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Performance of a pr...
Performance of a proposed event-type based analysis for the Cherenkov Telescope Array
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- Hassan, T. (författare)
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT)
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- Gueta, O. (författare)
- German Electron Synchrotron (DESY)
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- Maier, G. (författare)
- German Electron Synchrotron (DESY)
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- Nöthe, M. (författare)
- Technical University of Dortmund
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- Peresano, M. (författare)
- Paris Diderot University,University of Paris-Saclay
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- Vovk, I. (författare)
- University of Tokyo
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- Carlile, C. (författare)
- Lund University,Lunds universitet,Astronomi - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Lund Observatory - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
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- Dravins, D. (författare)
- Lund University,Lunds universitet,Astronomi - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Lund Observatory - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
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- Zmija, A. (författare)
- Friedrich-Alexander University Erlangen-Nürnberg
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(creator_code:org_t)
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- Trieste, Italy : Sissa Medialab, 2022
- 2022
- Engelska.
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Ingår i: 37th International Cosmic Ray Conference (ICRC2021) - GAI - Gamma Ray Indirect. - Trieste, Italy : Sissa Medialab. - 1824-8039. ; 395
- Relaterad länk:
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http://dx.doi.org/10... (free)
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https://pos.sissa.it...
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https://lup.lub.lu.s...
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https://doi.org/10.2...
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Abstract
Ämnesord
Stäng
- The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. Classically, data analysis in the field maximizes sensitivity by applying quality cuts on the data acquired. These cuts, optimized using Monte Carlo simulations, select higher quality events from the initial dataset. Subsequent steps of the analysis typically use the surviving events to calculate one set of instrument response functions (IRFs). An alternative approach is the use of event types, as implemented in experiments such as the Fermi-LAT. In this approach, events are divided into sub-samples based on their reconstruction quality, and a set of IRFs is calculated for each sub-sample. The sub-samples are then combined in a joint analysis, treating them as independent observations. This leads to an improvement in performance parameters such as sensitivity, angular and energy resolution. Data loss is reduced since lower quality events are included in the analysis as well, rather than discarded. In this study, machine learning methods will be used to classify events according to their expected angular reconstruction quality. We will report the impact on CTA high-level performance when applying such an event-type classification, compared to the classical procedure. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)
Ämnesord
- NATURVETENSKAP -- Fysik -- Astronomi, astrofysik och kosmologi (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences -- Astronomy, Astrophysics and Cosmology (hsv//eng)
Nyckelord
- Cosmology
- Gamma rays
- Germanium alloys
- Germanium compounds
- Intelligent systems
- Learning systems
- Quality control
- Telescopes
- Tellurium compounds
- Astroparticle physics
- Cherenkov telescope arrays
- Event Types
- Gamma-rays
- Instrument response functions
- Performance
- Reconstruction quality
- Sub-samples
- Type-based analysis
- Very high energies
- Monte Carlo methods
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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