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Abstract: Gamma rays serve as important messengers in modern astrophysics, offering insights into the most energetic processes in the cosmos. Advancements in gamma-ray astronomy, facilitated by international scientific collaboration, have expanded its reach and capabilities. The Fermi-Large Area Telescope (Fermi-LAT) has so far contributed immensely to our understanding of the gamma-ray sky at GeV energies, surveying numerous source classes. At the same time, ground-based observatories like H.E.S.S., MAGIC, VERITAS, HAWC, and LHASSO, enable the exploration of high-energy (HE) phenomena across various energy scales, reaching the PeV range. The collective data from Fermi-LAT and ground-based instruments provide a comprehensive picture of cosmic phenomena across diverse energy regimes. Efforts to catalog HE gamma-ray sources have resulted in the detection of several thousand sources at GeV, including Pulsar Wind Nebulae (PWNe), Supernova Remnants (SNRs), pulsars, blazars, and Gamma-Ray Bursts (GRBs), with the observational capability to study their spectral and spatial morphology enhancing our understanding of their origin and evolution. Looking ahead, the Cherenkov Telescope Array (CTA) represents the next frontier in ground-based gamma-ray astronomy. Operating at very high energies (VHE) between 20 GeV and 300 TeV, CTA's improved sensitivity, angular resolution, and expanded field of view (FoV) promise enhanced imaging of extended sources and performance of large-scale surveys. CTA's Key Science Projects (KSPs) include the Extragalactic (EGAL) survey, a survey of a quarter of the extragalactic sky, and the Galactic Plane Survey (GPS), a survey of the entire Galactic Plane (GP). The KSPs will receive dedicated observation time and careful planning to ensure the optimization of their scientific output. As CTA is currently entering the construction phase, simulations are being extensively employed to predict its response to various signals, playing a vital role in comprehending CTA's response and sensitivity to different signals. The derived predictions are paving the way for estimating the CTA's scientific output, informing the observational strategy, and ensuring its success in maximizing the contribution to HE gamma-ray astronomy. In this thesis, I contribute to assessing the sensitivity of the CTA surveys, particularly the GPS and the EGAL survey, to diverse astrophysical sources and signals. Focusing on the GPS, I delve into understanding the detectability of pulsar halos, which emit multi-TeV gamma rays, the detection of which was recently reported by the HAWC Observatory. The study involves a spatial-spectral likelihood analysis, evaluating sensitivity to simple Gaussian extended sources and physically modeled sources. Employing a template-fitting approach, I analyze CTA's GPS sensitivity to extended sources and explore the prospects for pulsar halo detection and characterization. A preliminary population study addresses the visibility of pulsar halos to CTA's GPS and explores the angular sensitivity to extended sources. The thesis sets the detectability prospects of pulsar halos with CTA and investigates what fraction of the preliminary pulsar halo population CTA will be able to probe. The thesis extends its exploration into the persistent mystery of dark matter (DM), a fundamental puzzle in cosmology. The search for DM signals remains a vigorous pursuit in the physics community, utilizing various astrophysical messengers resulting from DM particle annihilation or decay. I investigate the potential of CTA's GPS to detect dark sub-halos within our galaxy, utilizing a similar approach as in the sensitivity assessment to pulsar halos, applied to recent sub-halo population simulations. Furthermore, the thesis addresses the intricate task of disentangling DM components from astrophysical contributions in the observed gamma-ray sky. In terms of the EGAL survey, employing advanced statistical methods such as the cross-correlation technique, I explore the prospects of using CTA's EGAL survey to correlate the Extragalactic Gamma-ray Background (EGRB) with galaxy catalogs, providing insights into DM properties. While traditional methods rely on likelihood analysis with background subtraction or template fitting, the emergence of supervised machine learning (ML) offers a novel, potentially more effective approach for cataloging the sky. The thesis touches upon the usability of ML in the high and VHE gamma-ray sky. My study focuses on CTA's GPS and utilizes deep-learning-based algorithms in a detection pipeline for the automatic classification of extended sources from gamma-ray data. As CTA stands at the forefront of gamma-ray astronomy as the next-generation observatory, the research presented in this thesis contributes a small step towards answering the open questions about pulsar halos and DM, showcasing the potential breakthroughs that may emerge from CTA's observations. The detailed likelihood analysis performed aims to advance our understanding of these enigmas, from the physical intricacies of pulsar halos to the elusive nature of DM, driven by curiosity about the continuous exploration of the Universe's mysteries.
Keywords: high-energy gamma-ray astronomy, astroparticle physics, Cherenkov Telescope Array, pulsar halos, dark matter, dissertations
Published in RUNG: 06.06.2024; Views: 207; Downloads: 4
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