Citation

TauREx will output a bibliography at program finish for components used in a run (including plugins) or store a .bib file when run with --bibtex filename.bib. We also list references for components in the base TauREx3 installation.

Taurex 3

If you use TauREx 3 in your research and publications, please cite here:

@ARTICLE{2021ApJ...917...37A,
    author = {{Al-Refaie}, A.~F. and {Changeat}, Q. and {Waldmann}, I.~P. and {Tinetti}, G.},
        title = "{TauREx 3: A Fast, Dynamic, and Extendable Framework for Retrievals}",
    journal = {\apj},
    keywords = {Open source software, Astronomy software, Exoplanet atmospheres, Radiative transfer, Bayesian statistics, Planetary atmospheres, Planetary science, 1866, 1855, 487, 1335, 1900, 1244, 1255, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics},
        year = 2021,
        month = aug,
    volume = {917},
    number = {1},
        eid = {37},
        pages = {37},
        doi = {10.3847/1538-4357/ac0252},
archivePrefix = {arXiv},
    eprint = {1912.07759},
primaryClass = {astro-ph.IM},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2021ApJ...917...37A},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@ARTICLE{2022ApJ...932..123A,
    author = {{Al-Refaie}, A.~F. and {Changeat}, Q. and {Venot}, O. and {Waldmann}, I.~P. and {Tinetti}, G.},
        title = "{A Comparison of Chemical Models of Exoplanet Atmospheres Enabled by TauREx 3.1}",
    journal = {\apj},
    keywords = {Open source software, Publicly available software, Chemical abundances, Bayesian statistics, Exoplanet atmospheres, Exoplanet astronomy, Exoplanet atmospheric composition, Exoplanets, Radiative transfer, 1866, 1864, 224, 1900, 487, 486, 2021, 498, 1335, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
        year = 2022,
        month = jun,
    volume = {932},
    number = {2},
        eid = {123},
        pages = {123},
        doi = {10.3847/1538-4357/ac6dcd},
archivePrefix = {arXiv},
    eprint = {2110.01271},
primaryClass = {astro-ph.EP},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2022ApJ...932..123A},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Precomputed Mie cloud grids

If you use the built-in PyMieScattGridExtinction contribution, please also cite:

@ARTICLE{2026A&A...707A.127V,
    author = {{Voyer}, M. and {Changeat}, Q.},
        title = "{Precomputed aerosol extinction, scattering, and asymmetry grids for scalable atmospheric retrievals}",
    journal = {Astronomy and Astrophysics},
    year = 2026,
    month = mar,
    volume = {707},
        eid = {A127},
    pages = {A127},
        doi = {10.1051/0004-6361/202558469},
archivePrefix = {arXiv},
    eprint = {2601.14177},
primaryClass = {astro-ph.EP},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2026A&A...707A.127V},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Instrument and multimodel functionality

If you use TauREx instrument models or the multimodel functionality, please also cite:

@ARTICLE{2025A&A...699A.219C,
    author = {{Changeat}, Q. and {Bardet}, D. and {Chubb}, K. and {Dyrek}, A.
        and {Edwards}, B. and {Ohno}, K. and {Venot}, O.},
    title = "{Cloud and haze parameterization in atmospheric retrievals: Insights from Titan's Cassini data and JWST observations of hot Jupiters}",
    journal = {\aap},
    keywords = {techniques: spectroscopic, planets and satellites: atmospheres,
        infrared: planetary systems, Earth and Planetary Astrophysics,
        Instrumentation and Methods for Astrophysics},
    year = 2025,
    month = jul,
    volume = {699},
    eid = {A219},
    pages = {A219},
    doi = {10.1051/0004-6361/202453186},
archivePrefix = {arXiv},
    eprint = {2505.18715},
primaryClass = {astro-ph.EP},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2025A&A...699A.219C},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Retrieval

If you make use of any of these samplers then please cite the relevant papers

PyMultiNest and MultiNest

(PyMultiNest)
X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue
J. Buchner, A. Georgakakis, K. Nandra, L. Hsu, C. Rangel, M. Brightman, A. Merloni, M. Salvato, J. Donley and D. Kocevski
A&A, 564 (2014) A125
doi: 10.1051/0004-6361/201322971

MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics
F. Feroz, M.P. Hobson, M. Bridges
Mon. Not. Roy. Astron. Soc. 398: 1601-1614,2009
doi: 10.1111/j.1365-2966.2009.14548.x

PolyChord

polychord: next-generation nested sampling
W. J. Handley, M. P. Hobson, A. N. Lasenby
Mon. Not. Roy. Astron. Soc. 453: 4384–4398,2015
doi: 10.1093/mnras/stv1911

dyPolyChord

Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation
E. Higson, W. Handley, M. Hobson, A. Lasenby
Statistics and Computing volume 29, 891–913, 2019
doi: 10.1007/s11222-018-9844-0