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Title ACCELERATOR CHALLENGES OF THE LHeC PROJECT
Authors B. Holzer, K. AndrĂ©, O. BrĂ¼ning, M. Klein, Slawomir Bogacz
JLAB number JLAB-ACP-21-3399
LANL number (None)
Other number DOE/OR/23177-5223
Document Type(s) (Meeting) 
Category: Beam Dynamics
Associated with EIC: No
Supported by Jefferson Lab LDRD Funding: No
Funding Source: High Energy Physics (HEP)
 

Meeting
Poster compiled for IPAC21

Proceedings
Proceedings of IPAC 2021
Edited By Liu Lin, John M. Byrd, Regis Neuenschwander, Renan Picoreti, Volker R. W. Schaa
JACOW (2021)
Page(s) 2570-2573
Publication Abstract: The LHeC project studies the design of a future electron proton collider at CERN that will run in parallel to the standard LHC operation. For this purpose, the existing LHC storage ring is considered to be combined with an Energy Recovery Linac (ERL), that will accelerate electrons up to a kinetic energy of 50 GeV. This concept might also be applied to the FCC-eh, where even larger centre of mass energies are obtained. The peak luminosity of 10^34 requires a sophisticated design of the RF structures, linacs, arcs and interaction region lattices. For achieving highest luminosity and performance, the electrons are accelerated such that, after the interaction point, their energy is recovered through the same RF structures. While this energy recovery concept is a very promising approach, and will be investigated at the PERLE test facility, severe challenges are set by the layout of the interaction region, the beam separation concept and the design of the linac and arc lattice for highest possible momentum acceptance. The control of the emittance and beam-beam effect of both, electron and proton beams, has been studied in front-to-end simulations and will be presented. We summarise the design principles of the ERL, the optimisation of the lattice and the main parameters of the project.
Experiment Numbers: other
Group: Ctr for Adv Stud of Accel
Document: pdf
DOI: https://doi.org/10.18429/JACoW-IPAC2021-WEPAB001
Accepted Manuscript: wepab001.pdf
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Supporting Datasets: