Long-term rotational and emission variability of 17 radio pulsars
(2022)
Radio Galaxy Zoo: Using semi-supervised learning to leverage large unlabelled data-sets for radio galaxy classification under data-set shift
ArXiv 2204.08816 (2022)
The science case and challenges of space-borne sub-millimeter interferometry
(2022)
Hybrid photometric redshifts for sources in the COSMOS and XMM-LSS fields
Monthly Notices of the Royal Astronomical Society Oxford University Press 513:3 (2022) 3719-3733
Abstract:
In this paper we present photometric redshifts for 2.7 million galaxies in the XMM-LSS and COSMOS fields, both with rich optical and near-infrared data from VISTA and HyperSuprimeCam. Both template fitting (using galaxy and Active Galactic Nuclei templates within LePhare) and machine learning (using GPz) methods are run on the aperture photometry of sources selected in the Ks-band. The resulting predictions are then combined using a Hierarchical Bayesian model, to produce consensus photometric redshift point estimates and probability distribution functions that outperform each method individually. Our point estimates have a root mean square error of ∼0.08 − 0.09, and an outlier fraction of ∼3 − 4 percent when compared to spectroscopic redshifts. We also compare our results to the COSMOS2020 photometric redshifts, which contains fewer sources, but had access to a larger number of bands and greater wavelength coverage, finding that comparable photo-z quality can be achieved (for bright and intermediate luminosity sources where a direct comparison can be made). Our resulting redshifts represent the most accurate set of photometric redshifts (for a catalogue this large) for these deep multi-square degree multi-wavelength fields to date.Radio footprints of a minor merger in the Shapley Supercluster: from supercluster down to galactic scales
Astronomy and Astrophysics EDP Sciences 660 (2022) A81