Institut für Physik und Astronomie
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Institute
The current generation of ground-based instruments has rapidly extended the limits of the range accessible to us with very-high-energy (VHE) gamma-rays, and more than a hundred sources have now been detected in the Milky Way. These sources represent only the tip of the iceberg, but their number has reached a level that allows population studies. In this work, a model of the global population of VHE gamma-ray sources based on the most comprehensive census of Galactic sources in this energy regime, the H.E.S.S. Galactic plane survey (HGPS), will be presented. A population synthesis approach was followed in the construction of the model. Particular attention was paid to correcting for the strong observational bias inherent in the sample of detected sources. The methods developed for estimating the model parameters have been validated with extensive Monte Carlo simulations and will be shown to provide unbiased estimates of the model parameters. With these methods, five models for different spatial distributions of sources have been constructed. To test the validity of these models, their predictions for the composition of sources within the sensitivity range of the HGPS are compared with the observed sample. With one exception, similar results are obtained for all spatial distributions, showing that the observed longitude profile and the source distribution over photon flux are in fair agreement with observation. Regarding the latitude profile and the source distribution over angular extent, it becomes apparent that the model needs to be further adjusted to bring its predictions in agreement with observation. Based on the model, predictions of the global properties of the Galactic population of VHE gamma-ray sources and the prospects of the Cherenkov Telescope Array (CTA) will be presented.
CTA will significantly increase our knowledge of VHE gamma-ray sources by lowering the threshold for source detection, primarily through a larger detection area compared to current-generation instruments. In ground-based gamma-ray astronomy, the sensitivity of an instrument depends strongly, in addition to the detection area, on the ability to distinguish images of air showers produced by gamma-rays from those produced by cosmic rays, which are a strong background. This means that the number of detectable sources depends on the background rejection algorithm used and therefore may also be increased by improving the performance of such algorithms. In this context, in addition to the population model, this work presents a study on the application of deep-learning techniques to the task of gamma-hadron separation in the analysis of data from ground-based gamma-ray instruments. Based on a systematic survey of different neural-network architectures, it is shown that robust classifiers can be constructed with competitive performance compared to the best existing algorithms. Despite the broad coverage of neural-network architectures discussed, only part of the potential offered by the
application of deep-learning techniques to the analysis of gamma-ray data is exploited in the context of this study. Nevertheless, it provides an important basis for further research on this topic.
Eta Carinae
(2018)
The exceptional binary star Eta Carinae has been fascinating scientists and the people in the Southern hemisphere alike for hundreds of years. It survived an enormous outbreak, comparable to a supernova energy-wise, and for a short period became the brightest star of the night sky. From observations from the radio regime to X-rays the system's characteristics and its emission in photon energies up to ~ 50 keV are well studied today. The binary is composed of two massive stars of ~ 30 and ~ 100 solar masses. Either star drives a strong stellar wind that continuously carries away a fraction of its mass. The collision of these winds leads to a shock on each side of the encounter. In the wind-wind-collision region plasma gets heated when it is overrun by the shocks. Part of the emission seen in X-rays can be attributed to this plasma. Above ~ 50 keV the emission is no longer of thermal origin: the required plasma temperature exceeds the available mechanical energy input of the stellar winds. In contrast to its observational history in thermal energies observational evidence of Eta Carinae's non-thermal emission has only recently built up. In high-energy gamma-rays Eta Carinae is the only binary of its kind that has been detected unambiguously. Its energy spectrum reaches up to ~ hundred GeV, a regime where satellite-based gamma-ray experiments run out of statistics. Ground-based gamma-ray experiments have the advantage of large photon collection areas. H.E.S.S. is the only gamma-ray experiment located in the Southern hemisphere and thus able to observe Eta Carinae in this energy range. H.E.S.S. measures gamma-rays via electromagnetic showers of particles that very-high-energy gamma-rays initiate in the atmosphere. The main challenge in observations of Eta Carinae with H.E.S.S. is the UV emission of the Carina nebula that leads to a background that is up to 10 times stronger than usual for H.E.S.S. This thesis presents the first detection of a colliding-wind binary in very-high-energy gamma-rays and documents the studies that led to it. The differential gamma-ray energy spectrum of Eta Carinae is measured up to 700 GeV. A hadronic and leptonic origin of the gamma-ray emission is discussed and based on the comparison of cooling times a hadronic scenario is favoured.