thunder4D

Transverse-resolved Herriott-cell UPPE solver for Nonlinear Dynamics close to Experimental Reality, 4D: a 4D (x, y, z, t) UPPE solver for multipass cells, with a design helper that goes from a laser to a ready-to-run cell, and a graphical interface.

Documentation: https://victorkolt.github.io/thunder4D

Install

pip install thunder4d               # or: uv add thunder4d
pip install "thunder4d[gpu]"        # NVIDIA GPU (CuPy)
pip install "thunder4d[gui]"        # graphical interface: thunder4d-gui
pip install "thunder4d[numba]"      # faster CPU runs (Numba kernels)
pip install "thunder4d[fftw]"       # FFTW transforms on the CPU (fft_backend="fftw")

Example

1 mJ, 200 fs at 1030 nm through 26 passes of a cell filled with 0.7 bar of argon, then the best uniform compression.

import thunder4d as th
from thunder4d import diagnostics as dg

cfg = th.default_input(
    laser={"energy_J": 1e-3, "duration_fs": 200},
    medium={"gas": "Ar", "pressure_bar": 0.7},
    cell={"roc_m": 0.6, "separation_m": 1.183, "n_passes": 26},
    grid={"lambda_min_nm": 900, "lambda_max_nm": 1180},
)
b = th.run_input(cfg)                              # coarse grid: a few seconds on a laptop
print(dg.compress(b.grid, b.sim.Aw)["fwhm_fs"])    # 23.6 fs

Validation

Against published experiments, on the benchmark grids. Values are simulation (paper).

Details in the benchmark report.

License

MIT