PHOTO-CAT Contamination Assessment of the Ariel Mission Candidate Sample (MCS): Target-by-Target Gaia DR3 JSON Outputs

Le résumé fourni par la source

This dataset accompanies G. Galletta et al. (2026), "PHOTO-CAT - Photometric Contamination Analyzer Tool: A High-Performance Framework for Photometric Contamination Assessment". It contains the complete JSON outputs generated by PHOTO-CAT for the Ariel Mission Candidate Sample (MCS, May 2026), providing target-by-target wavelength-dependent photometric contamination estimates derived from Gaia DR3 and transformed into the Ariel instrumental bands using stellar spectral energy distributions and instrument transmission curves. The dataset includes contamination estimates for the six Ariel channels considered in the analysis: AIRS-CH0, AIRS-CH1, FGS1, FGS2, NIRSpec, and VISPhot. For each channel, two independent analyses are provided, corresponding to different circular contamination radii adopted as first-order approximations of the Ariel slit geometry: 13.2 arcsec radius, representing a conservative contamination scenario based on half of the Ariel slit length. 3.2 arcsec radius, representing the slit half-width and therefore contaminants that are geometrically unavoidable regardless of slit orientation. Each JSON file corresponds to one Ariel channel and one adopted contamination radius. Each entry corresponds to a single Ariel target and reports the target identifier and astrometric information, the contamination metrics computed in the corresponding instrumental band, the number of neighboring stars and selected contaminants, and the detailed properties of every contaminating source (including Gaia source identifier, coordinates, Gaia magnitude, angular separation, and estimated contribution in the selected Ariel channel). The adopted contamination model (top-hat aperture approximation) is also reported. The dataset therefore provides wavelength-dependent, target-by-target contamination estimates for all analyzed Ariel channels and allows the complete reproduction of the contamination statistics presented in the paper. It can be used to evaluate contamination risks, identify the neighboring sources responsible for flux contamination, compare contamination levels across Ariel channels, and support observation planning and target prioritization for the Ariel mission.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.