Non-invasive Longitudinal Beam Profile Diagnostic Exploiting Coherent Cherenkov Diffraction Radiation

Kirill Fedorov

Research output: ThesisDoctoral Thesis

164 Downloads (Pure)

Abstract

In this thesis, the possibility of noninvasive longitudinal beam profile diagnostic ex- ploiting Coherent Cherenkov Diffraction Radiation (ChDR) was considered in details. To achieve this a number of practical and theoretical problems have been solved.
First, a system for Coherent Cherenkov Diffraction Radiation generation has been developed as well as system for signal detection and spectral characteristic analysis. Experimental studies has been organized at the CLARA facilities based at Daresbury (United Kingdom) laboratory. With sub-ps long electron bunches, the measurements of the emitted coherent radiation spectra extend up to the THz frequency range was enough to provide its spectral analysis using Martin-Pupplet interferometer.
Second, investigation of the theoretical properties of ChDR taking into account the dielectric properties of the radiator (Teflon target) has been provided. The Polariza- tion Current Approach (PCA) has been used for the computation of the ChDR single electron spectrum generated by a prismatic shape target. The chosen approach allowed us to account for all essential experimental parameters, such as electron beam prop- erties, the distance between electron beam and radiator, the radiator dimensions, and the radiator dielectric properties.
Finally, by using obtained experimental data and theoretical evaluations, set of the longitudinal bunch profiles have been reconstructed. To reconstruct the bunch profile, the Kramers-Kronig analysis has been used.
As a result, it was the first demonstration of CChDR being used for noninvasive (not cutting the beam) longitudinal beam profile diagnostic, and the reliability of the results obtained are confirmed by the well-studied method based on Coherent Transition Radiation (CTR).
Original languageEnglish
QualificationPh.D.
Awarding Institution
  • Royal Holloway, University of London
Supervisors/Advisors
  • Karataev, Pavel, Supervisor
Award date1 Jun 2022
Publication statusUnpublished - 2021

Cite this