$\texttt{raccoon}$: A Python package for removing wiggle artifacts in the JWST NIRSpec integral field spectroscopy

TL;DR

raccoon is a Python package designed to remove resampling-induced wiggle artifacts from JWST NIRSpec IFS datacubes, improving spectral fidelity by modeling and subtracting these artifacts during data reduction.

Contribution

It introduces an empirical method to correct for undersampling-induced wiggles in NIRSpec data, enhancing data quality beyond standard pipeline capabilities.

Findings

Effective removal of wiggle artifacts from NIRSpec data

Restoration of spectral fidelity at the spaxel level

Improved scientific usability of JWST NIRSpec observations

Abstract

$\texttt{raccoon}$ is a Python package for removing resampling noise - commonly referred to as "wiggles'' - from spaxel-level spectra in datacubes obtained from the JWST Near Infrared Spectrograph's (NIRSpec) integral field spectroscopy (IFS) mode. These wiggles arise as artifacts during resampling of the 2D raw data into 3D datacubes, due to the point spread function (PSF) being undersampled. The standard JWST data reduction pipeline does not correct for this noise. The wiggle artifacts can significantly degrade the scientific usability of the data, particularly at the spaxel level, undermining the exquisite spatial resolution of NIRSpec. $\texttt{raccoon}$ provides an empirical correction by modeling and removing these artifacts, thereby restoring the fidelity of the extracted spectra. $\texttt{raccoon}$ forward-models the wiggles as a chirp function impacting one or more template spectra that are directly fit to the original data across the entire wavelength range. The best-fit wiggle model is then used to clean the data while propagating the associated uncertainties.