Browsing by Author "Buckley, David"

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    Accretion processes in cataclysmic variable stars: insights from optical transient surveys
    (2024) Motsoaledi, Mokhine; Woudt, Patrick; Buckley, David; Warner, Brian
    Cataclysmic variable (CV) stars are binary stars mostly characterised by accretion from a main sequence donor star to a white dwarf star. Multiple CV subclasses exist with varia tions in the nature of the CV, many of which have accretion discs surrounding the accretor. This study focuses on two sub-classes of CVs, namely AM Canum Venaticorum (AM CVn) stars with helium accretion from a (semi-)degenerate helium star or white dwarf donor star, and magnetic CVs, specifically polars, which have the strongest magnetic fields of the accreting white dwarfs in CVs and lack accretion discs. I make use of optical transient surveys to explore individual objects, as well as the global population of polars, with a focus on the Catalina Real-time Transient Survey (CRTS). Follow-up observations were carried out with the 1-m and 1.9-m telescopes and the 10-m Southern African Large Telescope (SALT) at the South African Astronomical Observatory (SAAO). Observations of 7 outbursting AM CVn stars with orbital periods ranging from
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    Machine Learning techniques to discover and understand the population of flare stars in MeerLICHT data
    (2022) Bangiso, Aphiwe; Groot, Paul; Buckley, David; Johnston, Cole
    In this era of information overload, machine learning and artificial intelligence have been increasingly popular in various fields, including the field of astronomy. These approaches attempt to extract meaningful information from the data through automated means. In this work, we develop generic machine learning models that classify a given transient object from the observed light curve. We train random forest (sect 4.1.1) and multilayer perceptron neural network (sect 4.1.3) models on simulated LSST PLAsTiCC data and real data from the MeerLICHT survey. We found that the random forest model outperforms the neural network model in both data sets, achieving test accuracy of 66.0% and 98.0% in the PLAsTiCC and MeerLICHT data respectively. On the other hand, the neural network model achieved test accuracy of 65.7% and 86.6 % in the PLAsTiCC and MeerLICHT data respectively. For PLAsTiCC simulated data, we also show that grouping all types of supernovae into one aggregate class and discarding distance information improves the performance of both models to 96.5% and 96.0% for random forest and neural networks respectively. As additional work, we attempt to find sub-classes within the M-type class in MeerLiCHT data using k-means and hierarchical clustering algorithms. We find two distinct sub-classes in this data. Namely variable and non-variable M-type stars.
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    Multi-wavelength study of neutron stars in the Magellanic Clouds
    (2020) Titus, Johanna; McBride, Vanessa; Stappers, Benjamin; Buckley, David
    Massive stars are essential drivers of galaxy evolution, as well as the synthesis of heavier elements, enriching the interstellar and intergalactic medium with metals through every cycle of star formation. Thus to understand the evolving universe, it is essential to quantify the formation and evolution of massive stars in different environments. Most massive stars are born in binaries, as such their evolution are significantly affected by episodes of mass transfer. In this thesis I explore neutron stars, one of the endpoints of massive stars' evolution, in a bid to further understand the effects of binarity on evolution. To start, I conduct an optical spectroscopic and timing study of candidate X-ray binaries in the Large Magellanic Cloud (LMC), resulting in a 50% increase in the confirmed population of accreting neutron stars in the LMC. Following this study, I carry out a targeted radio pulsar search in the Small Magellanic Cloud (SMC), leading to the discovery of new pulsars, corresponding to a population size increase of 40%. The new radio pulsars allow for further characterisation of the SMC pulsar population. To relate these observational incarnations of neutron stars (i.e. radio pulsars and accreting X-ray pulsars), I utilise a binary population synthesis code that enables the prediction of pulsars in the SMC under the assumption that all pulsars are products of massive binary evolution. The simulations successfully reproduce the observed radio pulsar population of the SMC. Ultimately, pairing observational results with simulations can establish practical guidelines for future surveys, and provide a basis for using different observed populations of neutron stars to constrain binary interactions and evolution.
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    SALT spectropolarimetry commissioning
    (2010) Brink, Janus Daniel; Woudt, Patrick Alan; Buckley, David; Potter, Stephen;
    The large (10m) aperture of the Southern African Large Telescope (SALT) coupled with the unique capabilities of the Robert Stobie Spectrograph (RSS), promises unparalleled prospects for polarimetric observations on an 8 - 10 m class telescope. RSS is a complex and highly versatile first-generation instrument of the SALT. RSS-VIS, the visible arm spanning 320-900 nm, employs a high UV-transmitting optical design to support UV spectroscopy down to the atmospheric cutoff at 320nm (rare on large telescopes).