There is a newer version of the record available.

Published June 3, 2020 | Version 0.5.0
Software Open

PIConGPU 0.5.0: Perfectly Matched Layer (PML) and Bug Fixes

Creators

  • 1. HZDR, TU Dresden
  • 2. HZDR
  • 3. LogMeIn, Inc.

Description

This release adds a new field absorber for the Yee solver, convolutional perfectly matched layer (PML). Compared to the still supported exponential damping absorber, PML provides better absorption rate and much less spurious reflections.

We added new plugins for computing emittance and transition radiation, particle rendering with the ISAAC plugin, Python tools for reading and visualizing output of a few plugins.

The release also adds a few quality-of-life features, including a new memory calculator, better command-line experience with new options and bash-completion, improved error handling, cleanup of the example setups, and extensions to documentation.

Please refer to our ChangeLog for a full list of features, fixes and user interface changes before getting started.

Thanks to Igor Andriyash, Sergei Bastrakov, Xeinia Bastrakova, Andrei Berceanu, Finn-Ole Carstens, Alexander Debus, Jian Fuh Ong, Marco Garten, Axel Huebl, Sophie Rudat (Koßagk), Anton Lebedev, Felix Meyer, Pawel Ordyna, Richard Pausch, Franz Pöschel, Adam Simpson, Sebastian Starke, Klaus Steiniger, René Widera for contributions to this release!

Files

ComputationalRadiationPhysics/picongpu-0.5.0.zip

Files (7.1 MB)

Additional details

Related works

Is supplement to
https://github.com/ComputationalRadiationPhysics/picongpu/tree/0.5.0 (URL)

References

  • L. V. Keldysh (1965). Ionization in the field of a strong electromagnetic wave.
  • D. Bauer and P. Mulser (1999). Exact field ionization rates in the barrier-suppression regime from numerical time-dependent Schrödinger-equation calculations. DOI:10.1103/PhysRevA.59.569
  • R. Pausch et al. (2014). How to test and verify radiation diagnostics simulations within particle-in-cell frameworks. DOI:10.1016/j.nima.2013.10.073
  • A. Huebl (2014). Injection Control for Electrons in Laser-Driven Plasma Wakes on the Femtosecond Time Scale. DOI:10.5281/zenodo.15924
  • A. Gonoskov et al. (2015). Extended particle-in-cell schemes for physics in ultrastrong laser fields: Review and developments. DOI:10.1103/PhysRevE.92.023305
  • A. Huebl et al. (2015). openPMD: A meta data standard for particle and mesh based data. DOI:10.5281/zenodo.591699
  • M. Vranic et al. (2016). Classical radiation reaction in particle-in-cell simulations. DOI:10.1016/j.cpc.2016.04.002
  • A. Matthes et al. (2016). In situ, steerable, hardware-independent and data-structure agnostic visualization with ISAAC. DOI:10.14529/jsfi160403
  • A. Huebl et al. (2017). On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective. DOI:10.1007/978-3-319-67630-2_2
  • R. Pausch et al. (2018). Quantitatively consistent computation of coherent and incoherent radiation in particle-in-cell codes - a general form factor formalism for macro-particles. DOI:10.1016/j.nima.2018.02.020
  • A. Huebl (2019). PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware. DOI:10.5281/zenodo.3266820