The LOFAR Two Metre Sky Survey Data Release 2: Probabilistic Spectral Source Classifications and Faint Radio Source Demographics
A. B. Drake, D. J. B. Smith, M. J. Hardcastle, P. N. Best, R., Kondapally, M. I. Arnaudova, S. Das, S. Shenoy, K. J. Duncan, H. J. A., R\"ottgering, C. Tasse

TL;DR
This paper introduces a probabilistic classification method for over 150,000 radio sources from the LOFAR survey, combining spectral diagnostics to identify different galaxy types and black hole activity with high reliability.
Contribution
The study develops a new probabilistic approach integrating radio luminosity excess and BPT diagnostics for classifying radio sources, enhancing accuracy and reliability over previous methods.
Findings
Identified 38,588 radio-excess AGN with >90% reliability.
Classified 38,729 star-forming galaxies and 18,726 RQAGN.
Validated classifications against literature and photometric techniques.
Abstract
We present an analysis of 152,355 radio sources identified in the second data release of the LOFAR Two Metre Sky Survey (LoTSS-DR2) with Sloan Digital Sky Survey (SDSS) spectroscopic redshifts in the range 0.00 < z < 0.57. Using Monte Carlo simulations we determine the reliability of each source exhibiting an excess in radio luminosity relative to that predicted from their Ha emission, and, for a subset of 124,023 sources we combine this measurement with a full BPT analysis. Using these two independent diagnostics we determine the reliability of each source hosting a supermassive black hole of high or low Eddington-scaled accretion rate, and combine the measurements to determine the reliability of sources belonging to each of four physical classes of objects: star forming galaxies (SFGs), radio-quiet active galactic nuclei (RQAGN), and high- or low-excitation radio galaxies (HERGs or…
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