We present a new radio continuum study of the Large Magellanic Cloud supernova remnant (SNR) MC SNR J0519–6902. With a diameter of $\sim$8 pc, this SNR shows a radio ring-like morphology with three bright regions towards the north, east, and south. Its linear polarisation is prominent with average values of $5\pm1$% and $6\pm1$% at 5 500 and 9 000 MHz, and we find a spectral index of ${-0.62\pm0.02}$, typical of a young SNR. The average rotation measure is estimated at ${-124\pm83}$ rad m$^{-2}$ and the magnetic field strength at ${\sim11}\,\mu$G. We also estimate an equipartition magnetic field of ${72\pm 5}\,\mu$G and minimum explosion energy of E$_\textrm{ min}$ = 2.6$\times10^{48}$ erg. Finally, we identified an H i cloud that may be associated with MC SNR J0519–6902, located in the southeastern part of the remnant, along with a potential wind-bubble cavity.

We undertake a comprehensive investigation into the distribution of in situ stars within Milky Way-like galaxies, leveraging TNG50 simulations and comparing their predictions with data from the H3 survey. Our analysis reveals that 28% of galaxies demonstrate reasonable agreement with H3, while only 12% exhibit excellent alignment in their profiles, regardless of the specific spatial cut employed to define in situ stars. To uncover the underlying factors contributing to deviations between TNG50 and H3 distributions, we scrutinise correlation coefficients among internal drivers (e.g. virial radius, star formation rate [SFR]) and merger-related parameters (such as the effective mass-ratio, mean distance, average redshift, total number of mergers, average spin-ratio, and maximum spin alignment between merging galaxies). Notably, we identify significant correlations between deviations from observational data and key parameters such as the median slope of virial radius, mean SFR values, and the rate of SFR change across different redshift scans. Furthermore, positive correlations emerge between deviations from observational data and parameters related to galaxy mergers. We validate these correlations using the Random Forest Regression method. Our findings underscore the invaluable insights provided by the H3 survey in unravelling the cosmic history of galaxies akin to the Milky Way, thereby advancing our understanding of galactic evolution and shedding light on the formation and evolution of Milky Way-like galaxies in cosmological simulations.

The abundance of dust within galaxies directly influences their evolution. Contemporary models attempt to match this abundance by simulating the processes of dust creation, growth, and destruction. While these models are accurate, they require refinement, especially at earlier epochs. This study aims to compare simulated and observed datasets and identify discrepancies between the two, providing a basis for future improvements. We utilise simulation data from the Simba cosmological simulation suite and observed data from the Galaxy and Mass Assembly (GAMA), a subset of the Cosmic Evolution Survey (G10-COSMOS), and the Hubble Space Telescope (3D-HST). We selected galaxies in the observed and simulated data in a stellar mass range of ($10^{8.59} \lt \text{M}_\odot \lt 10^{11.5}$) and at redshift bins centering around $z = 0.0$, $z = 0.1$, $z = 0.5$, $z = 1.0$, and $z = 1.5$ in a homogeneous dust mass range ($10^{6} \lt \text{M}_D [\text{ M}_\odot] \lt 10^{9}$). Our results show notable deviations between Simba and observed data for dust-poor and rich galaxies, with strong indications that differences in galaxy populations and Simba limitations are the underlying cause rather than the dust physics implemented in Simba itself.

The kinetic stability of collisionless, sloshing beam-ion ($45^\circ$ pitch angle) plasma is studied in a three-dimensional (3-D) simple magnetic mirror, mimicking the Wisconsin high-temperature superconductor axisymmetric mirror experiment. The collisional Fokker–Planck code CQL3D-m provides a slowing-down beam-ion distribution to initialize the kinetic-ion/fluid-electron code Hybrid-VPIC, which then simulates free plasma decay without external heating or fuelling. Over $1$–$10\;\mathrm{\unicode{x03BC} s}$, drift-cyclotron loss-cone (DCLC) modes grow and saturate in amplitude. The DCLC scatters ions to a marginally stable distribution with gas-dynamic rather than classical-mirror confinement. Sloshing ions can trap cool (low-energy) ions in an electrostatic potential well to stabilize DCLC, but DCLC itself does not scatter sloshing beam-ions into the said well. Instead, cool ions must come from external sources such as charge-exchange collisions with a low-density neutral population. Manually adding cool $\mathord {\sim } 1\;\mathrm{keV}$ ions improves beam-ion confinement several-fold in Hybrid-VPIC simulations, which qualitatively corroborates prior measurements from real mirror devices with sloshing ions.

The GLEAM 4-Jy (G4Jy) Sample is a thorough compilation of the ‘brightest’ radio sources in the southern sky (Declination $ \lt 30^{\circ}$), as measured at 151 MHz ($S_{\mathrm{151\,MHz}} \gt 4.0$ Jy) with the Murchison Widefield Array (MWA), through the GaLactic and Extragalactic All-sky MWA (GLEAM) Survey. In addition to flux-density measurements, the G4Jy catalogue (https://github.com/svw26/G4Jy.) provides host-galaxy identifications (through careful visual-inspection) and four sets of spectral indices. Despite their brightness in the radio, many of these sources are poorly studied, with the vast majority lacking a spectroscopic redshift in published work. This is crucial for studying the intrinsic properties of the sources, and so we conduct a multi-semester observing campaign on the Southern African Large Telescope (SALT), with optical spectroscopy enabling us to provide new redshifts to the astronomical community. Initial results show that not all of the host galaxies exhibit emission-line spectra in the optical ($\sim$4 500–7 500Å), which illustrates the importance of radio-frequency selection (rather than optical selection) for creating an unbiased sample of active galactic nuclei. By combining SALT redshifts with those from the 6-degree Field Galaxy Survey (6dFGS) and the Sloan Digital Sky Survey (SDSS), we calculate radio luminosities and linear sizes for 299 G4Jy sources (which includes one newly-discovered giant radio-galaxy, G4Jy 604). Furthermore, with the highest redshift acquired (so far) being $z \sim 2.2$ from SDSS, we look forward to evolution studies of this complete sample, as well as breaking degeneracies in radio properties with respect to, for example, the galaxy environment.

This study characterises the radio luminosity functions (RLFs) for star forming galaxies (SFGs) and active galactic nuclei (AGN) using statistical redshift estimation in the absence of comprehensive spectroscopic data. Sensitive radio surveys over large areas detect many sources with faint optical and infrared counterparts, for which redshifts and spectra are unavailable. This challenges our attempt to understand the population of radio sources. Statistical tools are often used to model parameters (such as redshift) as an alternative to observational data. Using the data from GAMA G23 and EMU early science observations, we explore simple statistical techniques to estimate the redshifts in order to measure the RLFs of the G23 radio sources as a whole and for SFGs and AGN separately. Redshifts and AGN/SFG classifications are assigned statistically for those radio sources without spectroscopic data. The calculated RLFs are compared with existing studies, and the results suggest that the RLFs match remarkably well for low redshift galaxies with an optical counterpart. We use a more realistic high redshift distribution to model the redshifts of (most likely) high redshift radio sources and find that the LFs from our approach match well with measured LFs. We also look at strategies to compare the RLFs of radio sources without an optical counterpart to existing studies.

One of the critical challenges in future high-current tokamaks is the avoidance of runaway electrons during disruptions. Here, we investigate disruptions mitigated with combined deuterium and noble gas injection in SPARC. We use multi-objective Bayesian optimisation of the densities of the injected material, taking into account limits on the maximum runaway current, the transported fraction of the heat loss and the current quench time. The simulations are conducted using the numerical framework Dream (disruption runaway electron analysis model). We show that during deuterium operation, runaway generation can be avoided with material injection, even when we account for runaway electron generation from deuterium–deuterium induced Compton scattering. However, when including the latter, the region in the injected-material-density space corresponding to successful mitigation is reduced. During deuterium–tritium operation, acceptable levels of runaway current and transported heat losses are only obtainable at the highest levels of achievable injected deuterium densities. Furthermore, disruption mitigation is found to be more favourable when combining deuterium with neon, compared with deuterium combined with helium or argon.

Continuing our work on group-theoretic generalisations of the prime Ax–Katz Theorem, we give a lower bound on the p-adic divisibility of the cardinality of the set of simultaneous zeros $Z(f_1,f_2,\dots,f_r)$ of r maps $f_j\,{:}\,A\rightarrow B_j$ between arbitrary finite commutative groups A and $B_j$ in terms of the invariant factors of $A, B_1,B_2, \cdots,B_r$ and the functional degrees of the maps $f_1,f_2, \dots,f_r$.

In this study, we conducted an electrical analysis of the effects of cold plasma on the properties of distilled water, using a corona discharge in a tip–plane configuration. The discharge was initiated by applying a voltage of 7.17 kV with a 2 mm gap between the tip and the water surface. We investigated the impact of plasma treatment on the total dissolved solids (TDS) and conductivity of 20 mL of distilled water, with exposure times ranging from 2 to 12 min. The results show that plasma treatment leads to a significant increase in conductivity and TDS, with a proportional increase relative to the exposure time. In addition to these measurements, we performed a detailed electrical analysis to evaluate the energy efficiency of the plasma treatment. This analysis involved calculating the useful power and energy efficiency using an equivalent electrical model of the corona discharge reactor, as direct measurement of these parameters is challenging in this context. The model allowed us to calculate energy consumption and analyse the electrical behaviour of the system throughout the treatment process. This study also enables us to monitor, control and optimize the energy during plasma treatment, providing insights into the energy dynamics involved. The findings have potential applications in improving energy efficiency in industrial and environmental processes.