Abstract
Context. Galaxy submillimetre number counts are a fundamental measurement in our understanding of galaxy evolution models. Most early measurements are obtained via single-dish telescopes with substantial source confusion, whereas recent interferometric observations are limited to small areas. Aims. We used a large database of ALMA continuum observations to accurately measure galaxy number counts in multiple (sub)millimetre bands, thus bridging the flux density range between single-dish surveys and deep interferometric studies. Methods. We continued the Automated Mining of the ALMA Archive in the COSMOS Field project (A3COSMOS) and extended it with observations from the GOODS-South field (A3GOODSS). The database consists of ∼4000 pipeline-processed continuum images from the public ALMA archive, yielding 2050 unique detected sources, including sources with and without a known optical counterpart. To infer galaxy number counts, we constructed a method to reduce the observational bias inherent to targeted pointings that dominate the database. This method comprises a combination of image selection, masking, and source weighting. The effective area was calculated by accounting for inhomogeneous wavelengths, sensitivities, and resolutions and for the spatial overlap between images. We tested and calibrated our method with simulations. Results. We derived the number counts in a consistent and homogeneous way in four different ALMA bands covering a relatively large area. The results are consistent with number counts retrieved from the literature within the uncertainties. In Band 7, at the depth of the inferred number counts, ∼40% of the cosmic infrared background is resolved into discrete sources. This fraction, however, decreases with increasing wavelength, reaching ∼4% in Band 3. Finally, we used the number counts to test models of dusty galaxy evolution, and find a good agreement within the uncertainties. Conclusions. By continuing the A3COSMOS and A3GOODSS archival effort, we obtained the deepest archive-based (sub)millimetre number counts measured to date over such a wide area. This database proves to be a valuable resource that, thanks to its substantial size, can be used for statistical analyses after having applied certain conservative restrictions.
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