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Abstract

The essence of this doctoral research constitutes the development and application of novel data analysis and modelling techniques to observations from the High Altitude Water Cherenkov (HAWC) gamma-ray observatory. This thesis is organised in three main parts, culminating in the study of extended very-high-energy sources such as the Fermi bubbles. We first develop a novel discriminator to distinguish between gamma-ray-induced and proton-induced atmospheric showers. Our discriminator is independent of core reconstruction and is useful for enhancing the accuracy of the detector simulation. Secondly, we developed a new background model which incorporates the cosmic-ray anisotropy, exploits all statistics available and has fast computation times. Thirdly, we present a profile likelihood approach to calculate the significance and flux from any region of the sky, which allows the combination of data from different shower sizes while consistently accounting for their relative contributions. With the above tools, we perform blind searches for large-scale structures in the TeV gamma-ray sky. We find a candidate source region with significance up to 5.30 sigma at 16 degree integration scale, which could be a TeV halo associated with a pulsar, molecular clouds or a galactic outflow. Finally, with no significant signal from the north Fermi bubble and its base, we compute their integral flux upper limits, at 95% confidence level and present a hadronic model with an estimated proton cut-off energy at 85 TeV.