arXiv subjects

Heinz Andernach

Publications and source records attributed to Heinz Andernach.

At least 19 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.

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arXiv2026

The GLEAM 4-Jy (G4Jy) Sample: IV. Multiwavelength data and analysis

We provide an updated 'multiwavelength' version of the G4Jy catalogue (available at https://github.com/svw26/G4Jy, https://zenodo.org/communities/g4jy/records, and through VizieR), which has 127 new host-galaxy identifications, as described in Paper III of this paper series. We also supplement the redshift information (0.0 < z < 3.6), gathered in Paper III, with $griz$ photometry available through DR10 of the DESI Legacy Surveys. Together, this legacy dataset allows us to investigate the multiwavelength properties of these southern radio-bright galaxies, which includes an initial analysis of radio spectral-curvature for this complete sample (S_151MHz > 4 Jy). For example, we present (for the first time in the literature) the radio-power--size diagram as a function of radio spectral-curvature, [P--D](SCI), noting that the spectral-curvature index (SCI) can act as a proxy for the spectral age of the radio source. This radio-power--size--age diagram shows a predominance of radio galaxies with SCI > 0.15 and D < 200 kpc, which are candidates for both remnant radio-galaxies and young radio sources, and a vast range of linear sizes for candidate restarted radio-galaxies (having SCI < -0.15). We also show that (i) G4Jy sources populate the entirety of WISE colour-colour space, (ii) optically point-like sources (i.e. candidate quasars) are brighter than the well-studied K--z relation (as expected), and (iii) there is no relation between the SCI of the radio source and its host-galaxy properties.

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arXiv2026

Here Be SDRAGNs - Spiral Galaxies Hosting Large Double Radio Sources

We present a sample of large double radio sources hosted by spiral galaxies (Spiral Double Radio Active Galactic Nuclei, SDRAGNs). Candidates were selected during Radio Galaxy Zoo, and refined using Sloan Digital Sky Survey images. The most promising were targeted in the Zoo Gems Hubble Space Telescope program, yielding images for 36 candidates. We assess the likelihood of each spiral galaxy being the genuine host of the radio emission finding 15 new high-probability SDRAGNs. SDRAGN hosts are seen preferentially close to edge-on. SDRAGNs predominantly show FR II radio structures and optical pseudobulges. Accounting for sample selection effects, the radio-jet axes lie preferentially near the poles of the galaxy disks; we find a constant probability distribution for intrinsic pole-jet angles < 30 degrees, ramping to zero at 60 degrees. We have obtained optical spectra for all these new SDRAGNs. Among both previous and new SDRAGN samples, 8/25 show Seyfert 2 signatures, 6/25 show central star formation, and 5/25 show LINER emission strong enough to indicate AGN or shock ionization, broadly similar to radio galaxies in elliptical hosts with the addition of star formation (diluting or masking weak AGN signatures). SDRAGNs include FR II sources seen at unusually low radio power, and preferentially occur in significant galaxy overdensities on 1-Mpc scales. Our "false alarms" - systems where HST data show the spiral to not be the actual host galaxy - include radio sources seen through large parts of foreground spiral disks, potentially useful for Faraday-rotation studies of disk magnetic fields.

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arXiv2026

The GLEAM 4-Jy (G4Jy) Sample: III. Further host-galaxy identification, and redshift assessment

In this paper we present 127 new host-galaxy identifications for G4Jy sources (S_151MHz > 4 Jy), based on radio images from MeerKAT, the Very Large Array Sky Survey (VLASS), and the Rapid ASKAP (Australian Square Kilometre Array Pathfinder) Continuum Survey (RACS). This includes identifications that result from visual inspection of radio contours on K_s-band images, as opposed to the AllWISE-W1 images that were used for the original set of overlays when defining the G4Jy Sample (Papers I and II). Our aim is to achieve 100 per cent spectroscopic completeness for the sample, where all of the spectroscopy is available in digital form online. For now, we have gathered (i) digital optical spectroscopy for 34 per cent of the sample, (ii) photometric redshifts for an additional 21 per cent of the sample, and (iii) further redshifts found through the NASA/IPAC Extragalactic Database (but not recently verified). Our assessment of the redshifts includes visual inspection of all of the digital spectroscopy, and re-fitting redshift templates where necessary. The resulting redshift range is (currently) 0.0 < z < 3.6. We also present 151-MHz luminosities and linear sizes for the G4Jy Sample, based on initial analysis.

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arXiv2025

Searching for the Largest Radio Galaxies

The origins of radio astronomy and the discovery of the first radio galaxies are described which showed that the radio emission of active galaxies is very diverse in shape and can reach a size of many times their optical extent. In 1974 the first "giant" radio galaxy (GRG) was discovered, several times larger than any previously known one. Since 2012, when about 100 such GRGs larger than 1 Megaparsec (3.3 million light years) had been reported in literature, the author is performing his own search for GRGs and maintains a list of currently nearly 7000 GRGs, with more than half of these found on his own or his students at the Departamento de Astronomía of Universidad de Guanajuato. An analysis of the very largest GRGs does not reveal any single property of these that would explain why they could grow to such large sizes. Recent advances in radio telescopes have led to vast amounts of images rich in GRGs, but due to the complexity of identifying their host galaxies only a fraction of these images can be searched with visual inspection by humans. Currently available machine algorithms and citizen science projects are prone to erroneous identifications and also leave unnoticed a substantial fraction of GRGs, such that supervision of the results by experts is essential to produce reliable results.

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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.

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arXiv2025

Discovery of Odd Radio Circles and Other Peculiars in the First Year of the EMU Survey using Object Detection

We present a systematic search for Odd Radio Circles (ORCs) and other unusual radio morphologies using data from the first year of the EMU (Evolutionary Map of the Universe) survey. ORCs are rare, enigmatic objects characterized by edge-brightened rings of radio emission, often found in association with distant galaxies. To identify these objects, we employ a hybrid methodology combining supervised object detection techniques and visual inspection of radio source candidates. This approach leads to the discovery of five new ORCs and two additional candidate ORCs, expanding the known population of these objects. In addition to ORCs, we also identify 55 Galaxies with Large-scale Ambient Radio Emission (GLAREs), which feature irregular, rectangular, or circular shapes of diffuse radio emission mostly surrounding central host galaxies. These GLAREs may represent different evolutionary stages of ORCs, and studying them could offer valuable insights into their evolutionary processes. We also highlight a subset of Starburst Radio Ring Galaxies (SRRGs), which are star-forming galaxies exhibiting edge-brightened radio rings surrounding their central star-forming regions. We emphasize the importance of multi-wavelength follow-up observations to better understand the physical properties, host galaxy characteristics, and evolutionary pathways of these radio sources.

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arXiv2025

Identification of 4876 Bent-Tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection

Bent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intra-cluster medium. A combined method, which involves a deep learning-based radio source finder along with visual inspection, has been utilized to search for BTRGs from the Faint Images of the Radio Sky at Twenty-centimeters survey images. Consequently, a catalog of 4876 BTRGs has been constructed, among which 3871 are newly discovered. Based on the classification scheme of the opening angle between the two jets of the galaxy, BTRGs are typically classified as either wide-angle-tail (WAT) sources or narrow-angle-tail (NAT) sources. Our catalog comprises 4424 WATs and 652 NATs. Among these, optical counterparts are identified for 4193 BTRGs. This catalog covers luminosities in the range of $1.91\times10^{20} \leq L_{\rm 1.4\,GHz} \leq 1.45\times10^{28}$ ${\rm W\,Hz^{-1}}$ and redshifts from $z = 0.0023$ to $z = 3.43$. Various physical properties of these BTRGs and their statistics are presented. Particularly, by the nearest neighbor method, we found that 1825 BTRGs in this catalog belong to galaxy clusters reported in literature.

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arXiv2024

MeerKAT discovery of a double radio relic and odd radio circle: connecting cluster and galaxy merger shocks

We present the serendipitous discovery of (1) a large double radio relic associated with the galaxy cluster PSZ2 G277.93+12.34 and (2) a new odd radio circle, ORC J1027-4422, both found in the same deep MeerKAT 1.3 GHz wide-band radio continuum image. The angular separation of the two arc-shaped cluster relics is ~16 arcmin or ~2.6 Mpc for a cluster redshift of z ~ 0.158. The thin southern relic, which shows several ridges/shocks including one possibly moving inwards, has a linear extent of ~1.64 Mpc. In contrast, the northern relic is about twice as wide, twice as bright, but only has a largest linear size of ~0.66 Mpc. Complementary SRG/eROSITA X-ray images reveal extended emission from hot intracluster gas between the two relics and around the narrow-angle tail (NAT) radio galaxy PMN J1033-4335 (z ~ 0.153) located just east of the northern relic. The radio morphologies of the NAT galaxy and the northern relic, which are also detected with the Australian Square Kilometer Array Pathfinder (ASKAP) at 888 MHz, suggest both are moving in the same outward direction. The discovery of ORC J1027-4422 in a different part of the same MeerKAT image makes it the 4th known single ORC. It has a diameter of ~90 arcsec corresponding to 400 kpc at a tentative redshift of z ~ 0.3 and remains undetected in X-ray emission. Supported by simulations, we discuss similarities between outward moving galaxy and cluster merger shocks as the formation mechanisms for ORCs and radio relics, respectively.

astro-ph.GA↗

arXiv2024

Rotation and flipping invariant self-organizing maps with astronomical images: A cookbook and application to the VLA Sky Survey QuickLook images

Modern wide field radio surveys typically detect millions of objects. Techniques based on machine learning are proving to be useful for classifying large numbers of objects. The self-organizing map (SOM) is an unsupervised machine learning algorithm that projects a many-dimensional dataset onto a two- or three-dimensional lattice of neurons. This dimensionality reduction allows the user to visualize common features of the data better and develop algorithms for classifying objects that are not otherwise possible with large datasets. To this aim, we use the PINK implementation of a SOM. PINK incorporates rotation and flipping invariance so that the SOM algorithm may be applied to astronomical images. In this cookbook we provide instructions for working with PINK, including preprocessing the input images, training the model, and offering lessons learned through experimentation. The problem of imbalanced classes can be improved by careful selection of the training sample and increasing the number of neurons in the SOM (chosen by the user). Because PINK is not scale-invariant, structure can be smeared in the neurons. This can also be improved by increasing the number of neurons in the SOM. We also introduce pyink, a Python package used to read and write PINK binary files, assist in common preprocessing operations, perform standard analyses, visualize the SOM and preprocessed images, and create image-based annotations using a graphical interface. A tutorial is also provided to guide the user through the entire process. We present an application of PINK to VLA Sky Survey (VLASS) images. We demonstrate that the PINK is generally able to group VLASS sources with similar morphology together. We use the results of PINK to estimate the probability that a given source in the VLASS QuickLook Catalogue is actually due to sidelobe contamination.

astro-ph.IM↗

arXiv2024

The power of relativistic jets: a comparative study

We present the results of a comparison between different methods to estimate the power of relativistic jets from active galactic nuclei (AGN). We selected a sample of 32 objects (21 flat-spectrum radio quasars, 7 BL Lacertae Objects, 2 misaligned AGN, and 2 changing-look AGN) from the Very Large Baseline Array (VLBA) observations at 43 GHz of the Boston University blazar program. We then calculated the total, radiative, and kinetic jet power from both radio and high-energy gamma-ray observations, and compare the values. We found an excellent agreement between the radiative power calculated by using the Blandford and Königl model with 37 or 43 GHz data, and the values derived from the high-energy $γ-$ray luminosity. The agreement is still acceptable if 15 GHz data are used, although with a larger dispersion, but it improves if we use a constant fraction of the $γ-$ray luminosity. We found a good agreement also for the kinetic power calculated with Blandford and Königl model with 15 GHz data, and the value from the extended radio emission. We also propose some easy-to-use equations to estimate the jet power.

astro-ph.HE↗

arXiv2024

RG-CAT: Detection Pipeline and Catalogue of Radio Galaxies in the EMU Pilot Survey

We present source detection and catalogue construction pipelines to build the first catalogue of radio galaxies from the 270 $\rm deg^2$ pilot survey of the Evolutionary Map of the Universe (EMU-PS) conducted with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The detection pipeline uses Gal-DINO computer-vision networks (Gupta et al., 2024) to predict the categories of radio morphology and bounding boxes for radio sources, as well as their potential infrared host positions. The Gal-DINO network is trained and evaluated on approximately 5,000 visually inspected radio galaxies and their infrared hosts, encompassing both compact and extended radio morphologies. We find that the Intersection over Union (IoU) for the predicted and ground truth bounding boxes is larger than 0.5 for 99% of the radio sources, and 98% of predicted host positions are within $3^{\prime \prime}$ of the ground truth infrared host in the evaluation set. The catalogue construction pipeline uses the predictions of the trained network on the radio and infrared image cutouts based on the catalogue of radio components identified using the Selavy source finder algorithm. Confidence scores of the predictions are then used to prioritize Selavy components with higher scores and incorporate them first into the catalogue. This results in identifications for a total of 211,625 radio sources, with 201,211 classified as compact and unresolved. The remaining 10,414 are categorized as extended radio morphologies, including 582 FR-I, 5,602 FR-II, 1,494 FR-x (uncertain whether FR-I or FR-II), 2,375 R (single-peak resolved) radio galaxies, and 361 with peculiar and other rare morphologies. We cross-match the radio sources in the catalogue with the infrared and optical catalogues, finding infrared cross-matches for 73% and photometric redshifts for 36% of the radio galaxies.

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arXiv2023

The Discovery of 63 Giant Radio Galaxies in the FIRST Survey

Giant Radio Galaxies (GRGs) are Active Galactic Nuclei (AGN) with radio emission that extends over projected sizes $>0.7\,$Mpc. The large angular sizes associated with GRGs complicate their identification in radio survey images using traditional source finders. In this Note, we use DRAGNhunter, an algorithm designed to find double-lobed radio galaxies, to search for GRGs in the Faint Images of the Radio Sky at Twenty cm survey (FIRST). Radio and optical images of identified candidates are visually inspected to confirm their authenticity, resulting in the discovery of $63$ previously unreported GRGs.

astro-ph.GA↗

arXiv2023

Tracing the assembly histories of galaxy clusters in the nearby universe

We have compiled a sample of 67 nearby ($z$ < 0.15) clusters of galaxies, for which on average more than 150 spectroscopic members are available, and, by applying different methods to detect substructures in their galaxy distribution, we have studied their assembly history. Our analysis confirms that substructures are present in 70% of our sample, having a significant dynamical impact in 57% of them. A classification of the assembly state of the clusters based on the dynamical significance of their substructures is proposed. In 19% of our clusters, the originally identified brightest cluster galaxy is not the central gravitationally dominant galaxy (CDG), but turns out to be either the second-rank, or the dominant galaxy of a substructure (a SDG, in our classification), or even a possible "fossil" galaxy in the periphery of the cluster. Moreover, no correlation was found in general between the projected offset of the CDG from the X-ray peak and its peculiar velocity. The comparison of the CDGs properties with the assembly states and dynamical state of the intracluster media, especially the core cooling status, suggests a complex assembly history, with clear evidence of co-evolution of the CDG and its host cluster in the innermost regions.

astro-ph.CO↗

arXiv2023

Deep Learning for Morphological Identification of Extended Radio Galaxies using Weak Labels

The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25-35 $μ$Jy/beam. We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP$_{50}$ of 67.5\% and 76.8\% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM

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arXiv2023

A Quick Look at the 3GHz Radio Sky. II. Hunting for DRAGNs in the VLA Sky Survey

Active Galactic Nuclei (AGN) can often be identified in radio images as two lobes, sometimes connected to a core by a radio jet. This multi-component morphology unfortunately creates difficulties for source-finders, leading to components that are a) separate parts of a wider whole, and b) offset from the multiwavelength cross identification of the host galaxy. In this work we define an algorithm, \textsc{DRAGNhunter}, for identifying Double Radio Sources associated with Active Galactic Nuclei (DRAGNs) from component catalog data in the first epoch \textit{Quick Look} images of the high resolution ($\approx 3''$ beam size) Very Large Array Sky Survey (VLASS). We use \textsc{DRAGNhunter} to construct a catalog of $>17,000$ DRAGNs in VLASS for which contamination from spurious sources is estimated at $\approx 11\,\%$. A `high-fidelity' sample consisting of $90\,\%$ of our catalog is identified for which contamination is $<3\,\%$. Host galaxies are found for $\approx 13,000$ DRAGNs as well as for an additional $234,000$ single-component radio sources. Using these data we explore the properties of our DRAGNs, finding them to be typically consistent with Fanaroff-Riley class II sources and allowing us to report the discovery of $31$ new giant radio galaxies identified using VLASS.

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arXiv2023

Identifying anomalous radio sources in the EMU Pilot Survey using a complexity-based approach

The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously unknown classes of objects. To maximise the scientific value and make new discoveries, the analysis of this data will need to go beyond simple visual inspection. We propose the coarse-grained complexity, a simple scalar quantity relating to the minimum description length of an image, that can be used to identify unusual structures. The complexity can be computed without reference to the broader sample or existing catalogue data, making the computation efficient on new surveys at very large scales (such as the full EMU survey). We apply our coarse-grained complexity measure to data from the EMU Pilot Survey to detect and confirm anomalous objects in this data set and produce an anomaly catalogue. Rather than work with existing catalogue data using a specific source detection algorithm, we perform a blind scan of the area, computing the complexity using a sliding square aperture. The effectiveness of the complexity measure for identifying anomalous objects is evaluated using crowd-sourced labels generated via the Zooniverse.org platform. We find that the complexity scan identifies unusual sources, such as odd radio circles, by partitioning on complexity. We achieve partitions where 5\% of the data is estimated to be 86\% complete, and 0.5\% is estimated to be 94\% pure, with respect to anomalies and use this to produce an anomaly catalogue.

astro-ph.IM↗

arXiv2023

Revisiting the alignment of radio galaxies in the ELAIS-N1 field

Aims. Previous studies reported an alignment of the major axes of radio galaxies on various angular scales. Here, we study the alignment of radio galaxies in the ELAIS-N1 Low Frequency ARray (LOFAR) deep field, which covers an area of 25 $\rm deg^2$. \newline Methods. The low noise level of about 20$ \rm ~ μJy/beam$ of the LOFAR deep field observations at 150 MHz enabled the identification of 447 extended ($> 30 \rm ''$) radio galaxies for which we have measured the major axis position angle. We found that 95\% of these sources have either photometric or spectroscopic redshifts, which we then used for a three-dimensional analysis. \newline Results. We show the distribution of the position angles of radio galaxies in the ELAIS-N1 field and perform multiple statistical tests to check whether the radio galaxies are randomly oriented. We found that the distribution of position angles is consistent with being uniform. Two peaks around position angles of 50 and 140$\rm~ deg$ are spurious and are not caused by an alignment, as shown by a 3D analysis. In conclusion, our results do not support a 2D or 3D alignment of radio galaxies on scales smaller than $\sim 4 \rm ~ deg$.

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