Ultra-short Bunch Length Measurements with Femtosecond Resolution - position filled
(University of Liverpool)
This project concerns the development of a superior diagnostic technique that provides excellent time resolution whilst being non-invasive. Currently, longitudinal diagnostics with such resolution is limited to only a handful of solutions. Each one has their strengths and weaknesses, but generally there is a compromise between longitudinal profile resolution, number of shots required, and ease of application.
The Fellow will develop a new longitudinal profile monitor based on broadband imaging of coherent radiation which is simple to operate on a shot-to-shot basis and provides a fs-resolution measurement of the bunch profile width and features. Whilst targeting the specific parameters of EuPRAXIA, an emphasis will be on developing a technique that can be easily integrated into essentially any short pulse accelerators, i.e. also including Free Electron Lasers or other plasma accelerator schemes such as AWAKE. They will progress the technique to form part of a virtual diagnostics toolkit – an entirely new approach in particle accelerators.
A THz-based imaging system has already been developed by the QUASAR Group at the University of Liverpool to image the source distribution of coherent transition (CTR) or diffraction radiation (CDR) which theory and simulations have shown is dependent on bunch length. A comparison of the bunch lengths obtained with this method and ELEGANT simulations was done and an excellent agreement between the measured CTR and the ELEGANT FWHM bunch length values was found.
This project builds on this existing framework to progress the monitor towards a non-invasive single-shot method of measuring detailed longitudinal profile information, working closely with company D-Beam and INFN, where tests with beam will be conducted. The Fellow will study optimum integration so the monitor can operate online and non-invasively. They will then integrate machine learning techniques to combine this monitor with existing diagnostic systems to develop a suite of so-called “virtual diagnostics” for EuPRAXIA and beyond. The process will involve implementing several diagnostics upstream and, crucially, away from the interaction point (IP). By using a combination of invasive diagnostics at the IP and machine parameters, a machine learning model will be developed which directly maps beam parameters upstream, to those at the IP. Once this training is complete, the IP diagnostics can be removed, and the measurements upstream will form a robust, online, virtual diagnostic system for the IP.
The Fellow will have access to the wide-ranging EuPRAXIA-DN training program which will include several international schools and workshops on plasma accelerator science and technology, as well as complementary skills.