The latest release of diffmah is available for installation with pip or conda-forge:
$ conda install -c conda-forge diffmah
To install diffmah into your environment from the source code:
$ cd /path/to/root/diffmah
$ pip install .
For a typical development environment in conda:
$ conda create -c conda-forge -n diffit python=3.9 numpy jax pytest ipython jupyter matplotlib scipy h5py diffmah
Data for this project can be found at this URL.
Online documentation for Diffmah is available at diffmah.readthedocs.io.
The diffmah_fitter_demo.ipynb notebook demonstrates how to fit the MAH of a simulated halo with a diffmah approximation. See history_fitting_script.py for an example of how to fit the MAHs of a large number of simulated halos in parallel with mpi4py.
The diffmah paper has been published by the Open Journal of Astrophysics. Citation information for the paper can be found at this ADS link, copied below for convenience:
@ARTICLE{2021OJAp....4E...7H,
author = {{Hearin}, Andrew P. and {Chaves-Montero}, Jon{\'a}s and {Becker}, Mathew R. and {Alarcon}, Alex},
title = "{A Differentiable Model of the Assembly of Individual and Populations of Dark Matter Halos}",
journal = {The Open Journal of Astrophysics},
keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies},
year = 2021,
month = jul,
volume = {4},
number = {1},
eid = {7},
pages = {7},
doi = {10.21105/astro.2105.05859},
archivePrefix = {arXiv},
eprint = {2105.05859},
primaryClass = {astro-ph.CO},
adsurl = {https://ui.adsabs.harvard.edu/abs/2021OJAp....4E...7H},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}