Update on the Modeling of Chains of Plasma Accelerator Stages for Future Colliders

ORAL

Abstract

One of the most challenging application of plasma accelerators is the development of a plasma-based collider for high-energy physics studies. Fast and accurate simulation tools are essential to study the physics toward configurations that enable the production and acceleration of very small beams with low energy spread and emittance preservation over long distances, as required for a collider. The Particle-In-Cell code WarpX is being developed by a team of the U.S. DOE Exascale Computing Project (with non-U.S. collaborators on part of the code) to enable the modeling of chains of tens of plasma accelerators on exascale supercomputers, for collider designs. We will present our latest application of the code to the modeling of up to 10 consecutive multi-GeV stages on the GPU-accelerated Summit supercomputer, together with the latest developments that made it possible.

Authors

  • Jean-Luc Vay

    LBNL, Lawrence Berkeley National Laboratory

  • Ann Almgren

    Lawrence Berkeley National Laboratory

  • Diana Amorim

    Lawrence Berkeley National Laboratory

  • John Bell

    Lawrence Berkeley National Laboratory

  • Lixin Ge

    SLAC National Accelerator Laboratory

  • Kevin Gott

    Lawrence Berkeley National Laboratory

  • David Grote

    LLNL, Lawrence Livermore National Laboratory

  • Mark Hogan

    SLAC National Accelerator Laboratory

  • Axel Huebl

    LBNL, previously HZDR, Lawrence Berkeley National Laboratory

  • Revathi Jambunathan

    Lawrence Berkeley National Laboratory

  • Remi Lehe

    LBNL, Lawrence Berkeley National Laboratory

  • Andrew Myers

    Lawrence Berkeley National Laboratory

  • Cho Ng

    SLAC National Accelerator Laboratory

  • Michael Rowan

    Lawrence Berkeley National Laboratory

  • Olga Shapoval

    Lawrence Berkeley National Laboratory

  • Maxence Thevenet

    DESY, previously LBNL, DESY

  • Eloise Yang

    Lawrence Berkeley National Laboratory

  • Weiqun Zhang

    Lawrence Berkeley National Laboratory

  • Yinjian Zhao

    Lawrence Berkeley National Laboratory

  • Edoardo Zoni

    Lawrence Berkeley National Laboratory