madspace 0.1.1

Fast and flexible phase space mappings

Modular and GPU-ready phase-space library

Installation

Package

Packages on PyPI are available for Linux and MacOS X (with Apple silicon), for Python 3.11 to 3.14.

pip install madspace

Build

First install scikit_build_core with

pip install scikit_build_core

The pre-installed version of cmake under MacOS is outdated, so you might need to install a newer version, for example with

brew install cmake

Then check out the madspace repository and build and install it with

git clone [e-mail]:madgraph-ml/madspace.git
cd madspace
pip install .

For a development version allowing for incremental build, use the following command instead:

pip install --no-build-isolation -Cbuild-dir=build -Ccmake.build-type=RelWithDebInfo .

This will create a directory build where you can run make directly to make development easier. To update the python module itself, make sure to also run the pip install command above again. This will not happen automatically, even if you make the installation editable! Build type RelWithDebInfo generates optimized code but includes debug symbols, so you can use lldb or gdb to debug the code.

Tests

To run the tests, you need to have the pytest, numpy and torch packages installed. One test optionally requires the lhapdf package (can be installed via conda or built from source) and the NNPDF40_nlo_as_01180 PDF set.

To run the tests, go to the root directory of the repository and run

pytest tests

Citation

If you use this MadSpace or parts of it, please cite:

@article{Heimel:2026hgp,
author = "Heimel, Theo and Mattelaer, Olivier and Winterhalder, Ramon",
title = "{MadSpace -- Event Generation for the Era of GPUs and ML}",
eprint = "2602.06895",
archivePrefix = "arXiv",
primaryClass = "hep-ph",
reportNumber = "MCNET-26-01, IRMP-CP3-26-04, TIF-UNIMI-2026-1",
month = "2",
year = "2026"}