To cut or not to cut: Data-quality evaluation for the ASTRI Mini-Array

The ASTRI Mini-Array consists of nine Cherenkov telescopes under construction at the Observatorio del Teide, with one of them already performing observations since November 2024. Given the complexity of the analysis of gamma-ray data acquired with Cherenkov telescopes, a proper evaluation of the quality of these data is important to avoid a negative impact on the high-level scientific products. There are several factors that can contribute to reducing the quality of the observations, such as clouds, high humidity or a high dust concentration in the air, among others. In order to take all these factors into account and evaluate their impact on the data, a quality check pipeline has been developed for ASTRI. This contribution describes the pipeline, from its inputs at different data levels to the production of outputs in the form of good-quality lists and diagnostic plots. We also show how setting preliminary quality cuts on the Crab Nebula data taken with the first ASTRI telescope can significantly improve the source detection.

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Publication Details

Published
2025-09-24
DOI
https://doi.org/10.22323/1.501.0767
Primary Topic
Medical Imaging Techniques and Applications
Type
article
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article

To cut or not to cut: Data-quality evaluation for the ASTRI Mini-Array

Simone Iovenitti, T. Mineo, Silvia Crestan, L. Foffano et al.
Medical Imaging Techniques and Applications
article

To cut or not to cut: Data-quality evaluation for the ASTRI Mini-Array

Simone Iovenitti, T. Mineo, Silvia Crestan, L. Foffano, F. Lucarelli, S. Lombardi, Edgar Molina
article en

Abstract

The ASTRI Mini-Array consists of nine Cherenkov telescopes under construction at the Observatorio del Teide, with one of them already performing observations since November 2024. Given the complexity of the analysis of gamma-ray data acquired with Cherenkov telescopes, a proper evaluation of the quality of these data is important to avoid a negative impact on the high-level scientific products. There are several factors that can contribute to reducing the quality of the observations, such as clouds, high humidity or a high dust concentration in the air, among others. In order to take all these factors into account and evaluate their impact on the data, a quality check pipeline has been developed for ASTRI. This contribution describes the pipeline, from its inputs at different data levels to the production of outputs in the form of good-quality lists and diagnostic plots. We also show how setting preliminary quality cuts on the Crab Nebula data taken with the first ASTRI telescope can significantly improve the source detection.

Openalex Percentile: Top 61%
Medical Imaging Techniques and Applications
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