Searches for pulsars during the past fifty years, have been characterised by two problems making their discovery difficult: i) an increasing volume of data to be searched, and ii) an increasing number of `candidate' pulsar detections arising from that data, requiring analysis. Whilst almost all are caused by noise or interference, these are often indistinguishable from real pulsar detections. Deciding which candidates should be studied is therefore difficult. Indeed it has become known as the `candidate selection problem'. This thesis presents an interdisciplinary study of the selection problem, with the aim of developing a new method able to mitigate it. Specifically for future pulsar surveys undertaken with the Square kilometre Array (SKA). Through a combination of critical literature evaluations, theoretical modelling exercises, and empirical investigations, the selection problem is described in-depth here for the first time. It is shown to be characterised by the dominance of Gaussian distributed noise signals, a factor that no existing selection method accounts for. It also reveals the presence of a significant trend in survey data rates, which suggest that candidate selection is transitioning from an off-line processing procedure, to an on-line, and real-time, decision making process. In response, a new real-time machine learning based method, the GH-VFDT, is introduced in this thesis. The results presented here show that a significant improvement in selection performance can be achieved using the GH-VFDT, which utilises a learning procedure optimised for data characterised by skewed class distributions. Whilst the principled development of new numerical features that maximise the separation between pulsars and Gaussian noise, have also greatly improved GH-VFDT pulsar recall. It is therefore concluded that the sub-optimal performance of existing selection systems, is due to a combination of poor feature design, insensitivity to noise, and an inability to deal with skewed class distributions.

No description available.

A supernova explosion of a massive star at the end of its life leaves behind a compact object, either a black hole or a neutron star. We study a particular aspect of neutron stars in this project. A neutron star is a fast spinning, extremely dense object with a strong magnetic field. Neutron stars can emit lightbeams from their magnetic poles. For an observer on earth these beams appear as pulses of light. These pulses of light are practically the only way to gather information about neutron stars. We use a model of a neutron star showing how the pulses of radiation would appear from Earth based on a set of chosen parameter values. These parameters contain information regarding the geometry of the neutron star, its mass and radius, as well as some properties related to the way the radiation is emitted. We also use a particle swarm optimization method to fit the simulated pulse to the observed light pulse of the x-ray emitting Centaurus X-3 (Cen X-3) binary system. This is done In order to retrieve information about Cen X-3. Our resulting fits do not converge to a single solution, rather it shows that there are many possible configurations leading to the observed light pulses. This shows that while our model can be used to simulate the behavior of neutron stars it requires further development if one wishes to obtain reliable parameter estimates.

The main objective of this thesis is the development of a nonparametric sequential estimation technique for the off-pulse interval(s) of a source function originating from a pulsar. It is important to identify the off-pulse interval of each pulsar accurately, since the properties of the off-pulse emissions are further researched by astrophysicists in an attempt to detect potential emissions from the associated pulsar wind nebula (PWN). The identification technique currently used in the literature is subjective in nature, since it is based on the visual inspection of the histogram estimate of the pulsar light curve. The developed nonparametric estimation technique is not only objective in nature, but also accurate in the estimation of the off-pulse interval of a pulsar, as evident from the simulation study and the application of the developed technique to observed pulsar data. The first two chapters of this thesis are devoted to a literature study that provides background information on the pulsar environment and -ray astronomy, together with an explanation of the on-pulse and off-pulse interval of a pulsar and the importance thereof for the present study. This is followed by a discussion on some fundamental circular statistical ideas, as well as an overview of kernel density estimation techniques. These two statistical topics are then united in order to illustrate kernel density estimation techniques applied to circular data, since this concept is the starting point of the developed nonparametric sequential estimation technique. Once the basic theoretical background of the pulsar environment and circular kernel density estimation has been established, the new sequential off-pulse interval estimator is formulated. The estimation technique will be referred to as `SOPIE'. A number of tuning parameters form part of SOPIE, and therefore the performed simulation study not only serves as an evaluation of the performance of SOPIE, but also as a mechanism to establish which tuning parameter configurations consistently perform better than some other configurations. In conclusion, the optimal parameter configurations are utilised in the application of SOPIE to pulsar data. For several pulsars, the sequential off-pulse interval estimators are compared to the off-pulse intervals published in research papers, which were identified with the subjective \eye-ball" technique. It is found that the sequential off-pulse interval estimators are closely related to the off-pulse intervals identified with subjective visual inspection, with the benefit that the estimated intervals are objectively obtained with a nonparametric estimation technique. / PhD (Statistics), North-West University, Potchefstroom Campus, 2014

The main objective of this thesis is the development of a nonparametric sequential estimation technique for the off-pulse interval(s) of a source function originating from a pulsar. It is important to identify the off-pulse interval of each pulsar accurately, since the properties of the off-pulse emissions are further researched by astrophysicists in an attempt to detect potential emissions from the associated pulsar wind nebula (PWN). The identification technique currently used in the literature is subjective in nature, since it is based on the visual inspection of the histogram estimate of the pulsar light curve. The developed nonparametric estimation technique is not only objective in nature, but also accurate in the estimation of the off-pulse interval of a pulsar, as evident from the simulation study and the application of the developed technique to observed pulsar data. The first two chapters of this thesis are devoted to a literature study that provides background information on the pulsar environment and -ray astronomy, together with an explanation of the on-pulse and off-pulse interval of a pulsar and the importance thereof for the present study. This is followed by a discussion on some fundamental circular statistical ideas, as well as an overview of kernel density estimation techniques. These two statistical topics are then united in order to illustrate kernel density estimation techniques applied to circular data, since this concept is the starting point of the developed nonparametric sequential estimation technique. Once the basic theoretical background of the pulsar environment and circular kernel density estimation has been established, the new sequential off-pulse interval estimator is formulated. The estimation technique will be referred to as `SOPIE'. A number of tuning parameters form part of SOPIE, and therefore the performed simulation study not only serves as an evaluation of the performance of SOPIE, but also as a mechanism to establish which tuning parameter configurations consistently perform better than some other configurations. In conclusion, the optimal parameter configurations are utilised in the application of SOPIE to pulsar data. For several pulsars, the sequential off-pulse interval estimators are compared to the off-pulse intervals published in research papers, which were identified with the subjective \eye-ball" technique. It is found that the sequential off-pulse interval estimators are closely related to the off-pulse intervals identified with subjective visual inspection, with the benefit that the estimated intervals are objectively obtained with a nonparametric estimation technique. / PhD (Statistics), North-West University, Potchefstroom Campus, 2014

Thesis (Ph.D. (Space Physics)--North-West University, Potchefstroom Campus, 2008.

Thesis (Ph.D. (Space Physics)--North-West University, Potchefstroom Campus, 2008.

Thesis (Ph.D. (Space Physics)--North-West University, Potchefstroom Campus, 2008.

Theoretical work in quantum information has demonstrated that a classical hidden-variable model of an entangled singlet state can explain nonclassical correlations observed in tests of Bell’s inequality if while measuring the Bell correlation, the underlying probability distribution of the hidden-variable changes depending on the measurement basis. To rule out this possibility, distant quasars can be utilized as random number generators to set measurement bases in an experimental test of Bell’s inequality. Here we report on the design and characterization of a device that uses the color of incoming quasar photons to output a random bit with nanosecond latency. Through the 1-meter telescope at JPL Table Mountain Observatory, we observe and generate random bits from quasars with redshifts z = 0.1−3.9. In addition, we formulate a mathematical model that quantifies the fidelity of the bits generated.

Understanding the asymmetry in core collapse supernova explosions is pointed out by various astrophysicists as it is the key factor in determining the observational properties of the pulsars. The initial kick given by the ex- plosion to the pulsar affects its spin period and space velocity. Up to now, although the observations do not show a direct relation between the observational features of the pulsar and its space velocity, they show a clear relation between the spin period and the magnetic field strength, hence its radiation processes. In this thesis, as the method, tracing the companions of progenitors if they were in close binaries, which becomes a runaway star after the supernova explosion was chosen. Over the candidates selected in Guseinov et al (2005), the spectral types of 11 runaway candidates from 7 supernova remnants determined through analyzing their spectroscopic observations. Radial velocity determination was applied to the discovered B6V type star GSC 03156-01430 inside the supernova remnant G78.2+2.1. Also by studying the proper motion data, we compared the motion of the runaway star and the related pulsar in order to determine the asymmetry in the supernova explosion. The neutron star PSR 2021+4026 is moving with a 2-D velocity of &sim / 580 km/s with respect to the rest frame of its birth association Cyg OB9. &sim / 550 km/s more than expected in the symmetric case. Re-constructing the pre-supernova binary shows that the asymmetry in the supernova explosion does not depend on the binarity.