WarpX: efficient modeling of plasma-based accelerators with mesh refinement

POSTER

Abstract

Plasma-based accelerators are being developed to provide a more compact and economical alternative to standard accelerator technology. High accelerating gradients were demonstrated in centimeter long plasmas. Recent studies focus on mitigating multiple non-linear, fast processes and instabilities that deteriorate the quality of plasma-based accelerated beams. High-fidelity numerical codes that can model beam propagation in plasma fields are necessary to study those nonlinear processes. Simulations are typically computationally demanding because they resolve small structures over large distances. The Adaptive Mesh Refinement (AMR) technique, where selected regions are modeled with higher resolution, can make simulations more efficient. For the Exascale Computing Project, we have been developing the WarpX tool that incorporates AMR through the AMReX framework in the Particle-In-Cell (PIC) code Warp. We present recent studies of beam evolution in consecutive plasma stages, done with and without using mesh-refinement.

*Supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration).

Authors

  • Ligia Diana Amorim

    • Lawrence Berkeley National Laboratory
  • Jean-Luc Vay

    • Lawrence Berkeley National Laboratory
  • Ann Almgren

    • Lawrence Berkeley National Laboratory
  • John Bell

    • Lawrence Berkeley National Laboratory
  • Revathi Jambunathan

    • Lawrence Berkeley National Laboratory
  • Remi Lehe

    • Lawrence Berkeley National Laboratory
  • Andrew Myers

    • Lawrence Berkeley National Laboratory
    • LBNL
  • Jaehong Park

    • Lawrence Berkeley National Laboratory
    • LBNL
  • Olga Shapoval

    • Lawrence Berkeley National Laboratory
    • LBNL
  • Maxence Thévenet

    • Lawrence Berkeley National Laboratory
    • LBNL
  • Weiqun Zhang

    • Lawrence Berkeley National Laboratory
  • David Grote

    • Lawrence Livermore National Laboratory
  • Mark Hogan

    • SLAC National Accelerator Laboratory
    • SLAC
  • Lixin Ge

    • SLAC National Accelerator Laboratory
    • SLAC
  • Cho Ng

    • SLAC National Accelerator Laboratory
    • SLAC