Author: Martinez de la Ossa, A.
Paper Title Page
WEPOST029 First Start-to-End Simulations of the 6 GeV Laser-Plasma Injector at DESY 1757
 
  • S.A. Antipov, I.V. Agapov, R. Brinkmann, Á. Ferran Pousa, M.A. Jebramcik, A. Martinez de la Ossa, M. Thévenet
    DESY, Hamburg, Germany
 
  DESY is studying the feasibility of a 6 GeV laser-plasma injector for top-up operation of its future flagship synchrotron light source PETRA IV. A potential design of such an injector involves a single plasma stage, a beamline for beam capture and phase space manipulation, and a X-band rf energy compressor. Numerical tracking with realistic beam distributions shows that an energy variation below 0.1%, rms and a transverse emittance about 1 nm-rad, rms can be achieved under realistic timing, energy, and pointing jitters. PETRA IV injection efficiency studies performed with a conservative 5% beta-beating indicate negligible beam losses for the simulated beams during top-up. Provided the necessary progress on high-power lasers and plasma cells, the laser plasma injector could become a competitive alternative to the conventional injector chain.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST029  
About • Received ※ 02 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 16 June 2022
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
WEPOST030 Multitask Optimization of Laser-Plasma Accelerators Using Simulation Codes with Different Fidelities 1761
 
  • Á. Ferran Pousa, M. Kirchen, A. Martinez de la Ossa, M. Thévenet
    DESY, Hamburg, Germany
  • S.T.P. Hudson, J.M. Larson
    ANL, Lemont, Illinois, USA
  • A. Huebl, R. Lehé, J.-L. Vay
    LBNL, Berkeley, California, USA
  • S. Jalas
    University of Hamburg, Hamburg, Germany
 
  When designing a laser-plasma acceleration experiment, one commonly explores the parameter space (plasma density, laser intensity, focal position, etc.) with simulations in order to find an optimal configuration that, for example, minimizes the energy spread or emittance of the accelerated beam. However, laser-plasma acceleration is typically modeled with full particle-in-cell (PIC) codes, which can be computationally expensive. Various reduced models can approximate beam behavior at a much lower computational cost. Although such models do not capture the full physics, they could still suggest promising sets of parameters to be simulated with a full PIC code and thereby speed up the overall design optimization. In this work we automate such a workflow with a Bayesian multitask algorithm, where each task has a different fidelity. This algorithm learns from past simulation results from both full PIC codes and reduced PIC codes and dynamically chooses the next parameters to be simulated. We illustrate this workflow with a proof-of-concept optimization using the Wake-T and FBPIC codes. The libEnsemble library is used to orchestrate this workflow on a modern GPU-accelerated high-performance computing system.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST030  
About • Received ※ 08 June 2022 — Accepted ※ 11 June 2022 — Issue date ※ 14 June 2022  
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)