arXiv subjects

Nikhel Gupta

Publications and source records attributed to Nikhel Gupta.

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.

astro-ph.GA↗

arXiv2025

Machine Learning Frameworks for Large-Scale Radio Surveys: A Summary of Recent Studies

The rapid growth of large-scale radio surveys, generating over 100 petabytes of data annually, has created a pressing need for automated data analysis methods. Recent research has explored the application of machine learning techniques to address the challenges associated with detecting and classifying radio galaxies, as well as discovering peculiar radio sources. This paper provides an overview of our investigations with the Evolutionary Map of the Universe (EMU) survey, detailing the methodologies employed-including supervised, unsupervised, self-supervised, and weakly supervised learning approaches -- and their implications for ongoing and future radio astronomical surveys.

astro-ph.IM↗

arXiv2025

Deep polarimetry study reveals double ring ORC-like structures

New observations with the current generation of advanced radio interferometers, such as ASKAP and MeerKAT, have led to the discovery of new classes of extended radio sources of unknown origin, including the so-called Odd Radio Circles (ORCs). These phenomena are detected exclusively in the radio continuum, with no clear counterparts at other wavelengths, making their physical nature and origin a subject of ongoing investigation. To better understand these objects, we study their radio continuum emission, spectral characteristics, and magnetic field properties. In this work, we present a radio spectropolarimetry analysis of a newly discovered ORC (ORC J0356-4216) that exhibits a rare double-ring morphology. We use data from the MeerKAT L-band and from the ASKAP Evolutionary Map of the Universe (EMU) at 943 MHz. ORC J0356-4216 shows a symmetric double-ring structure with a diameter of approximately 2 arcminutes, corresponding to a physical size of 668 kpc based on the redshift ($0.494 \pm 0.068$) of its apparent host galaxy WISEA J035609.67-421603.5. The radio spectra of both rings are steep, with spectral indices of $-1.18 \pm 0.03$ and $-1.12 \pm 0.05$, and show no significant substructure. Equipartition magnetic field strengths (assuming K0 = 1) are estimated to be 1.82 microGauss and 1.65 microGauss for the respective rings. The degree of polarisation across the object ranges between 20-30%, consistent with a non-thermal synchrotron origin. The morphology and polarisation are broadly consistent with large-scale shocks driven by powerful starburst outflows. However, the high degree of symmetry, the coherent double-ring structure, and the absence of internal substructure are features commonly associated with relic AGN lobes, making this scenario particularly compatible with the observed characteristics.

astro-ph.GA↗

arXiv2025

Stingrays in the radio sky: Two unusual diffuse radio relic sources in the direction of the Magellanic Stream

We present the discovery of two extended, low surface brightness radio continuum sources, each consisting of a near-circular body and an extended tail of emission, nicknamed Stingray 1 (ASKAP J0129-5350) and Stingray 2 (ASKAP J0245-5642). Both are found in the direction of the Magellanic Stream (MS) and were discovered in the Australian Square Kilometre Array Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) survey at 944 MHz. We combine the ASKAP data with low-frequency radio observations from the GaLactic and Extragalactic All-sky MWA Survey (GLEAM) to conduct a radio continuum analysis. We explore both Galactic/near Galactic scenarios, including runaway or circumgalactic supernova remnants (SNRs) and parentless pulsar-wind nebulae (PWNe), and extragalactic scenarios including radio active galactic nuclei (AGNs), dying radio galaxies, galaxy clusters, galaxy pairs or groups, head-tail radio galaxies, and Odd Radio Circles (ORCs), as well as the possibility that the morphology is due to a chance alignment. The Stingrays exhibit non-thermal emission with spectral indices of $\alpha$ = -0.89 $\pm$ 0.09 for Stingray 1 and $\alpha$ = -1.77 $\pm$ 0.06 for Stingray 2. We find that none of the proposed scenarios can explain all of the observed properties, however we determine it most likely that their shape is caused by some kind of complex environmental interaction. The most likely scenario from the available data is that of a head-tail radio galaxy, but more data is required for a definitive classification.

astro-ph.GA↗

arXiv2025

EMU and the DRAGNs I: A Catalogue of DRAGNs

We present a catalogue of 3557 Double Radio sources associated with Active Galactic Nuclei (DRAGNs) from the First Pilot Survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, covering 270 deg^2. We have extracted and identified each source by eye, tagged it with a morphological type and measured its parameters. The resulting catalogue will be used in subsequent papers to explore the properties of these sources, to train machine-learning algorithms for the detection of these sources in larger fields, and to compare with the results of Citizen Science projects, with the ultimate goal of understanding the physical processes that drive DRAGNs. Compared with earlier, lower sensitivity, catalogues, we find more diffuse structure and a plethora of more complex structures, ranging from wings of radio emission on the side of the jets, to types of object which have not been seen in earlier observations. As well as the well-known FR1 and FR2 sources, we find significant numbers of rare types of radio source such as Hybrid Morphology Radio Sources and one-sided jets, as well as a wide range of bent-tail and head-tail sources.

astro-ph.GA↗

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↗

arXiv2025

EMUSE: Evolutionary Map of the Universe Search Engine

We present EMUSE (Evolutionary Map of the Universe Search Engine), a tool designed for searching specific radio sources within the extensive datasets of the EMU (Evolutionary Map of the Universe) survey, with potential applications to other Big Data challenges in astronomy. Built on a multimodal approach to radio source classification and retrieval, EMUSE fine-tunes the OpenCLIP model on curated radio galaxy datasets. Leveraging the power of foundation models, our work integrates visual and textual embeddings to enable efficient and flexible searches within large radio astronomical datasets. We fine-tune OpenCLIP using a dataset of 2,900 radio galaxies, encompassing various morphological classes, including FR-I, FR-II, FR-x, R-type, and other rare and peculiar sources. The model is optimized using adapter-based fine-tuning, ensuring computational efficiency while capturing the unique characteristics of radio sources. The fine-tuned model is then deployed in EMUSE, allowing for seamless image- and text-based queries over the EMU survey dataset. Our results demonstrate the model's effectiveness in retrieving and classifying radio sources, particularly in recognizing distinct morphological features. However, challenges remain in identifying rare or previously unseen radio sources, highlighting the need for expanded datasets and continuous refinement. This study showcases the potential of multimodal machine learning in radio astronomy, paving the way for more scalable and accurate search tools in the field. The search engine is accessible at https://askap-emuse.streamlit.app/ and can be used locally by cloning the repository at https://github.com/Nikhel1/EMUSE.

astro-ph.GA↗

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.

astro-ph.GA↗

arXiv2024

ASKAP reveals the radio tail structure of the Corkscrew Galaxy shaped by its passage through the Abell 3627 cluster

Among the bent tail radio galaxies common in galaxy clusters are some with long, collimated tails (so-called head-tail galaxies) shaped by their interactions with the intracluster medium (ICM). Here we report the discovery of intricate filamentary structure in and beyond the ~28' (570 kpc) long, helical radio tail of the Corkscrew Galaxy (1610-60.5, ESO137-G007), which resides in the X-ray bright cluster Abell 3627 (D = 70 Mpc). Deep radio continuum data were obtained with wide-field Phased Array Feeds on the Australian Square Kilometer Array Pathfinder (ASKAP) at 944 MHz and 1.4 GHz. The Corkscrew Galaxy is located 15' north of the prominent wide-angle tail (WAT) radio galaxy 1610-60.8 (ESO137-G006) near the cluster centre. While the bright (young) part of its radio tail is highly collimated, the faint (old) part shows increasing oscillation amplitudes, break-ups, and filaments. We find a stunning set of arc-shaped radio filaments beyond and mostly orthogonal to the collimated Corkscrew tail end, forming a partial bubble. This may be the first detection of a "proto-lobe" seen in 3D MHD simulations by Nolting et al. (2019), formed by the face-on impact of the Corkscrew Galaxy with a shock front in the cluster outskirts. Interactions of the radio galaxy tail with the ICM are likely responsible for the tail collimation and shear forces within the ICM for its increasingly filamentary structure. We also report the discovery of small (~20-30 kpc) ram-pressure stripped radio tails in four Abell 3627 cluster galaxies.

astro-ph.GA↗

arXiv2024

The Physalis system: Discovery of ORC-like radio shells around a massive pair of interacting early-type galaxies with offset X-ray emission

We present the discovery of large radio shells around a massive pair of interacting galaxies and extended diffuse X-ray emission within the shells. The radio data were obtained with the Australian Square Kilometer Array Pathfinder (ASKAP) in two frequency bands centred at 944 MHz and 1.4 GHz, respectively, while the X-ray data are from the XMM-Newton observatory. The host galaxy pair, which consists of the early-type galaxies ESO 184-G042 and LEDA 418116, is part of a loose group at a distance of only 75 Mpc (redshift z = 0.017). The observed outer radio shells (diameter ~ 145 kpc) and ridge-like central emission of the system, ASKAP J1914-5433 (Physalis), are likely associated with merger shocks during the formation of the central galaxy (ESO 184-G042) and resemble the new class of odd radio circles (ORCs). This is supported by the brightest X-ray emission found offset from the centre of the Physalis system, instead centered at the less massive galaxy, LEDA 418116. The host galaxy pair is embedded in an irregular envelope of diffuse light, highlighting on-going interactions. We complement our combined radio and X-ray study with high-resolution simulations of the circumgalactic medium (CGM) around galaxy mergers from the Magneticum project to analyse the evolutionary state of the Physalis system. We argue that ORCs / radio shells could be produced by a combination of energy release from the central AGN and subsequent lightening up in radio emission by merger shocks traveling through the CGM of these systems.

astro-ph.GA↗

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.

astro-ph.GA↗

arXiv2023

A Multimodal Dataset and Benchmark for Radio Galaxy and Infrared Host Detection

We present a novel multimodal dataset developed by expert astronomers to automate the detection and localisation of multi-component extended radio galaxies and their corresponding infrared hosts. The dataset comprises 4,155 instances of galaxies in 2,800 images with both radio and infrared modalities. Each instance contains information on the extended radio galaxy class, its corresponding bounding box that encompasses all of its components, pixel-level segmentation mask, and the position of its corresponding infrared host galaxy. Our dataset is the first publicly accessible dataset that includes images from a highly sensitive radio telescope, infrared satellite, and instance-level annotations for their identification. We benchmark several object detection algorithms on the dataset and propose a novel multimodal approach to identify radio galaxies and the positions of infrared hosts simultaneously.

cs.CV↗

arXiv2023

RadioGalaxyNET: Dataset and Novel Computer Vision Algorithms for the Detection of Extended Radio Galaxies and Infrared Hosts

Creating radio galaxy catalogues from next-generation deep surveys requires automated identification of associated components of extended sources and their corresponding infrared hosts. In this paper, we introduce RadioGalaxyNET, a multimodal dataset, and a suite of novel computer vision algorithms designed to automate the detection and localization of multi-component extended radio galaxies and their corresponding infrared hosts. The dataset comprises 4,155 instances of galaxies in 2,800 images with both radio and infrared channels. Each instance provides information about the extended radio galaxy class, its corresponding bounding box encompassing all components, the pixel-level segmentation mask, and the keypoint position of its corresponding infrared host galaxy. RadioGalaxyNET is the first dataset to include images from the highly sensitive Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, corresponding infrared images, and instance-level annotations for galaxy detection. We benchmark several object detection algorithms on the dataset and propose a novel multimodal approach to simultaneously detect radio galaxies and the positions of infrared hosts.

astro-ph.IM↗

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 $\mu$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

astro-ph.IM↗

arXiv2022

Discovery of Peculiar Radio Morphologies with ASKAP using Unsupervised Machine Learning

We present a set of peculiar radio sources detected using an unsupervised machine learning method. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope to train a self-organizing map (SOM). The radio maps from three ASKAP surveys, Evolutionary Map of Universe pilot survey (EMU-PS), Deep Investigation of Neutral Gas Origins pilot survey (DINGO) and Survey With ASKAP of GAMA-09 + X-ray (SWAG-X), are used to search for the rarest or unknown radio morphologies. We use an extension of the SOM algorithm that implements rotation and flipping invariance on astronomical sources. The SOM is trained using the images of all "complex" radio sources in the EMU-PS which we define as all sources catalogued as "multi-component". The trained SOM is then used to estimate a similarity score for complex sources in all surveys. We select 0.5\% of the sources that are most complex according to the similarity metric, and visually examine them to find the rarest radio morphologies. Among these, we find two new odd radio circle (ORC) candidates and five other peculiar morphologies. We discuss multiwavelength properties and the optical/infrared counterparts of selected peculiar sources. In addition, we present examples of conventional radio morphologies including: diffuse emission from galaxy clusters, and resolved, bent-tailed, and FR-I and FR-II type radio galaxies. We discuss the overdense environment that may be the reason behind the circular shape of ORC candidates.

astro-ph.GA↗

arXiv2020

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4---the next-generation ground-based cosmic microwave background (CMB) experiment---is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semi-analytic projection tool, targeted explicitly towards optimizing constraints on the tensor-to-scalar ratio, $r$, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2--3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments given a desired scientific goal. To form a closed-loop process, we couple this semi-analytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for $r > 0.003$ at greater than $5\sigma$, or, in the absence of a detection, of reaching an upper limit of $r < 0.001$ at $95\%$ CL.

astro-ph.CO↗

arXiv2020

Mass Estimation of Galaxy Clusters with Deep Learning I: Sunyaev-Zel'dovich Effect

We present a new application of deep learning to infer the masses of galaxy clusters directly from images of the microwave sky. Effectively, this is a novel approach to determining the scaling relation between a cluster's Sunyaev-Zel'dovich (SZ) effect signal and mass. The deep learning algorithm used is mResUNet, which is a modified feed-forward deep learning algorithm that broadly combines residual learning, convolution layers with different dilation rates, image regression activation and a U-Net framework. We train and test the deep learning model using simulated images of the microwave sky that include signals from the cosmic microwave background (CMB), dusty and radio galaxies, instrumental noise as well as the cluster's own SZ signal. The simulated cluster sample covers the mass range 1$\times 10^{14}~\rm M_{\odot}$ $<M_{200\rm c}<$ 8$\times 10^{14}~\rm M_{\odot}$ at $z=0.7$. The trained model estimates the cluster masses with a 1 $σ$ uncertainty $ΔM/M \leq 0.2$, consistent with the input scatter on the SZ signal of 20%. We verify that the model works for realistic SZ profiles even when trained on azimuthally symmetric SZ profiles by using the Magneticum hydrodynamical simulations.

astro-ph.CO↗

arXiv2020

Forecasts for Next Generation tSZ Surveys: the Impact of a Cosmology-Dependent Selection Function

The thermal Sunyaev-Zel'dovich (tSZ) effect is one of the primary tools for finding and characterizing galaxy clusters. Several ground-based experiments are either underway or are being planned for mapping wide areas of the sky at $\sim 150$ GHz with large-aperture telescopes. We present cosmological forecasts for a 'straw man' tSZ survey that will observe a sky area between $200$ and $10^4$ deg$^2$ to an rms noise level between 2.8 and 20.2 $μ$K-arcmin. The probes we consider are the cluster number counts (as a function of the integrated Compton-$Y$ parameter and redshift) and their angular clustering (as a function of redshift). At fixed observing time, we find that wider surveys constrain cosmology slightly better than deeper ones due to their increased ability to detect rare high-mass clusters. In all cases, we notice that adding the clustering information does not practically improve the constraints derived from the number counts. We compare forecasts obtained by sampling the posterior distribution with the Markov-chain-Monte-Carlo method against those derived using the Fisher-matrix formalism. We find that the latter produces slightly optimistic constraints where errors are underestimated at the 10 per cent level. Most importantly, we use an analytic method to estimate the selection function of the survey and account for its response to variations of the cosmological parameters in the likelihood function. Our analysis demonstrates that neglecting this effect (as routinely done in the literature) yields artificially tighter constraints by a factor of 2.2 and 1.7 for $σ_8$ and $Ω_\mathrm{M}$, respectively.

astro-ph.CO↗