https://www.um.edu.mt/library/oar/handle/123456789/77101 Sun, 19 Apr 2026 23:33:30 GMT 2026-04-19T23:33:30Z https://www.um.edu.mt/library/oar/handle/123456789/101550 Title: Bayesian data analysis techniques in noisy environments Abstract: The Bayesian method, Ensemble Learning was newly applied to the problem of galaxy shape measurements and biased shear estimates. Based on Bayes' theorem, Ensemble Learning provides an alternative technique to derive approximate posterior distributions of individual galaxy shape measurements and shear estimates. Gravitational lensing describes the event when an astronomical body appears distorted as observed from a telescope due to foreground matter acting as a lens. Measuring the variations in the shape provides a direct measure of the shear that, if inferred with a high degree of accuracy, will provide a better understanding about the anatomy of our Universe. A lot of research has been conducted in an attempt to remove the bias in the measurements accredited to noise. Noise produces random pixel intensities that further distort the appearance of galaxies making the lensing signal very faint. Current galaxy shape measurement methods necessitate correction and calibration techniques to reach the required degree of accuracy. Ensemble Learning was applied for the first time to shed light onto the problem of bias currently reported in lensing. Chapter 2 provides a thorough explanation of the Bayesian method together with other standard techniques, mainly; Maximum Likelihood, Maximum A Posteriori and sampling methods. Previous research and results are provided in Chapter 3 whilst galaxy profile simulations are depicted in the beginning of Chapter 4. There onwards, different applications of Ensemble Learning were utilised on the simulated images, each providing insight on the bias problem and current methods' limitations. The research conducted in this thesis demonstrated that Bayesian methods arc sensitive to noisy pixels present in the data. Ensemble Learning demonstrated a slight improvement in all tests. This shows that whilst the approximate posterior distributions were still skewed, these recover some symmetry in comparison to the skewed likelihood distributions produced when noisy pixels propagate non-linearly into the observable galaxy shape parameters. Correction and calibration methods will, however, still be required for Ensemble Learning to reach the desired degree of accuracy. In conclusion, future shape measurement techniques should focus on deriving a convolution model-fitting algorithm with a linear function that converts pixels into galaxy shape measurements. Description: PHD.SPACE SCIENCES&ASTRONOMY Sun, 01 Jan 2017 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/101550 2017-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/78556 Title: Extreme stars in alternative theories of gravity Abstract: Theories based on the curvature scalar have been extensively studied. However, new upcoming theories have been emerging where instead of the curvature scalar, we base our theories on the torsion of the space-time through the Weitzenbook connection callef f(T). Such a theory, however does not take into account the aspect where the cosmological constant may be a variable, which may depend on the trace of the energy-momentum tensor, T, thus giving rise to the f(T, t) theory of gravity. f (T,T) theory of gravity is a more general form of f(T) theory. Description: M.SC.ASTROPHYSICS Sun, 01 Jan 2017 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/78556 2017-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/78253 Title: Galactic rotation dynamics in modified gravity Abstract: In this thesis galactic rotation curves in f (T) gravity are investigated. Throughout this work T represents a torsional quantity. The study centers on the particular Lagrangian f (T) = T + aTn, where [n] = 1 is a real number and a is a small unknown constant. To achieve this, galactic rotation curves are treated as being composed from the contributions of two distinct features of galaxies, namely the disk and the bulge. This process is carried out for several values of the index n. The resulting curve is then compared with Milky Way profile data to constrain the value of n while fitting for the parameter a. On the galactic scale it is found that f(T) gravity departs from Einstein's standard general relativistic theory in an important way. For a small range of values of n we find good agreement with data without the need for exotic matter components to be introduced. Description: M.SC.ASTROINFORMATICS Sun, 01 Jan 2017 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/78253 2017-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/78231 Title: GPU-based acceleration searching Abstract: Since the discovery of globular cluster pulsar, a number of exhaustive searches were performed, yielding over 140 globular cluster pulsars residing in at least 26 different clusters, 74 of which are found in binary systems. Searching for a priori unknown pulsars entails that in conducting any search procedure a wide range of parameters including the pulsar periodicity and the distance to the pulsar has to be taken into consideration. Searches for pulsars in binary systems are even more challenging due to the orbital motion smearing caused by Doppler-shift changes of binary motion. Consequently, binary pulsars show periodic changes in their pulse frequency derivative, causing a reduction in the Signal-to-Noise (S/N) ratio. Correlating the spectral components with an inverse frequency and a complex conjugate kernel template response enabled the recovery of the coherent response of the signal from the orbital motion caused by the acceleration of binarity. This algorithm is called Fourier-domain acceleration searching. This was implemented in CUDA C to accelerate computational-intensive tasks on GPUs. Optimizations were implemented to reduce the computational requirements as well as to perform a more efficient data transfer from host to device. This GPU-accelerated implementation was compared to PRESTO and PRESTO2 ON GPU. Results show that GPU-based implementations of acceleration searching outperform CPU-accelerated implementations when the number of kernel templates or segment size is increased. Despite the tact that this algorithm has a very low compute-to-memory ratio, results show that this GPU-based implementation achieved a peak speed-up of 11 times more than its PRESTO CPU-accelerated counterpart. Moreover, this implementation performed up to 30% better than PRESTO2 ON GPU. Description: M.SC.ASTROINFORMATICS Sun, 01 Jan 2017 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/78231 2017-01-01T00:00:00Z