducting-linac driven FEL, it can offer the precious opportunity to implement a fully non-invasive and absolute diagnostics of the bunch length.

Machine learning based longitudinal virtual diagnostics at SwissFEL

The bunch length in a linac driven Free Electron Laser (FEL) is a major parameter to be characterized to optimize the final accelerator performance. In linear machines, this observable is typically determined from the beam imaged on a screen located downstream of a Transverse Deflecting Structure (TDS) used to impinge a time dependent kick along the longitudinal coordinate of the beam. This measurement is typically performed during the machine setup and only sporadically to check the beam duration, but it cannot be continuously repeated because it is time consuming and invasive. A non-invasive method to determine the electron bunch length has already been presented in the past. This method is based on the analysis of the synchrotron radiation light spot emitted by the bunch passing through a magnetic chicane, provided that the energy chirp impinged on the bunch by the upstream radio frequency structures is known. In order to overcome a systematic discrepancy affecting the synchrotron radiation monitor based results compared to the absolute TDS based ones, we implemented and optimized a machine learning approach to predict the bunch length downstream of the two SwissFEL compression stages-from about 10 fs up to about 2 ps-as well as the beam longitudinal profile at the first one.