arXiv subjects

Lachlan J. Barnes

Publications and source records attributed to Lachlan J. Barnes.

3 recordsLinked to original sources

arXiv2026

Extended Radio Galaxies in EMU: A Comparative Look at Source-Finding Techniques

Extended radio sources present unique challenges for automated detection and classification in wide-field radio surveys. With current surveys such as the Evolutionary Map of the Universe (EMU), robust and scalable methods are essential to identify and catalogue these complex sources. We apply three automatic approaches to detect complex radio emission in EMU observations of the Galaxy And Mass Assembly (GAMA) 09 field (EMU-G09) in order to evaluate their relative strengths and limitations in preparation for large-scale application across future EMU data releases. These include DRAGNHunter, designed to detect likely DRAGNs (Double Radio sources associated with Active Galactic Nuclei) from a component catalogue; coarse-grained complexity, a metric designed to highlight regions of complex emission; and RG-CAT, a machine learning pipeline trained on radio sources identified in the EMU pilot survey. We find that together, the three methods recover nearly all extended sources in EMU-G09 but identify largely distinct, partially-overlapping subsets, with only 375 sources identified by all finders. This demonstrates that a combination of complementary techniques will be required to achieve a complete census of extended radio sources in future large-scale surveys.

astro-ph.GA↗

arXiv2026

The life of central radio galaxies in clusters: AGN-ICM studies of eRASS1 clusters in the ASKAP fields

The mechanical feedback from the central AGNs can be crucial for balancing the radiative cooling of the intracluster medium at the cluster centre. We aim to understand the relationship between the power of AGN feedback and the cooling of gas in the centres of galaxy clusters by correlating the radio properties of the brightest cluster galaxies (BCGs) with the X-ray properties of their host clusters. We used catalogues from the first SRG/eROSITA All-Sky Survey (eRASS1) along with ASKAP radio data. In total, we identified 134 radio sources associated with BCGs of the 151 eRASS1 clusters located in the PS1, PS2, and SWAG-X ASKAP fields. Non-detections were treated as upper limits. We correlated BCG radio luminosity, largest linear size (LLS), and BCG offset with the integrated X-ray luminosity of their host clusters. To characterise cool cores (CCs) and non-cool cores (NCCs), we used the concentration parameter $c_{R_{500}}$ and combined it with the BCG offset to assess cluster dynamical state. We analysed the correlation between radio mechanical power and X-ray luminosity within the CC subsample. We observe a potential positive trend between LLS and BCG offset, suggesting an environmental effect on radio-source morphology. We find a weak trend where more luminous central radio galaxies are found in clusters with higher X-ray luminosity. Within the CC subsample, there is a positive but highly scattered relationship between the mechanical luminosity of AGN jets and the X-ray cooling luminosity. This finding is supported by bootstrap resampling and flux-flux analyses. The correlation indicates that AGN feedback is ineffective in high-luminosity (high-mass) clusters. At a cooling luminosity of $L_{\mathrm{X},~r<R_\mathrm{cool}}\approx 5.50\times10^{43}$ erg/s, on average, AGN feedback appears to contribute only about 13%-22% of the energy needed to offset the radiative losses in the ICM.

astro-ph.CO↗

arXiv2025

Quantifying Radio Source Morphology

The advent of next-generation telescope facilities brings with it an unprecedented amount of data, and the demand for effective tools to process and classify this information has become increasingly important. This work proposes a novel approach to quantify the radio galaxy morphology, through the development of a series of algorithmic metrics that can quantitatively describe the structure of radio source, and can be applied to radio images in an automatic way. These metrics are intuitive in nature and are inspired by the intrinsic structural differences observed between the existing Fanaroff-Riley (FR) morphology types. The metrics are defined in categories of asymmetry, blurriness, concentration, disorder, and elongation ($ABCDE$/single-lobe metrics), as well as the asymmetry and angle between lobes (source metrics). We apply these metrics to a sample of $480$ sources from the Evolutionary Map of the Universe Pilot Survey (EMU-PS) and $72$ well resolved extensively studied sources from An Atlas of DRAGNs, a subset of the revised Third Cambridge Catalogue of Radio Sources (3CRR). We find that these metrics are relatively robust to resolution changes, independent of each other, and measure fundamentally different structural components of radio galaxy lobes. These metrics work particularly well for sources with reasonable signal-to-noise and well separated lobes. We also find that we can recover the original FR classification using probabilistic combinations of our metrics, highlighting the usefulness of our approach for future large data sets from radio sky surveys.

astro-ph.GA↗