The new architecture design of the Science Alert Generation pipeline of the Cherenkov Telescope Array Observatory

Abstract: The Cherenkov Telescope Array Observatory (CTAO) represents the next-generation gamma-ray observatory and will operate for several decades. It will be particularly suited to analyse transients and variable phenomena, which will trigger real-time scientific alerts. To support this, the Science Alert Generation (SAG) pipeline within the Array Control and Data Acquisition (ACADA) system will process data from telescope arrays in real time, using dedicated pipelines for data reconstruction (SAG-RECO), data quality monitoring (SAG-DQ) and science monitoring (SAG-SCI). The Supervisor (SAG-SUP) oversees the dynamic operations of SAG and its integration with other ACADA components. SAG is designed to issue candidate science alerts within 20 s of data availability, processing events on multiple time scales (seconds to hours) and handling trigger rates of tens of kHz. Meeting these requirements necessitates optimised software and hardware architectures. This work presents recent developments in SAG's architecture, aimed at two main challenges: (1) selecting data only from telescopes that have entered a stable tracking state, even when they begin tracking at different times during multi-telescope observations, and (2) incorporating environmental and system monitoring information to ensure high data quality. SAG-SUP can retrieve real-time telescope status and environmental conditions from telescope managers and the weather station through the ACADA Monitoring system, collect them in a database and then use them to filter out data from slewing phases or degraded conditions. These enhancements are crucial to ensure the reliability of science alerts and improve the overall performance and responsiveness of the CTAO real-time analysis framework.