SESNspectraPCA

This repository contains the code for running the PCA + SVM spectral analysis on Stripped-Envelope Core-Collapse Supernovae found in Williamson & Modjaz & Bianco (2019). There are also data products associated with the new SNID templates that were added to the SESNe spectral library compiled from Liu et al. 2016 and Modjaz et al. 2016. The repository is organized into the following folders:

• /Data contains the pickled spectral datasets used in Williamson & Modjaz & Bianco (2019) at phases 0, 5, 10, 15 days relative to V-band maximum. The spectra have been preprocessed. These pickled files are used in the Tutorial notebook.
• /SNePCAplots contains final figures showing PCA reconstruction of SN2011ei, cumulative variance captured by principal components, time evolution of the eigenspectra, comparison of mean spectra vs eigenspectra, and SVM classification of SESNe.
• /code contains the SNePCA.py which implements the PCA and SVM analysis used in Williamson & Modjaz & Bianco (2019). It also contains SNIDsn.py and SNIDdataset.py which are used to load the SNID template files (*.lnw files) and compile them into a dataset for easy use. There is a tutorial jupyter notebook, Tutorial.ipynb which generates plots from Williamson & Modjaz & Bianco (2019) and demonstrates how the code is run.

Compiling the SESNe SNID Dataset

In order to rerun the entirety of our analysis, including preprocessing, it is necessary to compile the dataset of SuperNova IDentification (SNID; Blondin & Tonry 2007) Templates used in Williamson & Modjaz & Bianco (2019). Follow these steps:

1. Download the default SNID library -- The default library of SESNe spectra for SNID can be found on Stephan Blondin's website
2. Add SNID Templates from nyusngroup -- The research group at New York University (NYU) lead by Professor Maryam Modjaz has published multiple papers presenting new SNID templates of SESNe in the literature, along with making adjustments to the SNID templates in the default SNID library. SESNtemple contains the new and adjusted SNID templates from Liu & Modjaz 2014, Liu et al. 2016 and in Modjaz et al. (2016), that are based on both CfA Data (initially released in Liu & Modjaz 2014) and the rest of literature data (included in Liu et al. 2016 for IIb and Ib, Modjaz et al. 2016 for Ic and Ic-bl). There are also SNID templates for the superluminous SNe presented in Liu, Modjaz & Bianco (2017), based on literature data. Finally, the new SNID templates for SESNe in the literature through August 2018 presented in Williamson & Modjaz & Bianco (2019) are included.
3. Set up SNID Template Directory -- Gather all of the SNID templates from the above two steps in a directory, and consider defining an environmental variable to be the path to your directory.

Acknowledgement:

If you use data products or the analysis in this code, please acknowledge this work by citing in your paper: Williamson & Modjaz & Bianco (2019).

Williamson & Modjaz & Bianco (2019):

@article{1903.06815,
Author = {Marc Williamson and Maryam Modjaz and Federica Bianco},
Title = {Optimal Classification and Outlier Detection for Stripped-Envelope Core-Collapse Supernovae},
Year = {2019},
Eprint = {arXiv:1903.06815},
}