ASTRI is a project aiming at the realization of a gamma-ray imaging Cherenkov telescope that observes the sky in the TeV band. Recently, the development of a mini-array (MA) of ASTRI telescopes has been funded by the Istituto Nazionale di Astrofisica. The ASTRI Comprehensive Data Challenge (ACDC) project aims at optimizing the scientific exploitation and analysis techniques of the ASTRI MA, by performing a complete end-to-end simulation of a tentative scientific program, from the generation of suitable instrument response functions to the proposal, selection, analysis, and interpretation of the simulated data. We assumed that the MA will comprise nine ASTRI telescopes arranged in a (almost) square geometry (mean distance between telescopes of similar to 250m). We simulated three years of observations, adopting a realistic pointing plan that takes into account, for each field, visibility constraints for an assumed site in Paranal (Chile) and observational time slots in dark sky conditions. We simulated the observations of nineteen Galactic and extragalactic fields selected for their scientific interest, including several classes of objects (such as pulsar wind nebulae, supernova remnants, gamma-ray binaries etc), for a total of 81 point-like and extended sources. Here we present an overview of the ACDC project, providing details on the different software packages needed to carry out the simulated three-years operation of the ASTRI MA. We discuss the results of a systematic analysis applied on the whole simulated data, by making use of prototype science tools widely adopted by the TeV astronomical community. Furthermore, particular emphasis is also given to some targets used as benchmarks. (C) 2020 Elsevier B.V. All rights reserved.
Scientific prospects for a mini-array of ASTRI telescopes: A γ-ray TeV data challenge / Pintore, F.; Giuliani, A.; Belfiore, A.; Paizis, A.; Mereghetti, S.; La Palombara, N.; Crestan, S.; Sidoli, L.; Lombardi, S.; D'Aì, A.; Saturni, F.G.; Caraveo, P.; Burtovoi, A.; Fiori, M.; Boccato, C.; Caccianiga, A.; Costa, A.; Cusumano, G.; Gallozzi, S.; Zampieri, L.; Balmaverde, B.; Tibaldo, L.. - In: JOURNAL OF HIGH ENERGY ASTROPHYSICS. - ISSN 2214-4048. - ELETTRONICO. - 26:(2020), pp. 83-94. [10.1016/j.jheap.2020.03.002]
Scientific prospects for a mini-array of ASTRI telescopes: A γ-ray TeV data challenge
Burtovoi, A.;
2020
Abstract
ASTRI is a project aiming at the realization of a gamma-ray imaging Cherenkov telescope that observes the sky in the TeV band. Recently, the development of a mini-array (MA) of ASTRI telescopes has been funded by the Istituto Nazionale di Astrofisica. The ASTRI Comprehensive Data Challenge (ACDC) project aims at optimizing the scientific exploitation and analysis techniques of the ASTRI MA, by performing a complete end-to-end simulation of a tentative scientific program, from the generation of suitable instrument response functions to the proposal, selection, analysis, and interpretation of the simulated data. We assumed that the MA will comprise nine ASTRI telescopes arranged in a (almost) square geometry (mean distance between telescopes of similar to 250m). We simulated three years of observations, adopting a realistic pointing plan that takes into account, for each field, visibility constraints for an assumed site in Paranal (Chile) and observational time slots in dark sky conditions. We simulated the observations of nineteen Galactic and extragalactic fields selected for their scientific interest, including several classes of objects (such as pulsar wind nebulae, supernova remnants, gamma-ray binaries etc), for a total of 81 point-like and extended sources. Here we present an overview of the ACDC project, providing details on the different software packages needed to carry out the simulated three-years operation of the ASTRI MA. We discuss the results of a systematic analysis applied on the whole simulated data, by making use of prototype science tools widely adopted by the TeV astronomical community. Furthermore, particular emphasis is also given to some targets used as benchmarks. (C) 2020 Elsevier B.V. All rights reserved.
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