| Title: | Exploring the population of Galactic very-high-energy γ-ray sources |
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| Authors: | ID Steppa, Constantin (Author)
ID Bhattacharyya, Saptashwa (Author)
ID MARČUN, Barbara (Author)
ID Pérez Romero, Judit (Author)
ID Stanič, Samo (Author)
ID Vodeb, Veronika (Author)
ID Vorobiov, Serguei (Author)
ID Zaharijas, Gabrijela (Author)
ID Zavrtanik, Marko (Author)
ID Zavrtanik, Danilo (Author)
ID Živec, Miha (Author), et al. |
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| Files: |  ICRC2021_798.pdf (744,16 KB)
MD5: F1E2CFA4DE096BFF57ECF95872173F21
 https://pos.sissa.it/395/
https://pos.sissa.it/395/798/pdf
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| Language: | English |
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| Work type: | Not categorized |
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| Typology: | 1.08 - Published Scientific Conference Contribution |
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| Organization: | UNG - University of Nova Gorica
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| Abstract: | At very high energies (VHE), the emission of γ rays is dominated by discrete sources. Due to the limited resolution and sensitivity of current-generation instruments, only a small fraction of the total Galactic population of VHE γ-ray sources has been detected significantly. The larger part of the population can be expected to contribute as a di˙use signal alongside emission originating from propagating cosmic rays. Without quantifying the source population, it is not possible to disentangle these two components. Based on the H.E.S.S. Galactic plane survey, a numerical approach has been taken to develop a model of the population of Galactic VHE γ-ray sources, which is shown to account accurately for the observational bias. We present estimates of the absolute number of sources in the Galactic Plane and their contribution to the total VHE γ-ray emission for five di˙erent spatial source distributions. Prospects for CTA and its ability to constrain the model are discussed. Finally, first results of an extension of our modelling approach using machine learning to extract more information from the available data set are presented. |
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| Keywords: | Cherenkov Telescope Array, very-high energy gamma-rays, gamma-ray sources |
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| Publication status: | Published |
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| Year of publishing: | 2021 |
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| PID: | 20.500.12556/RUNG-8430  |
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| COBISS.SI-ID: | 164865539 |
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| NUK URN: | URN:SI:UNG:REP:SNFYNOSN |
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| Publication date in RUNG: | 18.09.2023 |
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| Views: | 640 |
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| Downloads: | 5 |
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| Metadata: |     |
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