2019
DOI: 10.1103/physrevaccelbeams.22.031301
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Influence of proton bunch parameters on a proton-driven plasma wakefield acceleration experiment

Abstract: We use particle-in-cell (PIC) simulations to study the effects of variations of the incoming 400 GeV proton bunch parameters on the amplitude and phase of the wakefields resulting from a seeded selfmodulation (SSM) process. We find that these effects are largest during the growth of the SSM, i.e. over the first five to six meters of plasma with an electron density of 7 × 10 14 cm −3 . However, for variations of any single parameter by ±5%, effects after the SSM saturation point are small. In particular, the ph… Show more

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Cited by 2 publications
(2 citation statements)
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“…There may be additional variations in bunch waist size and location, and emittance that we do not monitor for each event. The influence of these variations on the phase can in principle be obtained from numerical simulations [21], though reaching percent level precision is very challenging. Third, variations due to the measurement accuracy influenced by the streak camera resolution of the modulation, the limited number of micro-bunches per image, signal noise, and uncertainties in determining the position of the LRS (0.16 ps).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…There may be additional variations in bunch waist size and location, and emittance that we do not monitor for each event. The influence of these variations on the phase can in principle be obtained from numerical simulations [21], though reaching percent level precision is very challenging. Third, variations due to the measurement accuracy influenced by the streak camera resolution of the modulation, the limited number of micro-bunches per image, signal noise, and uncertainties in determining the position of the LRS (0.16 ps).…”
Section: Resultsmentioning
confidence: 99%
“…With sufficiently strong initial amplitude, the phase of the wakefields varies by only a small fraction of 2π from event to event, the characteristic of seeded SM (SSM) [13]. This is despite natural variations of the incoming bunch parameters [21]. We thus observe the transition from SMI to SSM.…”
Section: ]mentioning
confidence: 85%