We present the second data release for the GaLactic and Extragalactic All-sky Murchison Widefield Array eXtended (GLEAM-X) survey. This data release is an area of 12 892-deg$^2$ around the South Galactic Pole region covering 20 h40 m$\leq$RA$\leq$6 h40 m, -90$^\circ$$\leq$Dec$\leq$+30$^\circ$. Observations were taken in 2020 using the Phase-II configuration of the Murchison Widefield Array (MWA) and covering a frequency range of 72–231 MHz with twenty frequency bands. We produce a wideband source finding mosaic over 170–231 MHz with a median root-mean-squared noise of $1.5^{+1.5}_{-0.5}$ mJy beam$^{-1}$. We present a catalogue of 624 866 components, including 562 302 components which are spectrally fit. This catalogue is 98% complete at 50 mJy, and a reliability of 98.7% at a 5 $\sigma$ level, consistent with expectations for this survey. The catalogue is made available via Vizier, and the PASA datastore and accompanying mosaics for this data release are made available via AAO Data Central and SkyView.

We present a detailed analysis of nearly two decades of optical/UV and X-ray data to study the multi-wavelength pre-explosion properties and post-explosion X-ray properties of nearby SN2023ixf located in M101. We find no evidence of precursor activity in the optical to UV down to a luminosity of $\lesssim$$1.0\times10^{5}\, \textrm{L}_{\odot}$, while X-ray observations covering nearly 18 yr prior to explosion show no evidence of luminous precursor X-ray emission down to an absorbed 0.3–10.0 keV X-ray luminosity of $\sim$$6\times10^{36}$ erg s$^{-1}$. Extensive Swift observations taken post-explosion did not detect soft X-ray emission from SN2023ixf within the first $\sim$3.3 days after first light, which suggests a mass-loss rate for the progenitor of $\lesssim$$5\times10^{-4}\,\textrm{M}_{\odot}$ yr$^{-1}$ or a radius of $\lesssim$$4\times10^{15}$ cm for the circumstellar material. Our analysis also suggests that if the progenitor underwent a mass-loss episode, this had to occur $>$0.5–1.5 yr prior to explosion, consistent with previous estimates. Swift detected soft X-rays from SN2023ixf $\sim$$4.25$ days after first light, and it rose to a peak luminosity of $\sim10^{39}$ erg s$^{-1}$ after 10 days and has maintained this luminosity for nearly 50 days post first light. This peak luminosity is lower than expected, given the evidence that SN2023ixf is interacting with dense material. However, this might be a natural consequence of an asymmetric circumstellar medium. X-ray spectra derived from merging all Swift observations over the first 50 days are best described by a two-component bremsstrahlung model consisting of a heavily absorbed and hotter component similar to that found using NuSTAR, and a less-absorbed, cooler component. We suggest that this soft component arises from cooling of the forward shock similar to that found in Type IIn SN2010jl.

Detection of the 21 cm signal from the Epoch of Reionisation (EoR) ($z \sim 6 - 10$) amidst the dominant foregrounds, which are 3–4 orders of magnitude greater than the weak cosmological signal, is a challenging task for the existing 21 cm experiments. The detection is further challenged by the large Field of View (FoV) of the instrument used for observation, as it becomes necessary to excise foregrounds present within the FoV to make a successful detection. In response to the challenges faced, in our previous work, we developed and installed a new instrument – the Central Redundant Array Mega-tile (CRAM) – and integrated it within the MWA Phase II configuration. It is a larger antenna tile configuration ($8\times 8$ dipoles) with a smaller FoV at every frequency under consideration and has multiple sidelobes of reduced response when compared with the existing Murchison Widefield Array (MWA) tiles. In this paper, we aim to demonstrate through power spectrum simulations that using the larger tile, such as the CRAM, can reduce the impact of bright radio foregrounds near the field edge. For the pedagogical approach aimed with this work, we developed a power spectrum pipeline to estimate the cylindrically averaged power spectrum. The power spectrum is estimated for MWA-MWA baselines and CRAM-MWA baselines using analytical beams, simulated diffuse sky maps and a semi-numerical 21 cm signal. Employing a drift scanning strategy, we estimate 1D and 2D power spectra for a series of two-minute observations spanning 24 hrs using the diffuse sky maps. Our simulations predict a power reduction at the edge of the EoR wedge. The reduction in foreground power is confirmed with the Fisher analysis of the expected signal-to-noise ratio (SNR) improvement, which reports a higher SNR with the power estimations from CRAM baselines when compared with the regular MWA baselines. The reduced power obtained with the CRAM baselines is consistent with the fact that the larger tile configuration has reduced the impact of foregrounds from near the horizon.

The operation of the ANU 2.3 m telescope transitioned from classically scheduled remote observing to fully autonomous queue scheduled observing in March 2023. The instrument currently supported is WiFeS, a visible-light low-resolution image-slicing integral field spectrograph with a $25^{\prime\prime}\,\times38^{\prime\prime}$ field of view (offering precision spectrophotometry free from aperture effects). It is highly suitable for rapid spectroscopic follow-up of astronomical transient events and regular cadence observations. The new control system implements flexible queue scheduling and supports rapid response override for target-of-opportunity observations. The ANU 2.3 m is the largest optical telescope to have been retro-fitted for autonomous operation to date, and it remains a national facility servicing a broad range of science cases. We present an overview of the automated control system and report on the first six months of continuous operation.

Recent discoveries of multiple long-period pulsars (periods ${\sim}10\,$s or larger) are starting to challenge the conventional notion that coherent radio emission cannot be produced by objects that are below the many theorised death lines. Many of the past pulsar surveys and software have been prone to selection effects that restricted their sensitivities towards long-period and sporadically emitting objects. Pulsar surveys using new-generation low-frequency facilities are starting to employ longer dwell times, which makes them significantly more sensitive in detecting long-period or nulling pulsars. There have also been software advancements to aid more sensitive searches towards long-period objects. Furthermore, recent discoveries suggest that nulling may be a key aspect of the long-period pulsar population. We simulate both long-period and nulling pulsar signals, using the Southern-sky MWA Rapid Two-meter (SMART) survey data as reference and explore the detection efficacy of popular search methods such as the fast Fourier transform (FFT), fast-folding algorithm (FFA) and single pulse search (SPS). For FFT-based search and SPS, we make use of the PRESTO implementation, and for FFA we use RIPTIDE. We find RIPTIDE’s FFA to be more sensitive; however, it is also the slowest algorithm. PRESTO’s FFT, although faster than others, also shows some unexpected inaccuracies in detection properties. SPS is highly sensitive to long-period and nulling signals, but only for pulses with high intrinsic signal-to-noise ratios. We use these findings to inform current and future pulsar surveys that aim to uncover a large population of long-period or nulling objects and comment on how to make optimal use of these methods in unison.

Fast Radio Bursts (FRBs) are millisecond dispersed radio pulses of predominately extra-galactic origin. Although originally discovered at GHz frequencies, most FRBs have been detected between 400 and 800 MHz. Nevertheless, only a handful of FRBs were detected at radio frequencies $\le$400 MHz. Searching for FRBs at low frequencies is computationally challenging due to increased dispersive delay that must be accounted for. Nevertheless, the wide field of view (FoV) of low-frequency telescopes – such as the the Murchison Widefield Array (MWA), and prototype stations of the low-frequency Square Kilometre Array (SKA-Low) – makes them promising instruments to open a low-frequency window on FRB event rates, and constrain FRB emission models. The standard approach, inherited from high-frequencies, is to form multiple tied-array beams to tessellate the entire FoV and perform the search on the resulting time series. This approach, however, may not be optimal for low-frequency interferometers due to their large FoVs and high spatial resolutions leading to a large number of beams. Consequently, there are regions of parameter space in terms of number of antennas and resolution elements (pixels) where interferometric imaging is computationally more efficient. Here we present a new high-time resolution imager BLINK implemented on modern graphical processing units (GPUs) and intended for radio astronomy data. The main goal for this imager is to become part of a fully GPU-accelerated FRB search pipeline. We describe the imager and present its verification on real and simulated data processed to form all-sky and widefield images from the MWA and prototype SKA-Low stations. We also present and compare benchmarks of the GPU and CPU code executed on laptops, desktop computers, and Australian supercomputers. The code is publicly available at https://github.com/PaCER-BLINK-Project/imager and can be applied to data from any radio telescope.

Traditional pulsar surveys have primarily employed time-domain periodicity searches. However, these methods are susceptible to effects like scattering, eclipses, and orbital motion. At lower radio frequencies ($\lesssim$300 MHz), factors such as dispersion measure and pulse broadening become more prominent, reducing the detection sensitivity. On the other hand, image domain searches for pulsars are not limited by these effects and can extend the parameter space to regions inaccessible to traditional search techniques. Therefore, we have developed a pipeline to form 1-second full Stokes images from offline correlated high time-resolution data from the Murchison Widefield Array (MWA). This led to the development of image-based methodologies to identify new pulsar candidates. In this paper, we applied these methodologies to perform a low-frequency image-based pulsar census of the galactic plane (12 MWA observations, covering $\sim$6 000 $\textrm{deg}^\textrm{2}$ sky). This work focuses on the detection of the known pulsar population which were present in the observed region of the sky using both image-based and beamformed methods. This resulted in the detection of 83 known pulsars, with 16 pulsars found only in Stokes I images but not in periodicity searches applied in beamformed data. Notably, for 14 pulsars these are the first reported low-frequency detections. This underscores the importance of image-based searches for pulsars that may be undetectable in time-series data, due to scattering and/or dispersive smearing at low frequencies. This highlights the importance of low-frequency flux density measurements in refining pulsar spectral models and investigating the spectral turnover of pulsars at low frequencies.

We explore the globular cluster population of NGC 1052-DF4, a dark matter deficient galaxy, using Bayesian inference to search for the presence of rotation. The existence of such a rotating component is relevant to the estimation of the mass of the galaxy, and therefore the question of whether NGC 1052-DF4 is truly deficient of dark matter, similar to NGC 1052-DF2, another galaxy in the same group. The rotational characteristics of seven globular clusters in NGC 1052-DF4 were investigated, finding that a non-rotating kinematic model has a higher Bayesian evidence than a rotating model, by a factor of approximately 2.5. In addition, we find that under the assumption of rotation, its amplitude must be small. This distinct lack of rotation strengthens the case that, based on its intrinsic velocity dispersion, NGC 1052-DF4 is a truly dark matter deficient galaxy.

We present radio observations of the galaxy cluster Abell S1136 at 888 MHz, using the Australian Square Kilometre Array Pathfinder radio telescope, as part of the Evolutionary Map of the Universe Early Science program. We compare these findings with data from the Murchison Widefield Array, XMM-Newton, the Wide-field Infrared Survey Explorer, the Digitised Sky Survey, and the Australia Telescope Compact Array. Our analysis shows the X-ray and radio emission in Abell S1136 are closely aligned and centered on the Brightest Cluster Galaxy, while the X-ray temperature profile shows a relaxed cluster with no evidence of a cool core. We find that the diffuse radio emission in the centre of the cluster shows more structure than seen in previous low-resolution observations of this source, which appeared formerly as an amorphous radio blob, similar in appearance to a radio halo; our observations show the diffuse emission in the Abell S1136 galaxy cluster contains three narrow filamentary structures visible at 888 MHz, between $\sim$80 and 140 kpc in length; however, the properties of the diffuse emission do not fully match that of a radio (mini-)halo or (fossil) tailed radio source.

A number of nearby dwarf galaxies have globular cluster (GC) candidates that require spectroscopic confirmation. Here, we present Keck telescope spectra for 15 known GCs and GC candidates that may be associated with a host dwarf galaxy and an additional 3 GCs in the halo of M31 that are candidates for accretion from a now-disrupted dwarf galaxy. We confirm six star clusters (of intermediate-to-old age) to be associated with NGC 247. The vast bulk of its GC system remains to be studied spectroscopically. We also confirm the GC candidates in F8D1 and DDO190, finding both to be young star clusters. The three M31 halo GCs all have radial velocities consistent with M31 and are old and very metal-poor. Their ages and metallicities are consistent with accretion from a low-mass satellite galaxy. Finally, three objects are found to be background galaxies – two are projected near NGC 247 and one (candidate GCC7) is near the IKN dwarf. The IKN dwarf thus has only five confirmed GCs but still a remarkable specific frequency of 124.

Observing stars and satellites in optical wavelengths during the day (optical daytime astronomy) has begun a resurgence of interest. The recent dramatic dimming event of Betelgeuse has spurred interest in continuous monitoring of the brightest variable stars, even when an object is only visible during the day due to their proximity to the Sun. In addition, an exponential increase in the number of satellites being launched into low Earth orbit in recent years has driven an interest in optical daytime astronomy for the detection and monitoring of satellites in space situational awareness (SSA) networks. In this paper we explore the use of the Huntsman Telescope as an optical daytime astronomy facility, by conducting an exploratory survey using a pathfinder instrument. We find that an absolute photometric accuracy between 1–10% can be achieved during the day, with a detection limit of V band 4.6 mag at midday in sloan $g,$ and $r,$ wavelengths. In addition, we characterise the daytime sky brightness, colour, and observing conditions in order to achieve the most reliable and highest signal-to-noise observations within the limitations of the bright sky background. We undertake a 7-month survey of the brightness of Betelgeuse during the day and demonstrate that our results are in agreement with measurements from other observatories. Finally we present our preliminary results that demonstrate obtaining absolute photometric measurements of the International Space Station during the day.

The baryon mass content (i.e. stellar and gas mass) of dark matter halos in the early Universe depends on both global factors – for example, ionising ultraviolet (UV) radiation background – and local factors – for example, star formation efficiency and assembly history. We use a lightweight semi-analytical model to investigate how both local and global factors impact the halo baryon mass content at redshifts of $z\geq 5$. Our model incorporates a time delay between when stars form and when they produce feedback of $0\leq t^d/\mathrm{Myr} \leq 30$, which can drive bursts of star formation, and a mass and redshift-dependent UV background, which captures the influence of cosmological reionisation on gas accretion onto halos. We use statistically representative halo assembly histories and assume that the cosmological gas accretion rate is proportional to the halo mass accretion rate. Delayed ($t^d$>0) feedback leads to oscillations in gas mass with cosmic time, behaviour that cannot be captured with instantaneous feedback ($t^d$=0). Highly efficient star formation drives stronger oscillations, while strong feedback impacts when oscillations occur; in contrast, inefficient star formation and weak feedback produce similar long-term behaviour to that observed in instantaneous feedback models. If the delayed feedback timescale is too long, a halo retains its gas reservoir but the feedback suppresses star formation. Our model predicts that lower mass systems (halo masses $m_\mathrm{h} \leq 10^7 \mathrm{M}_\odot$) at $z \leq 10$ should be strongly gas deficient ($m_\mathrm{g}\rightarrow 0$), whereas higher mass systems retain their gas reservoirs because they are sufficiently massive to continue accreting gas through cosmological reionisation. Interestingly, in higher mass halos, the median $m_\star/(m_\star+m_\mathrm{g}) \simeq 0.01-0.05$, but is a factor of 3–5 smaller when feedback is delayed. Our model does not include seed supermassive black hole feedback, which is necessary to explain massive quenched galaxies in the early Universe.

The nature of the first galaxies that reionised the universe during the Epoch of Reionisation (EoR) remains unclear. Attempts to directly determine spectral properties of these early galaxies are affected by both limited photometric constraints across the spectrum and by the opacity of the intergalactic medium to the Lyman Continuum (LyC) at high redshift. We approach this by analysing properties of analogous extreme emission line galaxies (EELGs, [OIII]+Hbeta EW $\gt 400$) at $2.5\lt z\lt 4$ from the ZFOURGE survey using the Multi-wavelength Analysis of Galaxy Physical Properties (MAGPHYS) SED fitting code. We compare these to galaxies at $z \gt 5.5$ observed with the James Webb Space Telesope with self-consistent spectral energy distribution fitting methodology. This work focuses on the comparison of their UV slopes (${\unicode{x03B2}}_P$), ionising photon production efficiencies $\xi_{ion}$, star formation rates and dust properties to determine the effectiveness of this analogue selection technique. We report the median ionising photon production efficiencies as log$_{10}(\xi_{ion}/(Hz\ {\rm erg}^{-1}))=$$25.14^{+0.06}_{-0.04}$, $25.16^{+0.06}_{-0.05}$, $25.16^{+0.04}_{-0.05}$, $25.18^{+0.06}_{-0.07}$ for our ZFOURGE control, ZFOURGE EELG, JADES, and CEERS samples, respectively. ZFOURGE EELGs are 0.57 dex lower in stellar mass and have half the dust extinction, compared to their ZFOURGE control counterparts. They also have a similar specific star formation rates and ${\unicode{x03B2}}_P$ to the $z\gt 5.5$ samples. We find that EELGs at low redshift ($2.5\lt z\lt 4$) are analogous to EoR galaxies in their dust attenuation and specific star formation rates. Their extensive photometric coverage and the accessibility of their LyC region opens pathways to infer stellar population properties in the EoR.

In radio astronomy, the science output of a telescope is often limited by computational resources. This is especially true for transient and technosignature surveys that need to search high-resolution data across a large parameter space. The tremendous data volumes produced by modern radio array telescopes exacerbate these processing challenges. Here, we introduce a ‘reduced-resolution’ beamforming approach to alleviate downstream processing requirements. Our approach, based on post-correlation beamforming, allows sensitivity to be traded against the number of beams needed to cover a given survey area. Using the MeerKAT and Murchison Widefield Array telescopes as examples, we show that survey speed can be vastly increased, and downstream signal processing requirements vastly decreased, if a moderate sacrifice to sensitivity is allowed. We show the reduced-resolution beamforming technique is intimately related to standard techniques used in synthesis imaging. We suggest that reduced-resolution beamforming should be considered to ease data processing challenges in current and planned searches; further, reduced-resolution beamforming may provide a path to computationally expensive search strategies previously considered infeasible.

We present the first of two papers dedicated to verifying the Australian Epoch of Reionisation pipeline (AusEoRPipe) through simulation. The AusEoRPipe aims to disentangle 21-cm radiation emitted by gas surrounding the very first stars from contaminating foreground astrophysical sources and has been in the development for close to a decade. In this paper, we build an accurate 21-cm sky model that can be used by the WODEN simulation software to create visibilities containing a predictable 21-cm signal. We verify that the power spectrum (PS) estimator CHIPS can recover this signal in the absence of foregrounds. We also investigate how measurements in Fourier-space are correlated and how their gridded density affects the PS. We measure and fit for this effect using Gaussian-noise simulations of the Murchison Widefield Array (MWA) phase I layout. We find a gridding density correction factor of 2.651 appropriate for integrations equal to or greater than 30 minutes of data, which contain observations with multiple primary beam pointings and LSTs. Paper II of this series will use the results of this paper to test the AusEoRPipe in the presence of foregrounds and instrumental effects.

Exploration of the 21cm signal during the Cosmic Dawn and the Epoch of Reionisation (EoR) can unravel the mysteries of the early Universe when the first stars and galaxies were born and ionised, respectively. However, the 21 cm signal is exceptionally weak, and thus, the detection amidst the bright foregrounds is extremely challenging. The Murchison Widefield Array (MWA) aims to measure the brightness temperature fluctuations of neutral hydrogen from the early Universe. The MWA telescope observes the radio sky with a large field of view (FoV) that causes the bright galaxies, especially near the horizon, to contaminate the measurements. These foregrounds contaminating the EoR datasets must be meticulously removed or treated to detect the signal successfully. The Central Redundant Array Mega-tile (CRAM) is a zenith-pointing new instrument, installed at the centre of the MWA Phase II southern hexagonal configuration, comprising of 64 dipoles in an $8 \times 8$ configuration with a FoV half the width of the MWA’s at every frequency under consideration. The primary objective of this new instrument is to mitigate the impact of bright radio sources near the field centre in accordance with the reduced primary beamshape and to reduce the contamination of foreground sources near the horizon with the reduced sidelobe response of the larger array configuration. In this paper, we introduce the new instrument to the community and present the system architecture and characteristics of the instrument. Using the first light observations, we determine the CRAM system temperature and system performance.

Since the turn of the century, astronomers have been exploiting the rich information afforded by combining stellar kinematic maps and imaging in an attempt to recover the intrinsic, three-dimensional (3D) shape of a galaxy. A common intrinsic shape recovery method relies on an expected monotonic relationship between the intrinsic misalignment of the kinematic and morphological axes and the triaxiality parameter. Recent studies have, however, cast doubt about underlying assumptions relating shape and intrinsic kinematic misalignment. In this work, we aim to recover the 3D shape of individual galaxies using their projected stellar kinematic and flux distributions using a supervised machine learning approach with mixture density network (MDN). Using a mock dataset of the EAGLE hydrodynamical cosmological simulation, we train the MDN model for a carefully selected set of common kinematic and photometric parameters. Compared to previous methods, we demonstrate potential improvements achieved with the MDN model to retrieve the 3D galaxy shape along with the uncertainties, especially for prolate and triaxial systems. We make specific recommendations for recovering galaxy intrinsic shapes relevant for current and future integral field spectroscopic galaxy surveys.

We present results regarding the longitudinal migrations of cool stellar spots that exhibit remarkable oscillations and explore their possible causes. We conducted analyses using high-quality data from nine target systems of various spectral types, spanning from F to M, which were observed by the Kepler Satellite. The systems in which the behaviour of the spots was examined are as follows: KIC 4357272, KIC 6025466, KIC 6058875, KIC 6962018, KIC 7798259, KIC 9210828, KIC 11706658, KIC 12599700, and KIC 8669092. Basic stellar parameters were calculated from light curve analysis using the PHOEBE V.0.32 software, and light curves were modelled to obtain sinusoidal variations occurring out-of-eclipses phases, induced by rotational modulation. Subsequently, we calculated the minimum times of the obtained sinusoidal variations using the Fourier transform. The distributions of ${\theta}_{\min}$ corresponding to these minimum times over time were computed using linear fits to determine the longitudinal migrations of the spotted areas. We then compared the longitudinal migration periods with the stellar parameters found in the literature. In addition, we also found a secondary variation in the spot migrations apart from the linear models. Our results revealed that the longitudinal migration periods vary in relation to the $B-V$ colour index of the stars.

Detecting and mitigating radio frequency interference (RFI) is critical for enabling and maximising the scientific output of radio telescopes. The emergence of machine learning (ML) methods capable of handling large datasets has led to their application in radio astronomy, particularly in RFI detection. Spiking neural networks (SNNs), inspired by biological systems, are well suited for processing spatio-temporal data. This study introduces the first exploratory application of SNNs to an astronomical data processing task, specifically RFI detection. We adapt the nearest latent neighbours (NLNs) algorithm and auto-encoder architecture proposed by previous authors to SNN execution by direct ANN2SNN conversion, enabling simplified downstream RFI detection by sampling the naturally varying latent space from the internal spiking neurons. Our subsequent evaluation aims to determine whether SNNs are viable for future RFI detection schemes. We evaluate detection performance with the simulated HERA telescope and hand-labelled LOFAR observation dataset the original authors provided. We additionally evaluate detection performance with a new MeerKAT-inspired simulation dataset that provides a technical challenge for machine-learnt RFI detection methods. This dataset focuses on satellite-based RFI, an increasingly important class of RFI and is an additional contribution. Our SNN approach remains competitive with the original NLN algorithm and AOFlagger in AUROC, AUPRC, and F1-scores for the HERA dataset but exhibits difficulty in the LOFAR and Tabascal datasets. However, our method maintains this accuracy while completely removing the compute and memory-intense latent sampling step found in NLN. This work demonstrates the viability of SNNs as a promising avenue for ML-based RFI detection in radio telescopes by establishing a minimal performance baseline on traditional and nascent satellite-based RFI sources and is the first work to our knowledge to apply SNNs in astronomy.