Welcome to k-Wave-python’s documentation!¶

k-Wave is an open source acoustics toolbox for MATLAB and C++ developed by Bradley Treeby and Ben Cox (University College London) and Jiri Jaros (Brno University of Technology). The software is designed for time domain acoustic and ultrasound simulations in complex and tissue-realistic media. The simulation functions are based on the k-space pseudospectral method and are both fast and easy to use.

A Python implementation of k-Wave — an acoustics toolbox for time-domain simulation of acoustic wave fields. Includes a pure NumPy/CuPy solver (backend="python", supports any CUDA-capable GPU) and an interface to the pre-compiled k-Wave C++ binaries (backend="cpp") with NVIDIA GPU support for compute capability 7.5 (Turing) and newer — covers every consumer/datacenter GPU since 2018, including all shipping Blackwell variants (B200/GB200, B300/GB300, Jetson Thor, RTX 50xx, RTX PRO 6000 Blackwell, GB10/DGX Spark).

Mission¶

Increase the accessibility and reproducibility of k-Wave simulations for medical imaging, algorithmic prototyping, and testing.

Getting started¶

A collection of examples covers common simulation scenarios. Run any example locally:

uv run examples/ivp_homogeneous_medium.py

No GPU required — all examples run on CPU with NumPy.

Installation¶

Using uv (recommended):

uv add k-wave-python

Or with pip:

pip install k-wave-python

Older GPUs (Maxwell, Pascal, Volta)¶

The backend="cpp" binaries shipped in v0.6.3+ require compute capability 7.5 (Turing) or newer. CUDA Toolkit 13.0 removed offline-compilation support for older architectures, so the following hardware is not covered by the bundled binaries:

Maxwell (GTX 9xx, Titan X Maxwell, Tesla M-series, Jetson Nano)
Pascal (GTX 10xx, P100, P40, Titan X(p)/Xp, Jetson TX2)
Volta (V100, Titan V, Quadro GV100, Jetson AGX Xavier)

Use backend="python" instead (NumPy/CuPy works on every CUDA-capable GPU), or build the C++ backend from source against CUDA Toolkit 12.x.

Development¶

Development instructions can be found here.

Documentation¶

The documentation for k-wave-python can be found here.

Citation¶

@software{k-Wave-Python,
author = {Yagubbayli, Farid and Sinden, David and Simson, Walter},
license = {GPL-3.0},
title = {{k-Wave-Python}},
url = {https://github.com/waltsims/k-wave-python}
}