Neuromorphic Readout for Hadron Calorimeters

• DOI: 10.48550/arxiv.2502.12693
• Publication Date: 2025-02-18
• Authors: Enrico Lupi; Abhishek; Max Aehle; Muhammad Awais; A. Breccia; Riccardo Carroccio; Long Chen; Abhijit Das; A. De Vita; T. Dorigo; Nicolas R. Gauger; R. Keidel; J. Kieseler; Anders Mikkelsen; Federico Nardi; Xuan Tung Nguyen; Fredrik Sandin; Kylian Schmidt; P. Vischia; Joseph Willmore
• Keywords: Neuromorphic engineering

We simulate hadrons impinging on a homogeneous lead-tungstate (PbWO4) calorimeter to investigate how the resulting light yield and its temporal structure, as detected by an array of light-sensitive sensors, can be processed neuromorphic computing system. Our model encodes photon distributions spike trains employs fully connected spiking neural network estimate total deposited energy, well position spatial distribution emissions within sensitive material. The extracted primitives offer valuable topological information about shower development in material, achieved without requiring segmentation active medium. A potential nanophotonic implementation using III-V semiconductor nanowires is discussed. It both fast energy efficient.