Multi-frequency matching, classification, and cosmic evolution of radio galaxy populations
thesisposted on 2023-05-28, 10:18 authored by Swan, JE
This thesis combines the third data release of the Australia Telescope Large Area Survey (ATLAS) with complimentary DES photometry and OzDES targeted spectroscopy. ATLAS 1:4 GHz is a deep (< 20 ˜í¬¿Jy/beam) survey of the combined 6:3 deg\\(^2\\) sky area of CDFS and ELAIS-S1. Cross-matching of 4903 ATLAS sources to photometric and spectroscopic counterparts is performed visually using custom interactive software: MCVCM. I compare the results from this visual matching to results from simple coordinate-based nearest-neighbour matching. The visually constructed catalogues are substantially more robust due to a better accounting of chance alignments and dense field mismatches. Both cross-matching techniques are performed directly from radio-to-optical, and indirectly by matching radio sources to an infrared-optical paired catalogue. There is a definite improvement for both visual and nearest-neighbour cross-matching when performed via SWIRE infrared intermediary catalogue. I use the visual catalogue to build a reliable sample of ATLAS sources matched to SWIRE infrared photometry, DES optical photometry, and OzDES spectra. This catalogue was developed carefully and is intended to for use as a comparison and training catalogue for the development of intelligent automated cross-matching algorithms. Galaxies are segregated into star-forming and AGN populations using a combination of visual spectral classification, morphology, multi-frequency diagnostics, and optical spectral line diagnostics. For these populations, 1:4 GHz radio luminosity functions (RLFs) are constructed incrementally out to a redshift z < 1.0. These results improve upon ATLAS-DR1 RLFs and agree with established literature results. Evidence of the space-density evolution of radio source is apparent for both populations towards higher redshifts, indicating increased star-formation and AGN luminosity in earlier cosmic epochs. I construct RLFs for both visual galaxy classification and a combined classification based on a novel numerical combination of classification diagnostics. The combined classification provides higher reliability and completeness resulting in less confounded and deeper RLF. Cross-matching techniques capable of identifying extended and confounded radio sources combined with a robust galaxy classification scheme are therefore essential for quantifying the evolution of radio galaxy populations.
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