Conveners
Astroparticle Physics / Space Weather
- Simone Riggi (Istituto Nazionale di Astrofisica (INAF))
Algorithms based on machine learning have been extraordinarily successful across many domains, including computer vision, machine translation, engineering, and science.
Moreover, in the physical sciences, the importance of machine learning is growing fast, driven by the necessity for precise and efficient algorithms that can effectively handle vast amounts of complex and high-dimensional...
Space-based experiments for direct detection of high-energy cosmic rays often employ optimized calorimeters, designed to achieve high energy resolution and broad acceptance capabilities. However, the significant volume of data collected demands innovative approaches for analysis and interpretation.
In this study, we introduce our efforts to develop an AI algorithm dedicated to classifying...
For tracking reconstruction purposes, various models inspired by computer vision applications have been studied, operating on an image-like representation of tracking detector data. Image-based methods encounter challenges in scaling up to realistic space experiment data due to high dimensionality and sparsity. Conversely, geometric deep learning methods such as graph neural networks (GNNs)...
The Cherenkov Telescope Array Observatory (CTAO) will provide incredible opportunities for the future of ground-based very-high-energy (VHE) gamma-ray astronomy. To optimise its scientific output, the CTAO will have a Science Alert Generation (SAG) system to reconstruct and analyse observations in real time, as part of the Array Control and Acquisition (ACADA) system. This work aims at...
