What is XSNAP?#

Introduction#

XSNAP (X-ray Supernova Analysis Pipeline) is a Python-based pipeline module that automates every step of X-ray supernova data reduction and analysis, from raw event processing and region selection to spectral fitting. XSNAP provides dedicated standard data calibration and spectral extraction scripts for Chandra X-ray Observatory (CXO), Swift-XRT, XMM-Newton, and NuSTAR data.

XSNAP, with the help of PyXspec, is able to model and fit spectra using a wide range of astrophysical models (e.g., Thermal-Bremsstrahlung and Powerlaw). Additionally, XSNAP can generate photometric data through the fitted spectra.

A follow-up analysis using the Thermal-Bremsstrahlung model can be made, specifically for Type II Supernova. From luminosity fitting to estimating Circumstellar Medium (CSM) densities and mass-loss rates of the supernova progenitors, XSNAP streamines the workflow so you can spend less time on rewriting each analysis manually.

More analysis functions can be made upon requests (view Development for more details)

Components#

XSNAP is organized into two main parts:

command-line scripts (where users can invoke on the shell or jupyter notebook), and
built-in module or Python API (where you can import functions and classes).

There are six scripts available for users to run:

Script	Description
`extract-chandra`	Calibrate & extract spectrum from Chandra observations.
`extract-swift`	Calibrate & extract spectrum from Swift-XRT (PC/WT mode available).
`swift-stack-pc`	Bin & stack Swift-XRT PC-mode data (default 1-day bins).
`extract-xmm`	Calibrate & extract spectrum from XMM-Newton.
`extract-nustar`	Calibrate & extract spectrum from NuSTAR.
`make-region`	Generate ICRS source/background region files. (Physical region files will also be made if you have DS9)

And there are five Python classes to call:

Class	Description
`SpectrumFit`	Model a spectrum and estimate best-fit parameters.
`SpectrumManager`	Handling and compiling a collection of `SpectrumFit`, streamlining bulk analysis of spectra.
`SourceDetection`	Detect a source with certain SNR (default SNR > 3), given the source’s RA and Dec.
`CSMAnalysis`	Analyze the circumstellar medium of the supernova.
`TemperatureEstimator`	Estimate temperature at a certain time with power-law, given a set of data or best-fit parameters