Probabilistic and progressive deblended far-infrared and sub-millimetre point source catalogues I. Methodology and first application in the COSMOS field
Lingyu Wang, Antonio La Marca, Fangyou Gao, William J. Pearson, Berta, Margalef-Bentabol, Matthieu B\'ethermin, Longji Bing, James Donnellan, Peter, D. Hurley, Seb J. Oliver, Catherine L. Hale, Matt J. Jarvis, Lucia Marchetti,, Mattia Vaccari, and Imogen H. Whittam

TL;DR
This paper introduces a Bayesian probabilistic deblending method using neural network emulators to create accurate far-IR and sub-mm point source catalogues, validated with simulations and real data in the COSMOS field.
Contribution
It develops a novel, progressive deblending pipeline that combines Bayesian modeling with neural network emulators for improved source separation across multiple wavelengths.
Findings
Higher flux accuracy compared to previous catalogues.
Effective deblending across multiple far-IR and sub-mm bands.
Public release of the deblended point source catalogues.
Abstract
Single-dish far-infrared (far-IR) and sub-millimetre (sub-mm) point source catalogues and their connections with catalogues at other wavelengths are of paramount importance. However, due to the large mismatch in spatial resolution, cross-matching galaxies at different wavelengths is challenging. This work aims to develop the next-generation deblended far-IR and sub-mm catalogues and present the first application in the COSMOS field. Our progressive deblending used the Bayesian probabilistic framework known as XID+. The deblending started from the Spitzer/MIPS 24 micron data, using an initial prior list composed of sources selected from the COSMOS2020 catalogue and radio catalogues from the VLA and the MeerKAT surveys, based on spectral energy distribution modelling which predicts fluxes of the known sources at the deblending wavelength. To speed up flux prediction, we made use of a…
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Taxonomy
TopicsCalibration and Measurement Techniques · Astronomical Observations and Instrumentation · Infrared Target Detection Methodologies
