We present MeerKAT neutral hydrogen (H I) observations of the Fornax A group, which is likely falling into the Fornax cluster for the first time. Our H I image is sensitive to 1.4 × 1019 atoms cm−2 over 44.1 km s−1, where we detect H I in 10 galaxies and a total of (1.12 ± 0.02) × 109 M⊙ of H I in the intra-group medium (IGM). We search for signs of pre-processing in the 12 group galaxies with confirmed optical redshifts that reside within the sensitivity limit of our H I image. There are 9 galaxies that show evidence of pre-processing and we classify each galaxy into their respective pre-processing category, according to their H I morphology and gas (atomic and molecular) scaling relations. Galaxies that have not yet experienced pre-processing have extended H I discs and a high H I content with a H2-to-H I ratio that is an order of magnitude lower than the median for their stellar mass. Galaxies that are currently being pre-processed display H I tails, truncated H I discs with typical gas fractions, and H2-to-H I ratios. Galaxies in the advanced stages of pre-processing are the most H I deficient. If there is any H I, they have lost their outer H I disc and efficiently converted their H I to H2, resulting in H2-to-H I ratios that are an order of magnitude higher than the median for their stellar mass. The central, massive galaxy in our group (NGC 1316) underwent a 10:1 merger ∼2 Gyr ago and ejected 6.6−11.2 × 108 M⊙ of H I, which we detect as clouds and streams in the IGM, some of which form coherent structures up to ∼220 kpc in length. We also detect giant (∼100 kpc) ionised hydrogen (Hα) filaments in the IGM, likely from cool gas being removed (and subsequently ionised) from an in-falling satellite. The Hα filaments are situated within the hot halo of NGC 1316 and there are localised regions that contain H I. We speculate that the Hα and multiphase gas is supported by magnetic pressure (possibly assisted by the NGC 1316 AGN), such that the hot gas can condense and form H I that survives in the hot halo for cosmological timescales.

The pulse shape discrimination capbability of the newly available EJ299-33 plastic scintillator is compared with that of the widely-used EJ301 liquid scintillator, using a digital implementation of the charge comparison algorithm. Typical pulse shapes for neutrons and gamma-rays produced by an Am-Be radioisotropic source are fitted to an analytical model, in order to determine the time constants and relative weightings of the fast, medium and slow decay components of scintillation. These pulse shapes are compared to those generated by a Monte-Carlo simulation, utilising the Geant4 toolkit.

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A neutron spectrometer based on a single EJ299-33 plastic scintillator ( cm diameter cm) is described. A digital implementation of pulse shape discrimination is used to separate events associated with neutrons from those associated with gamma-rays. Measurements made using a ns-pulsed neutron beam are used to produce response functions of the detector for neutrons over the energy range 10 -100 MeV. These lineshapes are used to test the capability of the spectrometer to produce neutron energy spectra, via the unfolding of pulse height spectra, for use in neutron fields having any type of time structure. The results are compared with those from a similar spectrometer constructed from EJ301 liquid scintillator.

Scientists across all disciplines increasingly rely on machine learning code to analyse the vast quantity of data that is now commonplace, rapidly growing in volume and complexity. As the compelling trends and outliers are identified, careful and close inspection will still be necessary to disentangle the astrophysics from, say, systematics and false positives. It is clearly necessary to migrate to new technologies to facilitate scientific analysis and exploration. Astrophysical data is inherently multi-parameter, with the spatial dimensions at the core of imaging, spectral, time-domain and simulation data. The arrival of mainstream virtualreality (VR) headsets and increased GPU power, as well as the availability of versatile development tools for video games, has enabled scientists to deploy such technology to effectively interrogate and interact with complex multidimensional data. In this paper we present development and results from custom-built interactive VR tools, called the iDaVIE suite, that are informed and driven by research on galaxy evolution, cosmic web large-scale structure, galaxy-galaxy interactions, and gas/kinematics of nearby galaxies in survey and targeted observations. The Era of Big Data ushered in by the SKA and its Pathfinders challenges our storage, calibration, reduction and refinement methods, and it also demands innovative ways to interrogate the data at intuitive -leveraging visual perception -levels necessary for new discovery.

In this paper, we describe an HDF5 schema created to support the efficient visualization of the large image cubes that will be produced by SKA Phase 1 and precursor radio telescopes. We demonstrate how the ''HDF5-IDIA'' schema's features can improve the performance of visualization software, using both low-level metrics and real-world tests of the schema's implementation in CARTA, an image viewer that is being developed to replace the existing CyberSKA and CASA viewers.

Progress towards the realization of a new compact neutron spectrometer is described. The detector is based on EJ299-33 plastic scintillator coupled to silicon photomultipliers, and a digital implementation of pulse shape discrimination is used to separate events associated with neutrons from those associated with gamma rays. The spectrometer will be suitable over the neutron energy range 1-100 MeV, illustrated in this work with measurements made using an AmBe radioisotopic source and quasi-monoenergetic neutron beams produced using a cyclotron.