Citations

GCfit was first introduced in Dickson et al. (2023) and updated in Dickson et al. (2024).

If you find this package useful in your research, please consider citing the above, and any relevant papers below:

Observational Data

Each observational dataset should come with it’s own source metadata, typically in the form of a bibcode identifier.

While these can be accessed directly through the metadata attribute of each Dataset:

>>> dset = obs['number_density']
>>> dset.mdata['source']
'2019MNRAS.485.4906D'

GCfit also comes equipped with some utility functions to automatically convert bibcodes to useful formats, like bibtex. This functionality requires the ads package to be installed correctly, with a valid ADS_DEV_KEY set.

The Observations and Dataset objects can provide some of the available formats directly:

>>> sources = obs.get_sources()
>>> print(sources['number_density'][0])
@ARTICLE{2019MNRAS.485.4906D,
       author = {{de Boer}, T.~J.~L. and {Gieles}, M. and {Balbinot}, E. and {H{\'e}nault-Brunet}, V. and {Sollima}, A. and {Watkins}, L.~L. and {Claydon}, I.},
        title = "{Globular cluster number density profiles using Gaia DR2}",
...
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
>>> print(dset.cite())
de Boer et al. (2019)

Or the utility methods can be used directly:

>>> print(gcfit.util.bibcode2bibtex(dset.mdata['source'])[0])
@ARTICLE{2019MNRAS.485.4906D,
       author = {{de Boer}, T.~J.~L. and {Gieles}, M. and {Balbinot}, E. and {H{\'e}nault-Brunet}, V. and {Sollima}, A. and {Watkins}, L.~L. and {Claydon}, I.},
        title = "{Globular cluster number density profiles using Gaia DR2}",
...
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
>>> print(gcfit.util.bibcode2cite(dset.mdata['source']))
de Boer et al. (2019)

Models

The equilibrium models used should be cited from the limepy paper: 2015MNRAS.454..576G.

The mass evolution algorithm (ssptools) is based off of the algorithm first introduced in 2018MNRAS.474.2479B (and updated in Dickson et al., 2023).

Samplers

If you are using the MCMC fitter (MCMC_fit), the sampler source software should be cited as the emcee paper: 2013PASP..125..306F. Specific proposal algorithm citations can be found within.

Nested sampling fits (nested_fit) should cite the dynesty paper: 2020MNRAS.493.3132S. For specific bound and sampler algorithm sources, see the dynesty documentation.

Other

Fitting on pulsar timing data was introduced in Smith et al. (2024).

If Bayesian hyperparameters are used (hyperparams=True in any fitting), the source paper 2002MNRAS.335..377H can be cited.

GCfit makes extensive use of the numpy, scipy, astropy, h5py and shapely libraries. All plotting functionality is enabled by the matplotlib library. Parallelization pools are handled by the schwimmbad library.