arXiv subjects

V. Pastore

Publications and source records attributed to V. Pastore.

3 recordsLinked to original sources

arXiv2025

The New Architecture of the Online Observation Quality System for the ASTRI Mini-Array Project

The ASTRI Mini-Array is an international collaboration led by the Italian National Institute for Astrophysics. The project aims to construct and operate an array of nine Imaging Atmospheric Cherenkov Telescopes to study gamma-ray sources at very high energy (TeV) and perform stellar intensity interferometry observations. We describe the updated Online Observation Quality System (OOQS) software architecture. The OOQS is one of the subsystems of the Supervisory Control and Data Acquisition (SCADA) system. It aims to execute real-time data quality checks on the data acquired by the Cherenkov cameras and intensity interferometry instruments and provide feedback to both SCADA and the Operator about abnormal conditions detected. The data quality results are stored in the Quality Archive for further investigation and sent to the Operator Human Machine Interface (HMI) through Kafka.

astro-ph.IM↗

arXiv2024

The Online Observation Quality System Implementation for the ASTRI Mini-Array Project

The ASTRI Mini-Array project, led by the Italian National Institute for Astrophysics, aims to construct and operate nine Imaging Atmospheric Cherenkov Telescopes for high-energy gamma-ray source study and stellar intensity interferometry. Located at the Teide Astronomical Observatory in Tenerife, the project's software is essential for remote operation, emphasizing the need for prompt feedback on observations. This contribution introduces the Online Observation Quality System (OOQS) as part of the Supervisory Control And Data Acquisition (SCADA) software. OOQS performs real-time data quality checks on data from Cherenkov cameras and Intensity Interferometry instruments. It provides feedback to SCADA and operators, highlighting abnormal conditions and ensuring quick corrective actions for optimal observations. Results are archived for operator visualization and further analysis. The OOQS data quality pipeline prototype utilizes a distributed application with three main components to handle the maximum array data rate of 1.15 Gb/s. The first is a Kafka consumer that manages the data stream from the Array Data Acquisition System through Apache Kafka, handling the data serialization and deserialization involved in the transmission. The data stream is divided into batches of data written in files. The second component monitors new files and conducts analyses using the Slurm workload scheduler, leveraging its parallel processing capabilities and scalability. Finally, the process results are collected by the last component and stored in the Quality Archive.

astro-ph.IM↗

arXiv2023

The Online Observation Quality System Software Architecture for the ASTRI Mini-Array Project

The ASTRI Mini-Array is an international collaboration led by the Italian National Institute for Astrophysics. This project aims to construct and operate an array of nine Imaging Atmospheric Cherenkov Telescopes to study gamma-ray sources at very high energy (TeV) and perform stellar intensity interferometry observations. We describe the software architecture and the technologies used to implement the Online Observation Quality System (OOQS) for the ASTRI Mini-Array project. The OOQS aims to execute data quality checks on the data acquired in real-time by the Cherenkov cameras and intensity interferometry instruments, and provides feedback to both the Central Control System and the Operator about abnormal conditions detected. The OOQS can notify other sub-systems, triggering their reaction to promptly correct anomalies. The results from the data quality analyses (e.g. camera plots, histograms, tables, and more) are stored in the Quality Archive for further investigation and they are summarised in reports available to the Operator. Once the OOQS results are stored, the operator can visualize them using the Human Machine Interface. The OOQS is designed to manage the high data rate generated by the instruments (up to 4.5 GB/s) and received from the Array Data Acquisition System through the Kafka service. The data are serialized and deserialized during the transmission using the Avro framework. The Slurm workload scheduler executes the analyses exploiting key features such as parallel analyses and scalability.

astro-ph.IM↗