We present an analysis of high-resolution ($R \sim 48\,000$) spectroscopic and photometric data of RS Sgr, a short-period Algol-type binary system. For the first time, precise spectroscopic and absolute parameters of the system have been determined. The primary component is identified as a B3 main-sequence star with an effective temperature of 19 000 K, while the secondary is classified as an A0-type star with a temperature of 9 700 K. The secondary appears to have recently evolved off the main sequence and currently fills its Roche lobe, transferring material through the inner Lagrangian point (L$_1$) to the hotter primary component. The H$_\alpha$ emission and absorption features observed in the spectra are attributed to a combination of a low-density circumprimary disk, a gas stream originating from the secondary, and a hot spot formed at the impact site on the primary. The combined analysis of spectroscopic and photometric data yields a system distance of approximately 418 pc, which is consistent with the value derived from GAIA DR3 within the uncertainty limits.

We present the serendipitous radio-continuum discovery of a likely Galactic supernova remnant (SNR) G305.4–2.2. This object displays a remarkable circular symmetry in shape, making it one of the most circular Galactic SNRs known. Nicknamed Teleios due to its symmetry, it was detected in the new Australian Square Kilometre Array Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) radio–continuum images with an angular size of 1 320$^{\prime\prime}$$\times$1 260$^{\prime\prime}$ and PA = 0$^\circ$. While there is a hint of possible H$\alpha$ and gamma-ray emission, Teleios is exclusively seen at radio–continuum frequencies. Interestingly, Teleios is not only almost perfectly symmetric, but it also has one of the lowest surface brightnesses discovered among Galactic SNRs and a steep spectral index of $\alpha$=–0.6$\pm$0.3. Our best estimates from Hi studies and the $\Sigma$–D relation place Teleios as a type Ia SNR at a distance of either $\sim$2.2 kpc (near-side) or $\sim$7.7 kpc (far-side). This indicates two possible scenarios, either a young (under 1 000 yr) or a somewhat older SNR (over 10 000 yr). With a corresponding diameter of 14/48 pc, our evolutionary studies place Teleios at the either early or late Sedov phase, depending on the distance/diameter estimate. However, our modelling also predicts X-ray emission, which we do not see in the present generation of eROSITA images. We also explored a type Iax explosion scenario that would point to a much closer distance of $\lt$1 kpc and Teleios size of only $\sim$3.3 pc, which would be similar to the only known type Iax remnant SN1181. Unfortunately, all examined scenarios have their challenges, and no definitive Supernova (SN) origin type can be established at this stage. Remarkably, Teleios has retained its symmetrical shape as it aged even to such a diameter, suggesting expansion into a rarefied and isotropic ambient medium. The low radio surface brightness and the lack of pronounced polarisation can be explained by a high level of ambient rotation measure (RM), with the largest RM being observed at Teleios’s centre.

Accurate redshift measurements are essential for studying the evolution of quasi-stellar objects (QSOs) and their role in cosmic structure formation. While spectroscopic redshifts provide high precision, they are impractical for the vast number of sources detected in large-scale surveys. Photometric redshifts, derived from broadband fluxes, offer an efficient alternative, particularly when combined with machine learning techniques. In this work, we develop and evaluate a neural network model for predicting the redshifts of QSOs in the Dark Energy Spectroscopic Instrument (DESI) Early Data Release spectroscopic catalogue, using photometry from DESI, the Widefield Infrared Survey Explorer (WISE), and the Galactic Evolution Explorer (GALEX). We compare the performance of the neural network model against a k-Nearest Neighbours approach, these being the most accurate and least resource-intensive of the methods trialled herein, optimising model parameters and assessing accuracy with standard statistical metrics. Our results show that incorporating ultraviolet photometry from GALEX improves photometric redshift estimates, reducing scatter and catastrophic outliers compared to models trained only on near infrared and optical bands. The neural network achieves a correlation coefficient with spectroscopic redshift of $0.9187$ with normalised median absolute deviation of $0.197$, representing a significant improvement over other methods. Our work combines DESI, WISE, and GALEX measurements, providing robust predictions which address the difficulties in predicting photometric redshift of QSOs over a large redshift range.

The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, largely through increasing the number of stations in the array and the frequency span sampled. The two primary problems encountered when processing the resultant avalanche of data are the need for abundant storage and the constraints imposed by I/O, as I/O bandwidths drop significantly on cold storage. An example of this is the data deluge expected from the SKA Telescopes of more than 60 PB per day, all to be stored on the buffer filesystem. While compressing the data is an obvious solution, the impacts on the final data products are hard to predict. In this paper, we chose an error-controlled compressor – MGARD – and applied it to simulated SKA-Mid and real pathfinder visibility data, in noise-free and noise-dominated regimes. As the data have an implicit error level in the system temperature, using an error bound in compression provides a natural metric for compression. MGARD ensures the compression incurred errors adhere to the user-prescribed tolerance. To measure the degradation of images reconstructed using the lossy compressed data, we proposed a list of diagnostic measures, exploring the trade-off between these error bounds and the corresponding compression ratios, as well as the impact on science quality derived from the lossy compressed data products through a series of experiments. We studied the global and local impacts on the output images for continuum and spectral line examples. We found relative error bounds of as much as 10%, which provide compression ratios of about 20, have a limited impact on the continuum imaging as the increased noise is less than the image RMS, whereas a 1% error bound (compression ratio of 8) introduces an increase in noise of about an order of magnitude less than the image RMS. For extremely sensitive observations and for very precious data, we would recommend a $0.1\%$ error bound with compression ratios of about 4. These have noise impacts two orders of magnitude less than the image RMS levels. At these levels, the limits are due to instabilities in the deconvolution methods. We compared the results to the alternative compression tool DYSCO, in both the impacts on the images and in the relative flexibility. MGARD provides better compression for similar error bounds and has a host of potentially powerful additional features.

We report the detection of a potential quasi-periodic signal with a period of $\sim$2 yr in the blazar ON 246, based on Fermi-LAT ($\gamma$-rays) and ASAS-SN (optical) observations spanning 11.5 yr (MJD 55932–60081). We applied various techniques to investigate periodic signatures in the light curves, including the Lomb-Scargle periodogram (LSP), weighted wavelet Z-transform (WWZ), and REDFIT. The significance of the signals detected in LSP and WWZ was assessed using two independent approaches: Monte Carlo simulations and red noise modelling. Our analysis revealed a dominant peak in the $\gamma$-ray and optical light curves, with a significance level exceeding 3$\sigma$ in both LSP and WWZ, consistently persisting throughout the observation period. Additionally, the REDFIT analysis confirmed the presence of a quasi-periodic signal at $\sim$0.00134 day$^{-1}$ with a 99$\%$ confidence threshold. To explain the observed quasi-periodic variations in $\gamma$-ray and optical emissions, we explored various potential physical mechanisms. Our analysis suggests that the detected periodicity could originate from a supermassive binary black hole (SMBBH) system or the jet-induced orbital motion within such a system. Based on variability characteristics, we estimated the black hole mass of ON 246. The study suggests that the mass lies within the range of approximately $(0.142 - 8.22) \times 10^9$ M$_{\odot}$.

Recently, there have been discussions about the shape of the heliopause. Some scientists question the classical form, which is close to a paraboloid. They suggest that the heliopause may have a two-jet collimated shape. While we disagree with this view of the heliopause shape, it seems likely that for stars with stronger stellar magnetic fields and those that are at rest or moving slowly through the interstellar medium, the astropause will have a two-jet collimated shape. This paper raises the question of the stability of the two-jet collimated astrosphere. Recent studies have noted the emergence of instability in the heliosheath near the axis of the heliospheric jets, linking this to the action of neutral hydrogen atoms. We note in this paper that astrospheric jets can become unstable in the presence of strong magnetic fields, even without the influence of atoms, which is unexpected. Furthermore, due to a feedback mechanism, astrospheric jets undergo self-oscillation. We investigated the development of this instability, the nature of the feedback mechanism, and the period of self-oscillation for different system parameters. Our findings provide valuable insights into the behaviour of these unique plasma structures, and they are another step towards studying the stability of two-jet collimated astrospheres.