CASSIS: The Cornell Atlas of Spitzer/Infrared Spectrograph Sources. II. High-resolution observations

TL;DR

CASSIS provides high-resolution Spitzer/IRS spectra for about one third of observed objects, enabling precise analysis of narrow spectral features and improving data quality through advanced extraction techniques.

Contribution

This paper introduces the addition of high-resolution spectra to the CASSIS database and details improved extraction methods for better spectral quality.

Findings

High-resolution spectra enable accurate measurement of narrow features.

The pipeline reduces artifacts like cosmic rays and rogue pixels.

Optimal extraction improves signal-to-noise ratio for unresolved sources.

Abstract

The Infrared Spectrograph (IRS) on board the Spitzer Space Telescope observed about 15,000 objects during the cryogenic mission lifetime. Observations provided low-resolution (R~60-127) spectra over ~5-38um and high-resolution (R~600) spectra over ~10-37um. The Cornell Atlas of Spitzer/IRS Sources (CASSIS) was created to provide publishable quality spectra to the community. Low-resolution spectra have been available in CASSIS since 2011, and we present here the addition of the high-resolution spectra. The high-resolution observations represent approximately one third of all staring observations performed with the IRS instrument. While low-resolution observations are adapted to faint objects and/or broad spectral features (e.g., dust continuum, molecular bands), high-resolution observations allow more accurate measurements of narrow features (e.g., ionic emission lines) as well as a better sampling of the spectral profile of various features. Given the narrow aperture of the two high-resolution modules, cosmic ray hits and spurious features usually plague the spectra. Our pipeline is designed to minimize these effects through various improvements. A super sampled point-spread function was created in order to enable the optimal extraction in addition to the full aperture extraction. The pipeline selects the best extraction method based on the spatial extent of the object. For unresolved sources, the optimal extraction provides a significant improvement in signal-to-noise ratio over a full aperture extraction. We have developed several techniques for optimal extraction, including a differential method that eliminates low-level rogue pixels (even when no dedicated background observation was performed). The updated CASSIS repository now includes all the spectra ever taken by the IRS, with the exception of mapping observations.