Browsing by Author "Erasmus, Nicolas"

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    Characterisation of small, close-approaching near-earth asteroids
    (2021) Janse van Rensburg, Petronella; Erasmus, Nicolas; Bershady, Matthew A
    Near-Earth Asteroids (NEAs) are a population of asteroids in a steady state, constantly being replenished with asteroids from the main belt. NEAs have orbits that come close to or cross the Earth's orbit and therefore some could have impacting trajectories and pose a threat. Small NEAs (diameter < 300 m) pose a greater threat compared to large NEAs because they are more abundant and can cause significant damage on impact. The characteristics of small NEAs can give an indication of the most likely properties of potential future impactors. Even though in recent years the number of discovery and characterisation programmes of NEAs have increased, the characterisation of the small NEA population still lags behind because they can only be observed with 1-m class telescopes when they pass close to the Earth and become bright enough. Presented here in this MSc thesis are 20 NEAs that were successfully observed and characterised with the South African Astronomical Observatory (SAAO) 40-inch telescope and the Sutherland HighSpeed Optical Camera. Out of the 20 NEAs, 14 had diameters < 300 m (H > 21). Characterisation involved assigning taxonomic probabilities to each NEA based on spectra from the Bus-DeMeo classification scheme and thereby inferring its most probable composition, as well as using a Lomb-Scargle periodogram to extract the rotation period from multi-band photometry. The taxonomic probabilities were determined with the colours g0−r 0 and r0−i 0 , in combination with a machine learning (ML) algorithm trained on synthetic colours from observed spectra obtained from literature. The taxonomies considered were the S-, C-, and X-complexes, and the D-, Q-, and V-types. In this thesis, the taxonomic probabilities are reported for all of the targets. A distinct taxonomic class was assigned to 15 NEAs that had a probability >50% in a specific taxonomy. New taxonomic classes are reported for 11 of the targets. A notable result of this study is the confirmation of the prediction that the most common meteorite, ordinary chondrites, are due to S-complex and Q-type asteroids. The fraction of meteorite falls due to ordinary chondrites are similar to the combined fraction of Scomplex and Q-type asteroids in this study (∼80%). This confirmation was only possible by including the Q-type asteroids in the classification and being able to differentiate between the C-complex and Q-type asteroids with two colours and a ML approach. A rotation period was extracted for nine NEAs that were observed for long enough to resolve a light curve period. The remaining targets had only partial or flat light curves and no period could be resolved from the periodogram. Reported here are also three small NEAs with H > 22 magnitude which were found to have rotation periods smaller than the 2.2 hour spin barrier and could be rigid pieces of rock instead of rubble piles.
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    Detecting surface inhomogeneity of asteroids
    (2025) Mnisi, Mandlenkosi; Erasmus, Nicolas; Monageng, Itumeleng
    This thesis investigates the detection of surface composition inhomogeneity on asteroids using time-series spectroscopy and photometry. Observations were conducted on three test cases—Pluto, asteroid 2005 EK70, and the weather satellite Meteosat-11 using the Mookodi instrument on the Lesedi telescope. For Pluto, time-resolved spectroscopy revealed methane ice absorption bands, with band depths varying between 3.33% and 4.80%, consistent with previously reported values. Photometric analysis supported these results, showing an r − i colour variation linked to surface inhomogeneity. For asteroid 2005 EK70, no significant spectral variations were detected, suggesting a uniform surface composition. The asteroid's diameter was determined to be 1.25 ± 0.26 km, with a rotation period of 4.34 hours, indicating it is stable. The third test case, Meteosat-11, served as a control to verify Mookodi's ability to track stationary objects. These findings demonstrate the capability of ground-based instruments like Lesedi to detect surface composition inhomogeneity from Earth. Future work could further refine these methods and apply them to a wider range of solar system objects.
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    Developing instrumentation and software for rapid follow-up and characterisation of near-Earth Asteroids
    (2025) Ngwane, Thobekile sandra; Erasmus, Nicolas; Groot, Paul
    Near-Earth Asteroids (NEAs), a subset of minor bodies in the Solar System, result from resonant interactions with major planets, particularly Jupiter, leading to their escape from the main asteroid belt. The International Astronomical Union's Minor Planet Center (MPC) database, as of December 2024, lists approximately 37,000 discovered NEAs, with an average daily discovery rate of 10 from dedicated survey programs like Catalina Sky Survey (CSS), the Panoramic Survey Telescope and Rapid Response System (PanSTARRS), and the Asteroid Terrestrial-impact Last Alert System (ATLAS). This project uses the robotic observing capabilities of the South African Astronomical Observatory's 1-meter telescope, Lesedi, equipped with the Mookodi instrument. Observations are scheduled in robotic mode using automated Python scripts, enabling rapid follow-up of newly discovered NEAs, often within the same night of detection. This rapid response is essential, as smaller asteroids (< 300 metres)—a significantly understudied group— quickly dim as they move away from Earth, making precise measurements challenging. Since the start of this project in February 2023, approximately 230 NEAs have been successfully observed in robotic mode, with an average absolute magnitude (H-magnitude) of 24.4. This magnitude corresponds to asteroid sizes ranging from 32 to 78 metres, depending on an assumed albedo of 0.05 to 0.30. Approximately 75% of these asteroids have a diameter (D) of less than 100 metres. Among the observed NEAs, 15 have been classified as potentially hazardous asteroids (PHAs). The findings presented in this study are based on multi-filter photometry and astrometric measurements collected as part of the program. The astrometric data significantly contributes to the MPC's orbital refinement and the observed NEAs designation. Photometric observations using g, r, and i filters enable the extraction of g - r and r - i colours, which approximate the spectral slope. These colours aid in determining the most likely taxonomic type (S, C, X, D, Q, or V-types in this project) of the observed NEAs, as defined by the Bus-DeMeo Classification Scheme. This provides insight into their composition. Using the collected data, the compositional distribution of the small NEA population was determined and compared with previous studies investigating a larger size population.