LISA Data Challenge software

LDC provides a set of tools to generate and analyse the LDC datasets.

Installation of the latest released version

pip install lisa-data-challenge

Installation of the dev version

Cloning the gitlab project

The default working branch is named develop. git clone -b develop https://gitlab.in2p3.fr/LISA/LDC.git

Installation

By default, pyproject.toml will be used to generate a temporary environement to build the package (see https://pip.pypa.io/en/stable/reference/build-system/pyproject-toml/)

pip install .

For older version of setuptools, a setup.py file is also provided.

python setup.py install

Troubleshooting

Prerequisites

• GSL : apt-get install libgsl-dev or conda install gsl
• FFTW3 : apt-get install libfftw3-dev or conda install fftw

Paths to FFTW and GSL can be set explicitly by editing setup.cfg.

Python dependencies

Make sure that all requirements are met.

The requirements.txt file defines the reference version for most of the dependencies for a python3.9 installation as recommended by LISA-CDE, but other versions of the listed package might work.

To comply with the CDE environement: pip install -r requirements.txt

Extensions for specific fast waveform generator can be disabled in the installation command line:

python setup.py install --no-fastGB --no-imrphenomD --no-fastAK

Extra dependencies

Some external tools are interfaced by the LDC and need separate installation:

• EMRI waveform with few: see https://bhptoolkit.org/FastEMRIWaveforms/html/index.html
• Fast BH waveform with lisabeta: see https://gitlab.in2p3.fr/marsat/lisabeta

Documentation

• LISA Data Challenge portal
• API documentation

Use policy

Do not forget to associate the authors of this software to your research:

• Please cite the DOI (see badge above) and acknowledge the LDC working group in any publication which makes use of it

• Do not hesitate to send an email for help and/or collaboration: ldc-at-lisamission.org, ldc-chairs-at-lisamission.org

  Project status

  This toolbox has been developed to support the simulation production and analysis of the LISA Data Challenges, over the 2020-2024 period. These are the LDC codenamed:

• Sangria LDC2a: mild enchilada (GB, MBHB), simple noise

• Spritz LDC2b: single source type (GB, MBHB), instrumental artifacts (glitches, gaps)

• Yorsh LDC1b: single source type: SOBH, EMRI

Following on the LISA adoption by space agencies in 2024, multiple projects to support this activity have been put in place, to address the forthcoming increase in complexity of the future LDC. Thus this toolbox is under a decommissioning phase.

The following table gives pointers to those new projects, for the different parts covered by this toolbox.