Key Points
Introduction to WarpX
🔮 The particle-in-cell method is used to simulate the self-consistent dynamics of relativistic charged particles
🚀 WarpX is a open-source high-performance particle-in-cell code
✨ WarpX is used in a variety of scientif domains
Install
🎯 WarpX is easy to install via Conda:
conda -c conda-forge warpx
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
Set Up a Simulation from Scratch
The WarpX examples and the documentation gallery are the best starting points for a new simulation.
Setting up a simulation is an iterative process: run, visualize, understand what’s wrong, fix it, repeat.
When the simulation doesn’t show the expected physics, check the basics first: enough timesteps? resolved scales? adequate particles per cell? temperature not too high?
The documentation parameter reference is your constant companion for understanding and modifying input files.
A Two-stream Instability
💡 The two-stream instability converts the kinetic energy of counter-streaming beams into electrostatic wave energy.
🔬 The instability growth rate depends on the ratio of drift velocity to thermal velocity: \(v_d / v_{\mathrm{th}} \gg 1\) is needed for the instability to develop.
📊 Reduced diagnostics (FieldEnergy,
FieldMaximum) let you track the instability growth in real
time without post-processing full datasets.
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you can use the openPMD-viewer library for Python.
A Weibel Instability
💡 The Weibel instability generates magnetic fields from a momentum anisotropy – unlike the two-stream instability, which generates electrostatic fields.
🔬 The instability produces current filaments with a characteristic size of order the plasma skin depth \(c/\omega_{pe}\).
📊 Reduced diagnostics (FieldEnergy,
FieldMaximum) are an efficient way to monitor the
instability growth without storing large field dumps.
⚡ Choosing parameters wisely (\(v_d \gg v_{\mathrm{th}}\), sufficient resolution and box size) is essential for observing the instability clearly.
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you can use the openPMD-viewer library for Python.
A Magnetic Mirror
💡 The external B field is loaded from an openPMD file, while the protons are defined as test particles.
📷 To analyze and visualize the simulation results in openPMD format, you
can use the openPMD-viewer
library for Python or you can open .pmd files directly in
Paraview.
A FODO Cell
🎯 Particle tracking follows individual particles, while envelope tracking follows the beam envelope - particle tracking is more detailed but computationally expensive.
🔬 A FODO cell is a periodic focusing structure with alternating focusing and defocusing quadrupole magnets.
⚡ WarpX allows you to turn space charge effects on/off and define arbitrary external fields.
🚀 WarpX is a full PIC code best suited for strong space charge effects and complex electromagnetic interactions. For cases with negligible space charge, ImpactX may be a more efficient choice.
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you can use the openPMD-viewer library for Python.
A Laser-Driven Ion Accelerator
💡 TNSA accelerates ions via a strong electrostatic sheath field created by hot electrons escaping the rear surface of a laser-irradiated thin target.
🔬 Key parameters controlling the maximum ion energy are the laser intensity (\(a_0\)), the target thickness, and the target density.
⚙️ Charge-conserving current deposition (esirkepov) and
proper boundary conditions (PML, absorbing) are essential for this type
of simulation.
⚡ This is a computationally expensive simulation – be prepared to iterate on resolution and target density to find a balance between physical fidelity and computational cost.
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you can use the openPMD-viewer library for Python.
A Beam-Beam Collision
💅 There are several details one needs to take care when setting up a beam-beam simulation
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you can use the openPMD-viewer library for Python.
OSSFE 2025 - Using WarpX, a general purpose particle-in-cell code
🚀 WarpX is a open-source high-performance particle-in-cell code
🎯 WarpX is easy to install via Conda:
conda -c conda-forge warpx
🔍 The documentation is the first place to look for answers, otherwise check out our issues and discussions and ask there.
📷 To analyze and visualize the simulation results in openPMD format, you
can use the openPMD-viewer
library for Python or you can open .pmd files directly in
Paraview.
UCB 2026 -- Two-Stream Instability Live Tutorial
Setting up a simulation is an iterative process: start from an existing example, modify, run, visualize, and refine.
The WarpX documentation and the examples gallery are the best starting points.
When things don’t look right, check the basics: enough timesteps, adequate resolution, and appropriate temperature.