Inside catalogs: a comparison of source extraction software
M. Annunziatella, A. Mercurio, M. Brescia, S. Cavuoti, G. Longo

TL;DR
This paper compares the performance of SExtractor with PSFEx against DAOPHOT with ALLSTAR for source extraction in simulated images, highlighting their respective strengths in star/galaxy separation, photometry, and catalog completeness.
Contribution
It demonstrates that the new SExtractor+PSFEx combination is competitive with DAOPHOT, especially for galaxy characterization and faint source detection.
Findings
SExtractor+PSFEx produces deeper catalogs than DAOPHOT.
Neural networks and SPREAD_MODEL improve star/galaxy separation.
Performance declines in crowded fields for both software.
Abstract
The scope of this paper is to compare the catalog extraction performances obtained using the new combination of SExtractor with PSFEx, against the more traditional and diffuse application of DAOPHOT with ALLSTAR; therefore, the paper may provide a guide for the selection of the most suitable catalog extraction software. Both software packages were tested on two kinds of simulated images having, respectively, a uniform spatial distribution of sources and an overdensity in the center. In both cases, SExtractor is able to generate a deeper catalog than DAOPHOT. Moreover, the use of neural networks for object classification plus the novel SPREAD\_MODEL parameter push down to the limiting magnitude the possibility of star/galaxy separation. DAOPHOT and ALLSTAR provide an optimal solution for point-source photometry in stellar fields and very accurate and reliable PSF photometry, with robust…
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