ASTRI Mini-Array Instrument Response Functions (Prod2, v1.0)

Aim:

This data repository provides access to a set of Instrument Response Functions (IRFs) of the ASTRI Mini-Array, saved in a FITS data file. The IRFs can be used as input to science analysis tools for high-level scientific analysis purposes.

Citations:

In the case the present ASTRI Mini-Array Instrument Response Functions (IRFs) are used in a research project, we kindly ask to add the following acknowledgement in any resulting publication:

"This research has made use of the ASTRI Mini-Array Instrument Response Functions (IRFs) provided by the ASTRI Project [citation]."

Please use the following BibTex Entry for [citation] in the reference section of your publication: https://zenodo.org/record/6827882/export/hx

Instrument:

The ASTRI Mini-Array is an international project led by the Italian National Institute for Astrophysics (INAF) to build and operate an array of nine 4-m class Imaging Atmospheric Cherenkov Telescopes (IACTs) at the Observatorio del Teide (Tenerife, Spain) [1]. The telescopes are an evolution of the dual-mirror ASTRI-Horn telescope, successfully installed and tested since 2014 at the INAF “M.C. Fracastoro” observing station in Serra La Nave (Mt. Etna, Italy) [2][3].

The ASTRI Mini-Array is designed to perform deep observations of the galactic and extragalactic gamma-ray sky in the TeV and multi-TeV energy band, with a differential sensitivity that surpass the one of current Cherenkov telescope facilities above a few TeV, extending the energy band well above hundreds of TeV [4].

The main science goals of the ASTRI Mini-Array in the very high-energy (VHE) gamma-ray band encompass both galactic and extragalactic science [5][6][7]. Important synergies with other ground-based gamma-ray facilities in the Northern Hemisphere and space-borne telescopes are foreseen.

Monte Carlo Simulations:

The IRFs of the ASTRI Mini-Array were obtained from a dedicated Monte Carlo (MC) production (dubbed ASTRI Mini-Array Prod2, version 1.0). Air showers initiated by gamma rays, protons and electrons were simulated using the CORSIKA package [8] (version 6.99), while the response of the array telescopes was simulated using the sim_telarray package [9] (version 2018-11-07).

The layout of the ASTRI Mini-Array telescopes considered in the MC simulations is based on the actual telescope positions at the Teide Observatory site (28.30°N, 16.51°W, 2390 m a.s.l.). The nominal telescope pointing configuration, in which all telescopes point to the same sky position, was assumed in all MC simulations. Air showers produced by the primaries were simulated as coming from a zenith angle of 20° and an azimuth angle of 0° and 180° (corresponding to telescope pointing directions toward the geomagnetic North and South, respectively). Although not-negligible differences in performance (on the order of ≤15% at a zenith angle of 20°) are found between the two azimuthal pointing directions, the final IRFs were obtained by averaging between the two directions. Finally, all MC simulations were generated with a night sky background (NSB) level corresponding to dark sky conditions at the Teide Observatory site.

Monte Carlo data reduction and analysis:

The MC simulations were reduced and analysed with A-SciSoft [10][11] (version 0.3.1), the scientific software package of the ASTRI Project. The calibration and reconstruction of the MC events were achieved with the standard methods implemented in the data reduction pipeline (see [10][11] for more details). In particular, the background rejection and energy reconstruction were achieved with a procedure based on the Random Forest method [12], while the arrival direction of each shower was estimated from a weighted intersection of the major axes of the images from different telescopes. After the full reconstruction of the MC events, the background (proton and electron) events were re-weighted according to recent experimental measurements of their spectra, while gamma-ray events with a power-law gamma-ray spectrum with a photon index of 2.62. This approach follows a similar procedure adopted in [13].

The final analysis cuts were based on the background rejection, shower arrival direction, and event multiplicity parameters. They were defined, in each considered energy bin and off-axis bin, by optimising the flux sensitivity for 50 hr exposure time. Then, five standard deviations (5σ, with σ defined as in Eq. 17 of [14]) were required for a detection in each energy bin and off-axis bin, considering the same exposure time (as in the cut optimization procedure) and a ratio of the off-source to on-source exposure equal to 5. In addition, the signal excess was required to be larger than 10 and at least 5 times the expected systematic uncertainty in the background estimation (assumed to be ∼1%). It should be noted that these analysis cuts, based on the best flux sensitivity, do not provide the best angular and energy resolution achievable by the system. Other analysis cuts, which take into account both differential flux sensitivity and angular/energy resolution in the cut optimization process, may actually provide better performance [4].

Instrument Response Functions (IRFs):

The IRFs are saved in a FITS data file [15] which contains the following quantities (FITS tables): effective collection area ("EFFECTIVE AREA" table), angular resolution ("POINT SPREAD FUNCTION" table), energy resolution ("ENERGY DISPERSION" table), and residual background rate ("BACKGROUND" table). These quantities are provided as a function of the energy and the off-axis. The energy bins are logarithmic and range between 10^-0.7 ~ 0.2 TeV and 10^2.5 ~ 316 TeV. Five energy bins per decade are used for the angular resolution and residual background rate, while ten energy bins per decade for the effective collection area. In the case of energy resolution, the energy migration matrix is provided with a much finer energy binning. The off-axis bins are linearly spaced between 0° and 6°, with a bin width equal to 1°. In the case of the residual background rate, a 2-dimensional squared spatial binning is used, which ranges between 0° and 6° with a bin width equal to 0.2° in each direction.

The IRFs can be used as input to science analysis tools and, in particular, are compliant with the input/output (I/O) data format requested by the science analysis tools Gammapy [16] and ctools [17].

Dataset:

The dataset consists of one file: "astri_100_43_008_0502_C0_20_AVERAGE_50h_SC_v1.0.lv3.fits".

The naming convention is: astri_[ARRAY_ID]_[ORIG_ID]_[REL_ID]_[PACKET_TYPE]_[CLASS_CUT]_[ZENITH]_[AZIMUTH]_[ EXPOSURE_TIME]_[AIM]_[VERSION].lv3.fits

where:

• [ARRAY_ID] = 100               (100 = ASTRI Mini-Array with 9 telescopes)
• [ORIG_ID] = 43                    (4 = INAF-OAR; 3 = AIV/AIT MC simulations)
• [REL_ID] = 008                    (008 = MC prod2, v1.0)
• [PACKET_TYPE] = 0502     (0502 = IRF3)
• [CLASS_CUT] = C0             (C0 = cuts based on sensitivity maximisation)
• [ZENITH] = 20                      [deg]
• [AZIMUTH] = AVERAGE      [deg]
• [EXPOSURE_TIME] = 50h
• [AIM] = SC                            (SC = SCience)
• [VERSION]= v1.0

Acknowledgments:

This work was conducted in the context of the ASTRI Project thanks to the support of the Italian Ministry of University and Research (MUR) as well as the Ministry for Economic Development (MISE) with funds specifically assigned to the Italian National Institute of Astrophysics (INAF). We acknowledge support from the Brazilian Funding Agency FAPESP (Grant 2013/10559-5) and from the South African Department of Science and Technology through Funding Agreement 0227/2014 for the South African Gamma-Ray Astronomy Programme. The Instituto de Astrofisica de Canarias (IAC) is supported by the Spanish Ministry of Science and Innovation (MICIU). This work has also been partially supported by H2020-ASTERICS, a project funded by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n. 653477. This work has gone through the internal ASTRI review process.

We would also like to thank the computing centres that provided resources for the generation of the Monte Carlo (MC) simulations used to produce the ASTRI Mini-Array Instrument Response Functions (IRFs) released in this work:

• CAMK, Nicolaus Copernicus Astronomical Center, Warsaw, Poland
• CIEMAT-LCG2, CIEMAT, Madrid, Spain
• CYFRONET-LCG2, ACC CYFRONET AGH, Cracow, Poland
• DESY-ZN, Deutsches Elektronen-Synchrotron, Standort Zeuthen, Germany
• GRIF, Grille de Recherche d’Ile de France, Paris, France
• IN2P3-CC, Centre de Calcul de l’IN2P3, Villeurbanne, France
• IN2P3-CPPM, Centre de Physique des Particules de Marseille, Marseille, France
• IN2P3-LAPP, Laboratoire d'Annecy de Physique des Particules, Annecy, France
• INFN-FRASCATI, INFN Frascati, Frascati, Italy
• INFN-T1, CNAF INFN, Bologna, Italy
• INFN-TORINO, INFN Torino, Torino, Italy
• MPIK, Heidelberg, Germany
• OBSPM, Observatoire de Paris Meudon, Paris, France
• PIC, port d’informacio cientifica, Bellaterra, Spain
• prague_cesnet_lcg2, CESNET, Prague, Czech Republic
• praguelcg2, FZU Prague, Prague, Czech Republic
• UKI-NORTHGRID-LANCS-HEP, Lancaster University, United Kingdom

References:

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11. Lombardi, S. et al., "ASTRI data reduction software in the framework of the Cherenkov Telescope Array", in [Software and Cyberinfrastructure for Astronomy V], Guzman, J. C. and Ibsen, J., eds., Society of Photo- Optical Instrumentation Engineers (SPIE) Conference Series 10707, 107070R (July 2018).
12. Breiman, L., "Random Forests", Machine Learning 45, 5–32 (Jan. 2001).
13. Cherenkov Telescope Array Observatory, & Cherenkov Telescope Array Consortium. (2021). CTAO Instrument Response Functions - prod5 version v0.1 (v0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5499840
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15. Pence, W. D. et al., "Definition of the Flexible Image Transport System (FITS), version 3.0", A&A 524, A42 (Dec. 2010).
16. Deil, C. et al., "Gammapy - A prototype for the CTA science tools", in [35th International Cosmic Ray Conference (ICRC2017)], International Cosmic Ray Conference 301, 766 (Jan. 2017).
17. Knödlseder, J. et al., "GammaLib and ctools. A software framework for the analysis of astronomical gamma- ray data", A&A 593, A1 (Aug. 2016).