GaussFit: A Tool for Multi-Gaussian Decomposition

Abstract GaussFit is a tool for fitting multiple Gaussians to one-dimensional (1D) data, capable of handling complex shapes consisting of many overlapping Gaussian components. GaussFit provides a readily available, easy-to-use way that automates the process of multi-Gaussian decomposition. Data is initially smoothed and continuum normalized to ease the fitting routine. Multi-Gaussian decomposition is done by iteratively fitting Gaussian components and determining the best-fit through Akaike Information Criterion (AIC)/Bayesian Information Criterion (BIC). GaussFit is applicable to studies of astrophysical objects with highly complex emission line shapes as it provides a simple way of obtaining the 3D kinematics from the means of Gaussian components. Further, the standard deviation and the amplitude of each Gaussian component can be used to obtain other physical parameters of the astrophysical object in many cases. As such, we expect GaussFit to be particularly useful for kinematic studies of energetic astrophysical phenomena such as supernova remnants (SNRs), and have applications to IFU data.