We present multi-wavelength observations of the nearby spiral galaxy NGC5938 (Araish) to investigate the origin of its radio emission, specifically the contribution from active galactic nucleus (AGN) activity and star formation. Using Evolutionary Map of the Universe (EMU) data, we detect extended radio emission extending outwards to the galactic axis, with a steep non-thermal spectral index (α = −1.2 ± 0.2) indicative of synchrotron radiation from an AGN jet. The jet has a physical extent of ≈ 8.2 kpc (angular length of 64″). Multi-wavelength data from The Dark Energy Camera Plane Survey 2 (DECaPS2),Wide-field Infrared Survey Explorer (WISE), and extended Roentgen Survey with an Imaging Telescope Array (eROSITA) provide further support for this interpretation. The colour-colour diagram presenting WISE infrared observations suggests the presence of dust and young stars that trace the galaxy’s disk structure. Our analysis reveals a radio jet, alongside star formation traced by infrared emission, demonstrating the complex interplay of AGN activity and star formation in this well-resolved galaxy. Intriguingly, the spatial relationship reveals the brighter X-ray emission to be largely adjacent to and enveloping the extended radio emission. This suggests that the radio jet, while extending at a significant angle to the galactic disk, is confined by the larger X-ray gas/halo, similar to other systems (i.e., ESO 295–IG022, Centaurus A) and may indicate jet collimation and channelling effects.

This paper presents the effects of radio frequency interference (RFI) mitigation on a radio telescope’s sensitivity and beam pattern. It specifically explores the impact of subspace-projection mitigation on the phased array feed (PAF) beams of the Australian SKA Pathfinder (ASKAP) telescope. The goal is to demonstrate ASKAP’s ability to make science observations during active RFI mitigation. The target interfering signal is a self-generated clock signal from the digital receivers of ASKAP’s PAF. This signal is stationary, so we apply the mitigation projection to the beamformer weights at the beginning of the observation and hold them fixed. We suppressed the unwanted narrowband signal by 31 dB, to the noise floor of an 880 s integration on one antenna, with a typical degradation in sensitivity of just 1.5%. Sensitivity degradation over the whole 36 antenna array of 3.1% was then measured via interferometric assessment of system equivalent flux density (SEFD). These measurements are in line with theoretical calculation of noise increase using the correlation of the beam weights and RFI spatial signature. Further, degradation to the main beam’s gain is $\pm$ 0.4% on average at the half-power point, with no significant change to the gain in the first sidelobe and no variation during extended observations; also consistent with our modelling. In summary, we present the first demonstration of mitigation via spatial nulling with PAFs on a large aperture synthesis array telescope and assess impact on sensitivity and beam shape via SEFD and holography measurements. The mitigation introduces smaller changes to sensitivity than intrinsic sensitivity differences between beams, does not preclude high dynamic range imaging and, in continuum 1 MHz mode, recovers an otherwise corrupted holography beam map and usable astronomical source correlations in the RFI-affected channel.

We present an initial analysis of Radio Frequency Interference (RFI) flagging statistics from archived Australian SKA Pathfinder (ASKAP) observations for the ‘Survey and Monitoring of ASKAP’s RFI environment and Trends’ (SMART) project. SMART is a two-part observatoryled project combining analysis of archived observations with a dedicated, comprehensive RFI survey. The survey component covers ASKAP’s full 700–1 800 MHz frequency range, including bands not typically used due to severe RFI. Observations are underway to capture a detailed snapshot of the ASKAP RFI environment over representative 24 h periods. In addition to this dedicated survey, we routinely archive and analyse flagging statistics for all scientific observations to monitor the observatory’s RFI environment in near real-time. We use the telescope itself as a very sensitive RFI monitor and directly assess the fraction of scientific observations impacted by RFI. To this end, flag tables are now automatically ingested and aggregated as part of routine ASKAP operations for all science observations, as a function of frequency and time. The data presented in this paper come from processing all archived data for several ASKAP Survey Science Projects (SSPs). We found that the average amount of flagging due to RFI across the routinely used ‘clean’ continuum science bands is 3%. The ‘clean’ mid band from 1 293 to 1 437 MHz (excluding the 144 MHz below 1293 MHz impacted by radionavigation-satellites which is discarded before processing) is the least affected by RFI, followed by the ‘clean’ low band from 742 to 1 085 MHz. ASKAP SSPs lose most of their data to the mobile service in the low band, aeronautical service in the mid band and satellite navigation service in the 1 510–1 797 MHz high band. We also show that for some of these services, the percentage of discarded data has been increasing year-on-year. SMART provides a unique opportunity to study ASKAP’s changing RFI environment, including understanding and updating the default flagging behaviour, inferring the suitability of and calibrating RFI monitoring equipment, monitoring spectrum management compliance in the Australian Radio Quiet Zone – Western Australia (ARQZWA), and informing the implementation of a suite of RFI mitigation techniques.

The VAST survey is a wide-field survey that observes with unprecedented instrument sensitivity (0.5 mJy or lower) and repeat cadence (a goal of 5 seconds) that will enable novel scientific discoveries related to known and unknown classes of radio transients and variables. Given the unprecedented observing characteristics of VAST, it is important to estimate source classification performance, and determine best practices prior to the launch of ASKAP's BETA in 2012. The goal of this study is to identify light-curve characterization and classification algorithms that are best suited for archival VAST light-curve classification. We perform our experiments on light-curve simulations of eight source types and achieve best-case performance of approximately 90% accuracy. We note that classification performance is most influenced by light-curve characterization rather than classifier algorithm.