Advanced stereoscopy applied to CTAO
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908559103492096 |
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| author | Messaoud, Hana Ali François, Tom Vuillaume, Thomas |
| author_facet | Messaoud, Hana Ali François, Tom Vuillaume, Thomas |
| contents | The Cherenkov Telescope Array Observatory (CTAO) is an international observatory currently under construction, which will consist of two sites (one in the Northern Hemisphere and one in the Southern Hemisphere). It will eventually be the largest and most sensitive ground-based gamma-ray observatory. In the meantime, a small subarray composed of four Large-Sized Telescopes (LSTs) at the Northern site will begin collecting data in the coming year. In preparation, we present a stereoscopic event reconstruction using graph neural networks (GNNs) to combine information from several telescopes of this subarray. In our previous work, we explored the use of GNNs for the stereoscopic reconstruction of gamma-ray events on simulated data from the Prod5 sample and showed that GNNs provide a better stereoscopic reconstruction. We now compare this approach to the currently foreseen method that analytically combines the output of monoscopic random forests, and explore how GNNs can be used in fusion with the Random forest algorithm in order to provide a more sensitive stereoscopic system. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_21366 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Advanced stereoscopy applied to CTAO Messaoud, Hana Ali François, Tom Vuillaume, Thomas Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena High Energy Physics - Phenomenology The Cherenkov Telescope Array Observatory (CTAO) is an international observatory currently under construction, which will consist of two sites (one in the Northern Hemisphere and one in the Southern Hemisphere). It will eventually be the largest and most sensitive ground-based gamma-ray observatory. In the meantime, a small subarray composed of four Large-Sized Telescopes (LSTs) at the Northern site will begin collecting data in the coming year. In preparation, we present a stereoscopic event reconstruction using graph neural networks (GNNs) to combine information from several telescopes of this subarray. In our previous work, we explored the use of GNNs for the stereoscopic reconstruction of gamma-ray events on simulated data from the Prod5 sample and showed that GNNs provide a better stereoscopic reconstruction. We now compare this approach to the currently foreseen method that analytically combines the output of monoscopic random forests, and explore how GNNs can be used in fusion with the Random forest algorithm in order to provide a more sensitive stereoscopic system. |
| title | Advanced stereoscopy applied to CTAO |
| topic | Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena High Energy Physics - Phenomenology |
| url | https://arxiv.org/abs/2509.21366 |