The Algorithm for the Refinement of DEtection limits via N-body stability Threshold (ARDENT) is a python package for the computation of exoplanet detection limits from radial velocity data. In addition to the classic data-driven detection limits, ARDENT includes the orbital stability constraint (what we call dynamical detection limits). The final output is a more constraining detection limits curve, taking into account both the detectability of potential planets and their dynamical plausibility.
The code can be used as two separate modules, for the data-driven detection limits and the dynamical detection limits. ARDENT can be used to refine the detection limits, test the dynamical plausibility of a planet candidate, and check if there is dynamical room for additional planets in a certain period range.
ARDENT is built on a series of python packages, contained in the requirements.txt file.
- numpy
- matplotlib
- pandas
- rebound
- reboundx
- joblib
- tqdm
- PyAstronomy
To use ARDENT, you can clone the repository to your computer: git clone https://github.com/manustalport/ardent.git.
Once on your computer, add ARDENT to your $PYTHONPATH. To proceed, in a terminal, cd into the ardent parent folder and then:
echo "export PYTHONPATH=$PWD/ardent:\$PYTHONPATH" >> ~/.bash_profilesource ~/.bash_profile
It is recommended using a virtual environment to run ARDENT, as some dependencies run on specific versions. This will avoid conflicts with your own system.
In a terminal, run python -m venv ardent_venv to create a virtual environment named ardent_venv.
You need to activate this environment with source ardent_venv/bin/activate.
Finally, install all the dependencies at once in your new virtual environment: pip install -r requirements.txt
The code was tested with Python 3.11, rebound 4.4.3 and reboundx 4.3.0.
ARDENT is installable on Linux and MacOS distributions.
Follow the steps of the ardent/hands-on_tutorial.ipynb file, that will guide you through the various ARDENT functions.
- Manu Stalport, University of Liège (contact point)
- Michaël Cretignier, University of Oxford
If you use ARDENT for your research, please cite:
- Stalport M., Cretignier M., Naponiello L., and Van Grootel V. 2025, A&A, arXiv:2509.13521
ARDENT: A Python package for fast dynamical detection limits with radial velocities