arXiv subjects

Nadeem Oozeer

Publications and source records attributed to Nadeem Oozeer.

15 recordsLinked to original sources

arXiv2026

TABASCAL: Removing multi-satellite interference from radio interferometry observations

In the first trajectory-based radio frequency interference (RFI) subtraction and calibration (TABASCAL) paper, we showed how to calibrate radio interferometers in the presence of RFI sources by simultaneously isolating the trajectories and signals of the RFI sources. In this paper, we show that we can accurately remove RFI (i.e. recover the astronomical signal) from simulated MeerKAT radio interferometry target data. We are able to do so for a single frequency channel, corrupted by up to nine simultaneous satellites, with average RFI amplitudes varying from weak to very strong (1-1000 Jy). Additionally, TABASCAL also manages to leverage the signal-to-noise ratio (S/N) of the RFI to phase-calibrate the astronomical signal. TABASCAL, effectively performs a suitably phased up fringe filter for each RFI source, which essentially allows for an ideal removal of RFI across all RFI strengths. As a result, TABASCAL is able to reach image noises equivalent to the uncorrupted, no-RFI, case. For larger RFI amplitudes, the resulting image noise is 10x - 100x smaller than those from traditional RFI flagging methods such as AOFLAGGER. As a specific application, we show that point-source science with TABASCAL almost matches the no-RFI case with near perfect completeness for all RFI amplitudes. In contrast, the completeness of AOFLAGGER and idealised $3σ$ flagging drops below 40% for strong RFI amplitudes, where recovered flux errors are approximately 10x - 100x worse than those from TABASCAL. Finally, we note that TABASCAL works for astronomical sources with both static and varying fluxes.

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arXiv2025

HI gas in the rejuvenated radio galaxy PKS 2014-55

We present new high-spectral-resolution MeerKAT observations of $\mathrm{HI}$ absorption against the central region of the restarted, giant, X-shaped radio galaxy PKS2014-55, which exhibits morphological evidence of three distinct cycles of activity. We report a wide component $(\mathrm{FWHM}=38 \pm 7~\mathrm{kms^{-1}})$ redshifted to $96 \pm 50~\mathrm{kms^{-1}}$, a deep narrow detection $(\mathrm{FWHM}=19 \pm 6~\mathrm{kms^{-1}})$ redshifted to $160 \pm 40~\mathrm{kms^{-1}}$, and a shallow component $(\mathrm{FWHM}=22 \pm 6~\mathrm{kms^{-1}})$ redshifted to $240 \pm 40~\mathrm{kms^{-1}}$. One of the three components exceeds the typical rotational velocity of $100~\mathrm{kms^{-1}}$, suggesting complex kinematics of the inflowing gas. These $\mathrm{HI}$ observations support the correlation between the occurrence of $\mathrm{HI}$ absorption and the rejuvenation of radio activity.

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arXiv2025

Mining the time axis with TRON. I. Millisecond pulsars in Omega Centauri, Terzan 5 and 47 Tucanae detected through MeerKAT interferometric imaging

Medium-timescale (minutes to hours) radio transients are a relatively unexplored population. The wide field-of-view and high instantaneous sensitivity of instruments such as MeerKAT provides an opportunity to probe this class of sources, using image-plane detection techniques. We aim to systematically mine archival synthesis imaging data in order to search for medium-timescale transients and variables that are not detected by conventional long-track image synthesis techniques. We deploy a prototype blind transient and variable search pipeline named TRON. This processes calibrated visibility data, constructs high-time cadence images, performs a search for variability on multiple timescales, and extracts lightcurves for detected sources. As proof of concept, we apply it to three MeerKAT observations of globular clusters, known to host transient or variable sources. We detect a previously known eclipsing MSP suspected to be a `black widow' system, in the globular cluster Omega Centauri, with a light curve confirming the eclipsing nature of the emission. We detect a previously known `red back' eclipsing MSP in the globular cluster Terzan 5. Using observations of the globular cluster 47 Tucanae, we detect two known millisecond pulsars (MSPs), and one previously reported MSP candidate, with hints of eclipsing behaviour.

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arXiv2025

Mining the time axis with TRON. II. MeerKAT detects a stellar radio flare from a distant RS CVn candidate

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arXiv2023

Trajectory Based RFI Subtraction and Calibration for Radio Interferometry

Radio interferometry calibration and Radio Frequency Interference (RFI) removal are usually done separately. Here we show that jointly modelling the antenna gains and RFI has significant benefits when the RFI follows precise trajectories, such as for satellites. One surprising benefit is improved calibration solutions, by leveraging the RFI signal itself. We present tabascal (TrAjectory BAsed RFI Subtraction and CALibration), a new algorithm that jointly models the RFI and calibration parameters in visibilities. We test tabascal on simulated MeerKAT calibration observations contaminated by satellite-based RFI. We obtain gain estimates that are both unbiased and up to an order of magnitude better constrained compared to uncontaminated data. When combined with an ad hoc RFI subtraction scheme, tabascal solutions can be further applied to an adjacent target observation: 5 minutes of calibration data results in an image with about a third the noise achieved when using flagging alone. The recovered flux distribution of RFI subtracted data was on par with uncontaminated data. In contrast, RFI flagging alone resulted in a higher detection threshold and consistent underestimation of source fluxes. For a mean RFI amplitude of 17 Jy, using RFI subtraction leads to less than 1% loss of data compared to 75% data loss from an ideal $3σ$ flagging algorithm, a very significant increase in data available for science analysis. Although we have examined the case of satellite RFI, tabascal should work for any RFI moving on parameterizable trajectories, relative to the phase centre, such as planes and/or objects fixed to the ground.

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arXiv2023

The Impact of GSM towers in Radio Astronomy

Radio astronomy is a specialised area of astronomy that examines the radio emissions from astronomical bodies within the electromagnetic spectrum's radio range. As radio telescopes have become increasingly sensitive due to technological advancements, radio astronomers face the significant challenge of reducing the impact of human-generated radio interference. Our research delved into the impact of Global System for Mobile Communication (GSM) signals on radio astronomy data, utilising a multidimensional framework approach with a probabilistic basis. We discovered a link between the location of cell towers in the nearby towns surrounding MeerKAT and a high probability of Radio Frequency Interference (RFI). However, we found no statistically significant association between the time of day and RFI occurrence at the 68% confidence level.

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arXiv2022

Nature and Evolution of UHF and L-band Radio Frequency Interference at the MeerKAT Radio Telescope

Radio Frequency Interference (RFI) is unwanted noise that swamps the desired astronomical signal. Radio astronomers have always had to deal with RFI detection and excision around telescope sites, but little has been done to understand the full scope, nature and evolution of RFI in a unified way. We undertake this for the MeerKAT array using a probabilistic multidimensional framework approach focussing on UHF-band and L-band data. In the UHF- band, RFI is dominated by the allocated Global System for Mobile (GSM) Communications, flight Distance Measuring Equipment (DME), and UHF-TV bands. The L-band suffers from known RFI sources such as DMEs, GSM, and the Global Positioning System (GPS) satellites. In the "clean" MeerKAT band, we noticed the RFI occupancy changing with time and direction for both the L-band and UHF band. For example, we saw a significant increase (300% increase) in the fraction of L-band flagged data in November 2018 compared to June 2018. This increase seems to correlate with construction activity on site. In the UHF-band, we found that the early morning is least impacted by RFI and other outliers. We also found a dramatic decrease in DME RFI during the hard lockdown due to the COVID-19 pandemic. The work presented here allows us to characterise the evolution of RFI at the MeerKAT site. Any observatory can adopt it to understand the behaviour of RFI within its surroundings.

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arXiv2021

Searching for high-z radio galaxies with the MGCLS

We present results from a search for high-redshift radio galaxy (H$z$RG) candidates using 1.28 GHz data in the Abell 2751 field drawn from the MeerKAT Galaxy Cluster Legacy Survey (MGCLS). We use the H$z$RG criteria that a radio source is undetected in all-sky optical and infrared catalogues, and has a very steep radio spectrum. We cross-match the radio catalogue against multi-wavelength galaxy catalogues from DECaLS and AllWISE. For those radio sources with no multi-wavelength counterpart, we further implement a radio spectral index criterium of $α< -1$, using in-band spectral index measurements from the wide-band MeerKAT data. Using a 5$σ$ signal-to-noise cut on the radio flux densities, we find a total of 274 HzRG candidates: 179 ultra-steep spectrum sources, and 95 potential candidates which cannot be ruled out as they have no spectral information available. The spectral index assignments in this work are complete above a flux density of 0.3 mJy, at least an order of magnitude lower than existing studies in this frequency range or when extrapolating from lower frequency limits. Our faintest HzRG candidates with and without an in-band spectral index measurement have a 1.28\,GHz flux density of 57 $\pm$ 8 $μ$Jy and 68 $\pm$ 13 $μ$Jy, respectively. Although our study is not complete down to these flux densities, our results indicate that the sensitivity and bandwidth of the MGCLS data makes them a powerful radio resource to search for H$z$RG candidates in the Southern sky, with 20 of the MGCLS pointings having similar image quality as the Abell~2751 field and full coverage in both DECaLS and AllWISE. Data at additional radio frequencies will be needed for the faintest source populations, which could be provided in the near future by the MeerKAT UHF band (580 -- 1015 MHz) at a similar resolution ($\sim$ 8-10 arcsec).

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arXiv2021

A Multiwavelength Dynamical State Analysis of ACT-CL J0019.6+0336

In our study, we show a multiwavelength view of ACT-CL J0019.6+0336 (which hosts a radio halo), to investigate the cluster dynamics, morphology, and ICM. We use a combination of XMM-Newton images, Dark Energy Survey (DES) imaging and photometry, SDSS spectroscopic information, and 1.16 GHz MeerKAT data to study the cluster properties. Various X-ray and optical morphology parameters are calculated to investigate the level of disturbance. We find disturbances in two X-ray parameters and the optical density map shows elongated and axisymmetric structures with the main cluster component southeast of the cluster centre and another component northwest of the cluster centre. We also find a BCG offset of $\sim$950 km/s from the mean velocity of the cluster, and a discrepancy between the SZ mass, X-ray mass, and dynamical mass ($M_{X,500}$ and $M_{SZ,500}$ lies >3 $σ$ away from $M_{\rm{dyn},500}$), showing that J0019 is a merging cluster and probably in a post-merging phase.

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arXiv2020

Deep Learning improves identification of Radio Frequency Interference

Flagging of Radio Frequency Interference (RFI) is an increasingly important challenge in radio astronomy. We present R-Net, a deep convolutional ResNet architecture that significantly outperforms existing algorithms -- including the default MeerKAT RFI flagger, and deep U-Net architectures -- across all metrics including AUC, F1-score and MCC. We demonstrate the robustness of this improvement on both single dish and interferometric simulations and, using transfer learning, on real data. Our R-Net model's precision is approximately $90\%$ better than the current MeerKAT flagger at $80\%$ recall and has a 35\% higher F1-score with no additional performance cost. We further highlight the effectiveness of transfer learning from a model initially trained on simulated MeerKAT data and fine-tuned on real, human-flagged, KAT-7 data. Despite the wide differences in the nature of the two telescope arrays, the model achieves an AUC of 0.91, while the best model without transfer learning only reaches an AUC of 0.67. We consider the use of phase information in our models but find that without calibration the phase adds almost no extra information relative to amplitude data only. Our results strongly suggest that deep learning on simulations, boosted by transfer learning on real data, will likely play a key role in the future of RFI flagging of radio astronomy data.

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arXiv2020

Multidimensional RFI Framework for Characterising Radio Astronomy Observatories

Radio Frequency Interference (RFI) has historically plagued radio astronomy, worsening with the rapid spread of electronics and increasing telescope sensitivity. We present a multi-dimensional probabilistic framework for characterising the RFI environment around a radio astronomy site that uses automatically flagged data from the array itself. We illustrate the framework using about 1500 hours of commissioning data from the MeerKAT radio telescope; producing a 6-dimensional array that yields both average RFI occupancy as well as confidence intervals around the mean as a function of key variables (frequency, direction, baseline, time). Our results provide the first detailed view of the MeerKAT RFI environment at high sensitivity as a function of direction, frequency, time of day and baseline. They allow us to track the historical evolution of the RFI and to quantify fluctuations which can be used for alerting on new RFI. As expected we find the major RFI contributors for MeerKAT site are from Global Positioning System (GPS) satellites, flight Distance Measurement Equipment (DME) and the Global System for Mobile (GSM) Communications. Beyond characterising RFI environments our approach allows observers access to the prior probability of RFI in any combination of tracked variables, allowing for more efficient observation planning and data excision.

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arXiv2017

MERGHERS: An SZ-selected cluster survey with MeerKAT

The MeerKAT telescope will be one of the most sensitive radio arrays in the pre-SKA era. Here we discuss a low-frequency SZ-selected cluster survey with MeerKAT, the MeerKAT Extended Relics, Giant Halos, and Extragalactic Radio Sources (MERGHERS) survey. The primary goal of this survey is to detect faint signatures of diffuse cluster emission, specifically radio halos and relics. SZ-selected cluster samples offer a homogeneous, mass-limited set of targets out to higher redshift than X-ray samples. MeerKAT is sensitive enough to detect diffuse radio emission at the faint levels expected in low-mass and high-redshift clusters, thereby enabling radio halo and relic formation theories to be tested with a larger statistical sample over a significantly expanded phase space. Complementary multiwavelength follow-up observations will provide a more complete picture of any clusters found to host diffuse emission, thereby enhancing the scientific return of the MERGHERS survey.

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arXiv2015

Bayesian Inference for Radio Observations - Going beyond deconvolution

Radio interferometers suffer from the problem of missing information in their data, due to the gaps between the antennas. This results in artifacts, such as bright rings around sources, in the images obtained. Multiple deconvolution algorithms have been proposed to solve this problem and produce cleaner radio images. However, these algorithms are unable to correctly estimate uncertainties in derived scientific parameters or to always include the effects of instrumental errors. We propose an alternative technique called Bayesian Inference for Radio Observations (BIRO) which uses a Bayesian statistical framework to determine the scientific parameters and instrumental errors simultaneously directly from the raw data, without making an image. We use a simple simulation of Westerbork Synthesis Radio Telescope data including pointing errors and beam parameters as instrumental effects, to demonstrate the use of BIRO.

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arXiv2015

Bayesian Inference for Radio Observations

New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inadequate uncertainty estimates and biased results because any correlations between parameters are ignored. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realization of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. This enables it to derive both correlations and accurate uncertainties, making use of the flexible software MEQTREES to model the sky and telescope simultaneously. We demonstrate BIRO with two simulated sets of Westerbork Synthesis Radio Telescope data sets. In the first, we perform joint estimates of 103 scientific (flux densities of sources) and instrumental (pointing errors, beamwidth and noise) parameters. In the second example, we perform source separation with BIRO. Using the Bayesian evidence, we can accurately select between a single point source, two point sources and an extended Gaussian source, allowing for 'super-resolution' on scales much smaller than the synthesized beam.

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arXiv2015

KAT-7 detection of radio halo emission in the Triangulum Australis galaxy cluster

We report the presence of high significance diffuse radio emission from the Triangulum Australis cluster using observations made with the KAT-7 telescope and propose that this emission is a giant radio halo. We compare the radio power from this proposed halo with X-ray and SZ measurements and demonstrate that it is consistent with the established scaling relations for cluster haloes. By combining the X-ray and SZ data we calculate the ratio of non-thermal to thermal electron pressure within Triangulum Australis to be $X=0.658\pm0.054$. We use this ratio to constrain the maximum magnetic field strength within the halo region to be $B_{\rm max, halo} = 33.08\,μ$G and compare this with the minimum field strength from equipartition of $B_{\rm min, halo} = 0.77(1+k)^{2/7}\,μ$G to place limits on the range of allowed magnetic field strength within this cluster. We compare these values to those for more well-studied systems and discuss these results in the context of equipartition of non-thermal energy densities within clusters of galaxies.

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