extrabol 1.2.1

Estimate SN bolometric light curves

extrabol

extrabol is a Python 3.x package for rapidly and systematicaly estimating the bolometric luminosity and black body properties of (thermal) extragalactic transients from broadband UVONIR data. extrabol is broken down into three main steps:

• Read in and pre-process a data file holding observations of a supernova or other transient event over time, through any number of broadband filters.
• Interpolate this data using a Gaussian Process(GP), a non-physical, statistical model utilizing covariance.
• Fit a series of blackbody curves to the interpolated data to estimate the bolometric luminosity, temperature, and radius of the transient over time.

Author: Ian Thornton

Installation and Documentation

Install with pip:

pip install extrabol

The latest documentation is available here.

Usage

extrabol 'filename.dat' ARGUMENTS

Optional Arguments:

--verbose
    Increase output verbosity

-m MEAN, --mean MEAN
    Use a supernova template as the mean function for the GP; Choose \'1a\',\'1bc\', \'2l\', \'2p\', or \'0\' (for no template)
    Default = 0

-t, --show-template
    Shows supernova template on plots as dotted lines

-d DIST, --dist DIST
    Object luminosity distance in Mpc

-z REDSHIFT, --redshift REDSHIFT
    Object redshift
    If no argument is provided, redshift will be read from the input file

--dm DM
    Object distance modulus

--plot BOOL
    Output plots, Default is TRUE

--outdir OUTDIR
    A file location for outputs to be written to

--ebv EBV
    Milky Way extinction E(B-V) value, if known
    If no argument is probided the extinction will be read from the input file

--hostebv HOSTEBV
    Host extinction E(B-V)

-s START, --start START
    Start time of analysis window relative to peak luminosity
    Default = -50 days

-e END, --end END
    End time of analysis window relative to peak luminosity
    Default = 150 days

-snr SNR
    Minimum signal to noise ratio for observations
    Default = 4.0

-mc, --use-mcmc
    Use a Markov Chain Monte Carlo to fit black bodies instead of curve_fit.
    This provides better error estimates but takes much longer.

--T_max T_MAX
    Modify the prior on temperature for blackbody fits by specifying a maximum temperature.
    Default = 40,000K

-k, --kernel-width
    The width (:math:`r^2`) of the GP kernel in the (time, wavelength) direction.
    If not given, the kernel width will be optimized.

Input Files

SNANA format: The metadata section contains key-value pairs, each on a new line, followed by the observational data section. The observational data is defined by the VARLIST line and is preceded by a metadata section.

The observational data lines must start with 'OBS:' followed by values corresponding to the variables listed in the VARLIST line.

extrabol format: The first two lines must contain redshift and Milky Way extinction E(B-V) respectively. If these values are unknown, simply put 0.0. The following lines contain observational data in 5 columns as shown below:

Time(MJD)   Apparent Magnitude   Error(in magnitudes)   Filter SVO ID   Type of magnitude (AB or Vega)

Any white space can be used as the column delimiter. NaNs, non-detections, and data points with no error bars should not be included. An example input file can be found under extrabol/example.

Example Input

extrabol ./example/SN2010bc.snana.dat --verbose -m 1a

This example may take a minute the first time you run it as astroquery fetches filter information!

Filters must be specified by their SVO ID.