PICLas is a parallel, three-dimensional particle-based kinetic simulation framework combining the Particle-in-Cell (PIC), Direct Simulation Monte Carlo (DSMC), BGK, and Fokker-Planck methods for the simulation of plasma dynamics and rarefied gas flows.
The code is developed cooperatively by the Institute of Space Systems (IRS) and the spin-off company boltzplatz. PICLas is designed to be a flexible, modular particle simulation suite, supporting unstructured meshes, MPI parallelism, and dynamic load balancing for high-performance computing environments.
 |
 |
 |
 |
 |
 |
 |
 |
- Particle-in-Cell (PIC) solver for self-consistent electromagnetic and electrostatic plasma simulations
- Direct Simulation Monte Carlo (DSMC) for rarefied, non-equilibrium gas flows
- Coupled PIC-DSMC for reactive plasma flow simulation
- BGK and Fokker-Planck collision operators as computationally efficient alternatives to DSMC in near-continuum regimes
- Support for unstructured, high-order meshes
- MPI parallelization with dynamic load balancing for large-scale HPC simulations
- Variable particle weighting (including radial/cell-local weighting for 2D/axisymmetric cases)
- Surface interaction models: data-driven scattering, surface chemistry, and charging
Full documentation, including the installation procedure, is available in the PICLas User Guide. Installation instructions specifically can be found in Chapter 2.
Pre-compiled executables (that only require pre-installed MPI for parallel execution) for Linux can directly be downloaded as AppImage containers from the PICLas release tag assets.
PICLas is built using CMake. A typical build looks like:
git clone https://github.com/piclas-framework/piclas.git
cd piclas
mkdir build && cd build
cmake ..
make -jSee the User Guide for detailed configuration options, compiler requirements, and dependency setup.
PICLas uses several external libraries as well as auxiliary functions from open source projects, including:
A set of tutorials covering common use cases (PIC, DSMC, and coupled simulations) is included in the tutorials directory and documented in the User Guide: Tutorials.
An overview of the regression tests used for continuous integration is given in REGGIE.md.
PICLas is a scientific project. If you use PICLas for publications or presentations in science, please support the project by citing following paper and the repository. In addition, if you use specific methods, please also cite the corresponding papers shown in REFERENCES.md
For general citation cite the repository and the general publication about PICLas:
-
Repository: use GitHub's
Cite this repositoryoption -
Paper:
@article{fasoulas_combining_2019,
author = "Fasoulas, S. and Munz, C.-D. and Pfeiffer, M. and Beyer, J. and Binder, T. and Copplestone, S. and Mirza, A. and Nizenkov, P. and Ortwein, P. and Reschke, W.",
title = "Combining particle-in-cell and direct simulation Monte Carlo for the simulation of reactive plasma flows",
journal = "Physics of Fluids",
volume = "31",
number = "7",
pages = "072006-1 -- 072006-19",
year = "2019",
month = "07",
doi = "10.1063/1.5097638",
}We welcome contributions of all kinds - from bug fixes and documentation improvements to new features. Please see CONTRIBUTING.md for guidelines.
You can also reach the team through:
- Academic: Numerical Modelling and Simulation Group, Institute of Space Systems, University of Stuttgart
- Simulation services & training: boltzplatz - numerical plasma dynamics GmbH
A list of current contributors is maintained in CONTRIBUTORS.md.
The PICLas code is licensed under the GNU General Public License v3.0. The license can be found in LICENSE.md and the list of contributors in CONTRIBUTORS.md.