Searching For Dark Matter With Imaging Atmospheric Cherenkov Telescopes
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Searching for Dark Matter with Imaging Atmospheric Cherenkov Telescopes
Author | : Alessandro Montanari |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2024-10-21 |
Genre | : Science |
ISBN | : 9783031664694 |
Download Searching for Dark Matter with Imaging Atmospheric Cherenkov Telescopes Book in PDF, Epub and Kindle
This book provides a comprehensive review of the methodologies and searches for dark matter (DM) annihilation signals using very-high-energy gamma rays (VHE, E > 100 GeV), utilizing data from current Imaging Atmospheric Cherenkov Telescopes (IACTs) in the pre-Cherenkov Telescope Array (CTA) era. It presents the state-of-the-art statistical analysis methods and theoretical models related to TeV DM, applied to data from the H.E.S.S. telescope array, which is currently the most sensitive IACT array for observing the Galactic Center (GC), where the brightest DM annihilation signals are expected. The authors delve into the astrophysics of VHE gamma-ray production through cosmic ray acceleration. They explain the Imaging Atmospheric Cherenkov technique, describe the H.E.S.S. array, and discuss possibilities for DM annihilation-induced gamma-ray spectra and DM distribution profiles. By employing advanced statistical methods, they search for weak signals in the GC region using the H.E.S.S. Inner Galaxy Survey dataset and address systematic uncertainties. The authors present and debate the most constraining results on TeV dark matter models. Finally, this book presents the sensitivity of current IACTs to DM annihilation signals using IGS mock datasets, accounting for systematic and instrumental uncertainties. Detection prospects for canonical TeV DM models, such as the Wino, Higgsino, and quintuplet, are discussed. Sensitivity benchmarks on indirect DM searches with IACTs using H.E.S.S. as an example are provided, setting the stage for future developments in the CTA era. It serves as a consolidated resource for graduate students and researchers, presenting methodologies that could lead to significant advancements in the quest to understand dark matter.
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