Magnetar+Bump Modeling of Superluminous Supernovae

<p>These data files are associated with the article <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210909743H">&quot;Bumpy Declining Light Curves are Common in Hydrogen-poor Superluminous Supernovae.&quot;</a> This repository contains four directories, described below.</p> <p><strong>MOSFiT Output Files</strong></p> <p>The &quot;mosfit&quot; directory contains the raw output files from the Modular Open-Source Fitter for Transients (Guillochon et al. <a href="https://doi.org/10.3847/1538-4365/aab761">2017</a>). See its <a href="https://mosfit.readthedocs.io">documentation</a> for the output format. Keep in mind that some detections have been converted into nondetections in these files (see the paper for a full explanation), so you should not use them as a source for the photometry.</p> <p><strong>Magnetar Models</strong></p> <p>The &quot;models&quot; directory contains the range of models for each supernova. These are stored as <a href="https://docs.astropy.org/en/latest/io/ascii/ecsv.html">ECSV</a> files, which can be read using Astropy tables. The columns are MJD, filter, apparent magnitude (median, minimum, maximum), and absolute magnitude (median, minimum, maximum). The metadata contains the median and standard deviation of each parameter discussed in the paper, as well as the supernova name, distance modulus, and extinction.</p> <p><strong>Magnetar Parameters</strong></p> <p>The &quot;params&quot; directory contains the magnetar model parameters corresponding to each model realization, also stored as <a href="https://docs.astropy.org/en/latest/io/ascii/ecsv.html">ECSV</a> files. In other words, you can use these files to reproduce the posterior for each parameter. The metadata contains the units for each parameter and a LaTeX representation of each variable name.</p> <p><strong>Bump Models</strong></p> <p>The &quot;bumps&quot; directory contains the raw output for the bump modeling. These are stored as compressed Numpy files (.npz) and can be read using np.load. The keywords are as follows:</p> <ul> <li>&quot;chain&quot;: the flattened MCMC chain, stored as a 2D array. The 0th dimension corresponds to the number of walkers times the number of steps. The 1st dimension corresponds to the parameters: amplitude, center (MJD), and FWHM (observed days). In the case of 2 bumps, the parameters are amplitude 1, center 1, FWHM 1, amplitude 2, center 2, FWHM 2.</li> <li>&quot;pmed&quot;: the median of each parameter, followed by the median absolute deviation for each parameter (converted to a standard deviation).</li> <li>&quot;energies&quot;: the integrated energy in each model realization (in watt-days).</li> <li>&quot;energy&quot;: the median of the &ldquo;energies&rdquo; array.</li> <li>&quot;denergy&quot;: the median absolute deviation of the &ldquo;energies&rdquo; array (converted to a standard deviation).</li> <li>&quot;integral&quot;: the integral of the magnetar residuals before modeling (in watt-days). This is not used in the paper.</li> <li>&quot;t0&quot; and &quot;t1&quot;: the range of MJDs used in the bump fitting.</li> </ul> <p>If you have any questions about this dataset, feel free to contact the author, <a href="mailto:griffin0@arizona.edu">Griffin Hosseinzadeh</a>.</p>