Speakers
Description
The Cherenkov Telescope Array Observatory (CTAO) represents the next generation of ground-based gamma-ray telescopes, designed to probe the very-high-energy (VHE) sky above 20 GeV with unprecedented sensitivity. The northern array (CTAO-North) will be composed of an ensemble of Medium-Sized Telescopes (MSTs) and four Large-Sized Telescopes (LSTs), the latter designed to detect the lowest-energy gamma rays. Currently, only LST-1 is operational, while the remaining telescopes will come into operation in the coming years. Given the limited lifetime of the current cameras, new prototypes are being developed for the next generation of LSTs. The LST Advanced Camera (AdvCam), based on silicon photomultipliers, digitizes signals from nearly 8,000 pixels at a rate of 1 GHz, producing a data rate that requires highly efficient trigger systems, as the vast majority of recorded images correspond to Night Sky Background. Unlike previous LST cameras, AdvCam performs digitization prior to triggering, enabling the use of advanced online algorithms to improve sensitivity at the lowest energies. In this work, we study and compare different trigger algorithmic architectures, ranging from simple logical OR schemes to clustering algorithms and convolutional neural networks suitable for online inference, with particular emphasis on the computational constraints imposed by real-time operation at GHz sampling rates.