Learning from ASTRI-Horn: products and applications of Variance data

TL;DR

This paper discusses the implementation and application of Variance mode data from the ASTRI-Horn prototype, enhancing telescope monitoring and sky condition assessment during Cherenkov observations.

Contribution

It introduces new algorithms and processing pipelines for Variance data, improving real-time telescope health monitoring and sky condition evaluation.

Findings

Variance data can infer telescope mis-pointing and background levels.

Online processing enables real-time sky condition assessment.

Enhanced monitoring supports optimal Cherenkov data collection.

Abstract

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.