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Main Authors: Iovenitti, Simone, Crestan, Silvia, Mineo, Teresa, Leto, Giuseppe, Giuliani, Andrea, Lombardi, Saverio
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.17392
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author Iovenitti, Simone
Crestan, Silvia
Mineo, Teresa
Leto, Giuseppe
Giuliani, Andrea
Lombardi, Saverio
author_facet Iovenitti, Simone
Crestan, Silvia
Mineo, Teresa
Leto, Giuseppe
Giuliani, Andrea
Lombardi, Saverio
contents In the context of the ASTRI MiniArray project (9 dual-mirror air Cherenkov telescopes being installed at the Observatorio del Teide in the Canary Islands), the ASTRI- Horn prototype was previously implemented in Italy (Sicily). It was a crucial test bench for establishing observation strategies, hardware upgrades, and software solutions. Specifically, during the winter 2022/2023 observing campaign, we implemented significant enhancements in using the so-called Variance mode, an auxiliary output of the ASTRI Cherenkov camera able to take images of the night sky background in the near UV/visible band. Variance data are now processed online and on site using a dedicated pipeline and stored in tech files. This data can infer possible telescope mis-pointing, background level, number of identified stars, and point spread function. In this contribution, we briefly present these quantities and their importance together with the algorithms adopted for their calculation. They provide valuable monitoring of telescope health and sky conditions during scientific data collection, enabling the selection of optimal time sequences for Cherenkov data reduction.
format Preprint
id arxiv_https___arxiv_org_abs_2507_17392
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Learning from ASTRI-Horn: products and applications of Variance data
Iovenitti, Simone
Crestan, Silvia
Mineo, Teresa
Leto, Giuseppe
Giuliani, Andrea
Lombardi, Saverio
Instrumentation and Methods for Astrophysics
High Energy Astrophysical Phenomena
In the context of the ASTRI MiniArray project (9 dual-mirror air Cherenkov telescopes being installed at the Observatorio del Teide in the Canary Islands), the ASTRI- Horn prototype was previously implemented in Italy (Sicily). It was a crucial test bench for establishing observation strategies, hardware upgrades, and software solutions. Specifically, during the winter 2022/2023 observing campaign, we implemented significant enhancements in using the so-called Variance mode, an auxiliary output of the ASTRI Cherenkov camera able to take images of the night sky background in the near UV/visible band. Variance data are now processed online and on site using a dedicated pipeline and stored in tech files. This data can infer possible telescope mis-pointing, background level, number of identified stars, and point spread function. In this contribution, we briefly present these quantities and their importance together with the algorithms adopted for their calculation. They provide valuable monitoring of telescope health and sky conditions during scientific data collection, enabling the selection of optimal time sequences for Cherenkov data reduction.
title Learning from ASTRI-Horn: products and applications of Variance data
topic Instrumentation and Methods for Astrophysics
High Energy Astrophysical Phenomena
url https://arxiv.org/abs/2507.17392