Quickstart

Quickstart#

Get up and running with soliton_solver in minutes.

Running a built-in example#

The fastest way to see soliton_solver in action is to run one of the built-in examples:

python -m soliton_solver.examples.chiral_magnet_gl

This launches an interactive visualization of magnetic skyrmions in a chiral ferromagnet, simulated entirely on the GPU with real-time rendering.

Other available examples:

  • abelian_higgs_gl — Abelian Higgs vortices

  • anisotropic_gl — Anisotropic superconductor

  • anyon_gl — Anyons in Chern-Simons theory

  • baby_skyrme_gl — Baby Skyrme model

  • bose_einstein_condensate_gl — Rotating BEC

  • chiral_magnet_gl — Chiral ferromagnet skyrmions

  • liquid_crystal_gl — Chiral liquid crystal

  • spin_triplet_gl — Spin-triplet superconductor

  • super_ferro_gl — Ferromagnetic superconductor

Basic workflow#

Here is a typical workflow:

1. Load a theory#

from soliton_solver.theories import load_theory

theory = load_theory("Chiral magnet")

2. Create simulation parameters#

params = theory.params.default_params(
    xlen=320, ylen=320,           # Grid points
    xsize=10.0, ysize=10.0,       # Physical domain size
    # Theory-specific parameters follow
    J=40e-12,                     # Exchange coupling
    K=0.8e+6,                     # Anisotropy
    D=4e-3,                       # Dzyaloshinskii-Moriya interaction
    M=580e+3,                     # Saturation magnetization
    B=0e-3,                       # Magnetic field
)

3. Initialize simulation#

from soliton_solver.core.simulation import Simulation

sim = Simulation(params, theory)
sim.initialize({"mode": "ground"})

The initialize method sets up initial field conditions. The "ground" mode initializes fields in a topological configuration suitable for soliton relaxation.

4. Run with visualization#

theory.render_gl.run_viewer(sim, sim.rp, steps_per_frame=5)

This launches an interactive OpenGL window showing the field configuration. Simulations execute entirely on the GPU; field data streams directly from CUDA memory into OpenGL buffers using zero-copy CUDA–OpenGL interop.

Complete example: Chiral magnet skyrmions#

Here is a complete runnable script:

from soliton_solver.theories import load_theory
from soliton_solver.core.simulation import Simulation

theory = load_theory("Chiral magnet")

def run_gl_simulation():
    params = theory.params.default_params(
        xlen=320, ylen=320, 
        xsize=10.0, ysize=10.0,
        J=40e-12, 
        K=0.8e+6, 
        D=4e-3, 
        M=580e+3, 
        B=0e-3,
        mu0=1.25663706127e-6,
        dmi_term="Heusler", 
        ansatz="anti",
        demag=True,
        newtonflow=False,
        unit_magnetization=True
    )
    sim = Simulation(params, theory)
    sim.initialize({"mode": "ground"})
    theory.render_gl.run_viewer(sim, sim.rp, steps_per_frame=5)

if __name__ == "__main__":
    run_gl_simulation()

Run this script:

python my_simulation.py

Visualizing results#

After running a simulation, you can plot results:

python -m soliton_solver.theories.chiral_magnet.results.plotting

This generates plots of field densities, energy, and other observables.

Next steps#

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