This section allows you to download input files that correspond to different physical situations.
We provide two kinds of inputs:
PICMI python input files, with parameters described here.
inputsfiles, with parameters described here,
For a complete list of all example input files, also have a look at our Examples/ directory. It contains folders and subfolders with self-describing names that you can try. All these input files are automatically tested, so they should always be up-to-date.
LWFA: External injection in the boosted frame
LWFA: Ionization injection in the lab frame using a LASY data file
PWFA: External injection in the boosted frame
PWFA: Self-injection in the lab frame
MVA (3D & RZ)
MR for the planar example?
Particle Accelerator & Beam Physics
Beam Transport or Injector
High Energy Astrophysical Plasma Physics
ARTEMIS (Adaptive mesh Refinement Time-domain ElectrodynaMIcs Solver) is based on WarpX and couples the Maxwell’s equations implementation in WarpX with classical equations that describe quantum material behavior (such as, LLG equation for micromagnetics and London equation for superconducting materials) for quantifying the performance of next-generation microelectronics.
Magnetically Confined Plasma with a Single Coil - Magnetic bottle: simple geometry with an external field
Fundamental Plasma Physics
Expanding Sphere example
Kinetic-fluid Hybrid Models
Several examples and benchmarks of the kinetic-fluid hybrid model are shown below. The first few examples are replications of the verification tests described in Muñoz et al. . The hybrid-PIC model was added to WarpX in PR #3665 - the figures in the examples below were generated at that time.
High-Performance Computing and Numerics
The following examples are commonly used to study the performance of WarpX, e.g., for computing efficiency, scalability, and I/O patterns. While all prior examples are used for such studies as well, the examples here need less explanation on the physics, less-detail tuning on load balancing, and often simply scale (weak or strong) by changing the number of cells, AMReX block size and number of compute units.
Manipulating fields via Python
TODO: The section needs to be sorted into either science cases (above) or later sections (workflows and Python API details).
An example of using Python to access the simulation charge density, solve the Poisson equation (using
superLU) and write the resulting electrostatic potential back to the simulation is given in the input file below. This example uses the
fields.py module included in the
An example of initializing the fields by accessing their data through Python, advancing the simulation for a chosen number of time steps, and plotting the fields again through Python. The simulation runs with 128 regular cells, 8 guard cells, and 10 PML cells, in each direction. Moreover, it uses div(E) and div(B) cleaning both in the regular grid and in the PML and initializes all available electromagnetic fields (E,B,F,G) identically.
Many Further Examples, Demos and Tests
WarpX runs over 200 integration tests on a variety of modeling cases, which validate and demonstrate its functionality. Please see the Examples/Tests/ directory for many more examples.
P.A. Muñoz, N. Jain, P. Kilian, and J. Büchner. A new hybrid code (chief) implementing the inertial electron fluid equation without approximation. Computer Physics Communications, 224:245–264, 2018. URL: https://www.sciencedirect.com/science/article/pii/S0010465517303521, doi:https://doi.org/10.1016/j.cpc.2017.10.012.
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S. C. Wilks, A. B. Langdon, T. E. Cowan, M. Roth, M. Singh, S. Hatchett, M. H. Key, D. Pennington, A. MacKinnon, and R. A. Snavely. Energetic proton generation in ultra-intense laser–solid interactions. Physics of Plasmas, 8(2):542–549, 02 2001. URL: https://doi.org/10.1063/1.1333697, arXiv:https://pubs.aip.org/aip/pop/article-pdf/8/2/542/12669088/542\_1\_online.pdf, doi:10.1063/1.1333697.
S. S. Bulanov, A. Brantov, V. Yu. Bychenkov, V. Chvykov, G. Kalinchenko, T. Matsuoka, P. Rousseau, S. Reed, V. Yanovsky, D. W. Litzenberg, K. Krushelnick, and A. Maksimchuk. Accelerating monoenergetic protons from ultrathin foils by flat-top laser pulses in the directed-coulomb-explosion regime. Phys. Rev. E, 78:026412, Aug 2008. URL: https://link.aps.org/doi/10.1103/PhysRevE.78.026412, doi:10.1103/PhysRevE.78.026412.
Andrea Macchi, Marco Borghesi, and Matteo Passoni. Ion acceleration by superintense laser-plasma interaction. Rev. Mod. Phys., 85:751–793, May 2013. URL: https://link.aps.org/doi/10.1103/RevModPhys.85.751, doi:10.1103/RevModPhys.85.751.
B. Dromey, S. Kar, M. Zepf, and P. Foster. The plasma mirror—A subpicosecond optical switch for ultrahigh power lasers. Review of Scientific Instruments, 75(3):645–649, 02 2004. URL: https://doi.org/10.1063/1.1646737, arXiv:https://pubs.aip.org/aip/rsi/article-pdf/75/3/645/8814694/645\_1\_online.pdf, doi:10.1063/1.1646737.
C. Rödel, M. Heyer, M. Behmke, M. Kübel, O. Jäckel, W. Ziegler, D. Ehrt, M. C. Kaluza, and G. G. Paulus. High repetition rate plasma mirror for temporal contrast enhancement of terawatt femtosecond laser pulses by three orders of magnitude. Applied Physics B, 103(2):295–302, November 2010. URL: http://dx.doi.org/10.1007/s00340-010-4329-7, doi:10.1007/s00340-010-4329-7.
A. Le, W. Daughton, H. Karimabadi, and J. Egedal. Hybrid simulations of magnetic reconnection with kinetic ions and fluid electron pressure anisotropy. Physics of Plasmas, 03 2016. 032114. URL: https://doi.org/10.1063/1.4943893, doi:10.1063/1.4943893.
M. M. Turner, A. Derzsi, Z. Donkó, D. Eremin, S. J. Kelly, T. Lafleur, and T. Mussenbrock. Simulation benchmarks for low-pressure plasmas: Capacitive discharges. Physics of Plasmas, 01 2013. 013507. URL: https://doi.org/10.1063/1.4775084, doi:10.1063/1.4775084.
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