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Flows Simulations

This repository contains the analysis to test the homogeneity of Type Ia Supernovae (SNe Ia) in the Near-infrared (NIR) for accurate distance estimations

SNe Ia sample and light-curve fitter

In this work, we use the Carnegie Supernova Project (CSP I+II) sample of SNe Ia with uBgVriYJH-band light curves. To fit these objects we use SNooPy (Burns et al. 2011)

Running the notebooks

To run the notebooks it is recommended to create an environment first (e.g., using Anaconda) and activate it:

conda create -n flows_sims pip
conda activate flows_sims

and then install the rest of the requirements (except for SNooPy -- see below):

pip install -r requirements.txt

To install the latest version of SNooPy (v2.6 at the momment), follow these commands:

git clone https://github.com/obscode/snpy
cd snpy
git checkout gen3
python setup.py install

Citation

If you make use of these scripts or the analysis, please cite the following paper: https://ui.adsabs.harvard.edu/abs/2022arXiv220704780M/abstract

@ARTICLE{2022arXiv220704780M,
       author = {{M{\"u}ller-Bravo}, T.~E. and {Galbany}, L. and {Karamehmetoglu}, E. and {Stritzinger}, M. and {Burns}, C. and {Phan}, K. and {I{\'a}{\~n}ez Ferres}, A. and {Anderson}, J.~P. and {Ashall}, C. and {Baron}, E. and {Hoeflich}, P. and {Hsiao}, E.~Y. and {de Jaeger}, T. and {Kumar}, S. and {Lu}, J. and {Phillips}, M.~M. and {Shahbandeh}, M. and {Suntzeff}, N. and {Uddin}, S.~A.},
        title = "{Testing the Homogeneity of Type Ia Supernovae in the Near-Infrared for Accurate Distance Estimations}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics},
         year = 2022,
        month = jul,
          eid = {arXiv:2207.04780},
        pages = {arXiv:2207.04780},
archivePrefix = {arXiv},
       eprint = {2207.04780},
 primaryClass = {astro-ph.CO},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220704780M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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