Crossmatch Skill

Astronomical source cross-matching compares detected sources in image data against reference catalogs like NVSS, FIRST, or RACS. It calculates positional offsets between matched pairs, enabling you to correct astrometry in radio continuum imaging pipelines.

Multi-catalog matching supports comparing detected sources against several reference catalogs simultaneously. The Skill utilizes Python scripts to execute nearest neighbor and all matches algorithms, providing matched pairs, unmatched sources, and positional offsets as outputs.

Flux scale correction validates detected source fluxes by comparing them to established catalog values. The Skill calculates flux scale ratios from matched sources, allowing you to adjust and align your detected source fluxes with known reference catalog measurements.

Source cross-matching is designed to facilitate astrometric and flux scale corrections for radio continuum imaging pipelines. It processes image data to identify known cataloged objects and outputs matched pairs alongside unmatched sources for pipeline integration.

Crossmatching outputs include matched source pairs, unmatched detected sources, positional offsets, and flux scale ratios. These results enable source identification, astrometry correction, and flux scale validation for your radio imaging data.

Nearest neighbor matching identifies the closest catalog source for each detection, while all matches retrieves every potential counterpart. Choose nearest neighbor for straightforward source identification, or all matches to analyze complex regions with multiple nearby cataloged objects.