TY - GEN
T1 - Development of a 6D Electron Beam Diagnostics Suite for Novel Acceleration Experiments at FEBE on CLARA
AU - Pacey, Thomas
AU - Angal-Kalinin, Deepa
AU - Bainbridge, Alexander
AU - Henderson, James
AU - Jones, James
AU - Joshi, Nirav
AU - Mathisen, Storm
AU - Overton, Toby
AU - Pollard, Amelia
AU - Saveliev, Yuri
AU - Snedden, Edward
AU - Swain, Catherine
AU - Tollervey, Calum
AU - Walsh, David
AU - Wolfenden, Joseph
PY - 2022/11/13
Y1 - 2022/11/13
N2 - The FEBE beamline at the CLARA facility will combine a 250 MeV FEL quality electron beam with a 100 TW class laser. One area of research FEBE will support is novel acceleration schemes; both structure and plasma based. There are stringent diagnostic requirements for measuring the input electron beam and challenges in characterisation of the accelerated beams produced by these novel schemes. Several of these challenges include measurement of: micrometer scale transverse profiles, 10 fs scale bunch lengths, single shot emittance, broadband energy spectra at high resolution, and laser-electron time of arrival jitter. Furthermore, novel shot-by-shot non-invasive diagnostics are required for machine learning driven optimisation and feedback systems. This paper presents an overview of R activities in support of developing a 6D diagnostics suite to meet these challenges.
AB - The FEBE beamline at the CLARA facility will combine a 250 MeV FEL quality electron beam with a 100 TW class laser. One area of research FEBE will support is novel acceleration schemes; both structure and plasma based. There are stringent diagnostic requirements for measuring the input electron beam and challenges in characterisation of the accelerated beams produced by these novel schemes. Several of these challenges include measurement of: micrometer scale transverse profiles, 10 fs scale bunch lengths, single shot emittance, broadband energy spectra at high resolution, and laser-electron time of arrival jitter. Furthermore, novel shot-by-shot non-invasive diagnostics are required for machine learning driven optimisation and feedback systems. This paper presents an overview of R activities in support of developing a 6D diagnostics suite to meet these challenges.
UR - https://jacow.org/ibic2022/doi/JACoW-IBIC2022-MO1C3.html
U2 - 10.18429/JACOW-IBIC2022-MO1C3
DO - 10.18429/JACOW-IBIC2022-MO1C3
M3 - Conference contribution
BT - Proceedings of the 11th International Beam Instrumentation Conference
ER -