Author: Thévenet, M.
Paper Title Page
MOOYGD1
Experiments Towards High-Repetition Rate Plasma Wakefield Acceleration at FLASHForward  
 
  • G. Loisch, J. Beinortaite, G.J. Boyle, R.T.P. D’Arcy, S. Diederichs, J.M. Garland, P. Gonzalez-Caminal, C.A. Lindstrøm, J. Osterhoff, T. Parikh, S. Schreiber, S. Schröder, M. Thévenet, S. Wesch, M. Wing
    DESY, Hamburg, Germany
  • J. Chappell, M. Wing
    UCL, London, United Kingdom
  • B. Foster
    JAI, Oxford, United Kingdom
  • P. Gonzalez-Caminal
    Universität Hamburg, Hamburg, Germany
 
  Beam-driven plasma-wakefield acceleration (PWFA) is one of the most promising techniques to reduce significantly the size and cost of future lepton accelerators. Huge steps have been taken in the last decades towards achieving high acceleration gradients with simultaneous beam-quality preservation. However, in order to match both the luminosity demands of high-energy physics and the brilliance requirements of photon science, PWFA must be capable of accelerating thousands of bunches per second ’ orders of magnitude beyond the current state of the art. Historically, investigation of the rate limitation in plasmas was limited by the number of bunches available from the accelerator front-end. The FLASHForward facility, which is driven by the superconducting linac of the FLASH free-electron laser, is the first experiment capable of addressing this issue. We report here on first experimental results from the facility, aimed at determining the repetition rate limit of plasma accelerators arising from fundamental plasma processes* and finally advancing the repetition rate of PWFA from proof-of-principle experiments at a few bunches per second to a competitive plasma accelerator.
* R. D’Arcy et al., Recovery time of a plasma-wakefield accelerator, Nature (in press)
 
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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
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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  
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