Journal Article

PUBDB-2021-00902

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Bayesian Optimization of a Laser-Plasma Accelerator

Jalas, S. (Corresponding author)CFEL*Extern* ; Kirchen, M.CFEL*Extern* ; Messner, P.CFEL*Extern*DESY* ; Winkler, P.DESY* ; Hübner, L.DESY* ; Dirkwinkel, J.DESY* ; Schnepp, M.CFEL*Extern* ; Lehe, R. ; Maier, A.CFEL*Extern*DESY*

2021
APS College Park, Md.

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Please use a persistent id in citations: doi:10.1103/PhysRevLett.126.104801  doi:10.3204/PUBDB-2021-00902

Abstract: Generating high-quality laser-plasma accelerated electron beams requires carefully balancing a plethora of physical effects and is therefore challenging—both conceptually and in experiments. Here, we use Bayesian optimization of key laser and plasma parameters to flatten the longitudinal phase space of an ionization-injected electron bunch via optimal beam loading. We first study the concept with particle-in-cell simulations and then demonstrate it in experiments. Starting from an arbitrary set point, the plasma accelerator autonomously tunes the beam energy spread to the subpercent level at 254 MeV and 4.7 pC/MeV spectral density. Finally, we study a robust regime, which improves the stability of the laser-plasma accelerator and delivers sub-five-percent rms energy spread beams for 90% of all shots.

Keyword(s): Plasma and Beam Physics

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Contributing Institute(s):

1. UNI/EXP (CFEL-LUX)
2. Plasma Accelerators (MPA)
3. Laser für Plasmabeschleunigung (MLS)

Research Program(s):

1. 621 - Accelerator Research and Development (POF4-621) (POF4-621)

Experiment(s):

1. Relativistic Electron Gun for Atomic Exploration

Appears in the scientific report 2021

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Electronics and Telecommunications Collection ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; Nationallizenz ; SCOAP3 sponsored Journal ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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