Simulation and Experimental Study of Proton Bunch Self-Modulation in Plasma with Linear Density Gradients
P.I. Morales Guzm\'an, P. Muggli, R. Agnello, C.C. Ahdida, M. Aladi,, M.C. Amoedo Goncalves, Y. Andrebe, O. Apsimon, R. Apsimon, A.-M. Bachmann,, M.A. Baistrukov, F. Batsch, M. Bergamaschi, P. Blanchard, F. Braunm\"uller,, P.N. Burrows, B. Buttensch\"on, A. Caldwell, J. Chappell

TL;DR
This study combines simulations and experiments to analyze how linear plasma density gradients affect proton bunch self-modulation, revealing the impact on charge, frequency, and wakefield dephasing.
Contribution
It provides a detailed comparison of simulation and experimental results, highlighting the effects of plasma density gradients on proton bunch self-modulation.
Findings
Negative gradients reduce modulated bunch charge
Modulation frequency varies with plasma gradient
Dephasing causes charge loss in wakefields
Abstract
We present numerical simulations and experimental results of the self-modulation of a long proton bunch in a plasma with linear density gradients along the beam path. Simulation results agree with the experimental results reported in arXiv:2007.14894v2: with negative gradients, the charge of the modulated bunch is lower than with positive gradients. In addition, the bunch modulation frequency varies with gradient. Simulation results show that dephasing of the wakefields with respect to the relativistic protons along the plasma is the main cause for the loss of charge. The study of the modulation frequency reveals details about the evolution of the self-modulation process along the plasma. In particular for negative gradients, the modulation frequency across time-resolved images of the bunch indicates the position along the plasma where protons leave the wakefields. Simulations and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
