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EZ: An Efficient, Charge Conserving Current Deposition Algorithm for Electromagnetic Particle-In-Cell Simulations

Steiniger, K.; Widera, R.; Bastrakov, S.; Bussmann, M.; Chandrasekaran, S.; Hernandez, B.; Hübl, A.; Juckeland, G.; Kelling, J.; Leinhauser, M.; Pausch, R.; Rogers, D.; Schramm, U.; Young, J.; Debus, A.

We present EZ, a novel Current Deposition algorithm for particle-in-cell simulations, which calculates the current density field due to macro-particle motion within a time step by solving the electrodynamic continuity equation.
Being a charge conserving hybridization of \textbf{E}sirkepov's method and \textbf{Z}igZag, we refer to it as ``EZ'' as shorthand for ``Esirkepov meets ZigZag''.
EZ achieves the same level of charge conservation as the commonly used method by Esirkepov, yet reaches higher performance for macro-particle assignment-functions up to third-order.
Key considerations of its implementation in PIConGPU, an open source, C++, performance portable, fully relativistic 3D3V particle-in-cell code, are outlined in addition to the detailed description of EZ along with remarks on its optimization and customization.

Keywords: EZ; particle-in-cell; current deposition; PIConGPU; high-performance computing

Related publications

  • Computer Physics Communications 291(2023), 108849
    Online First (2023) DOI: 10.1016/j.cpc.2023.108849
  • Invited lecture (Conferences)
    Advanced Accelerators Concepts Workshops 2022, 06.-11.11.2022, Hauppauge, New York, United States of America

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  • Secondary publication expected from 16.07.2024

Permalink: https://www.hzdr.de/publications/Publ-34476