Neuromorphic Readout for Hadron Calorimeters

• URL: http://arxiv.org/abs/2502.12693v1
• Date: Tue, 18 Feb 2025 09:51:42 GMT
• Title: Neuromorphic Readout for Hadron Calorimeters
• Authors: Enrico Lupi, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Abhijit Das, Andrea De Vita, Tommaso Dorigo, Nicolas R. Gauger, Ralf Keidel, Jan Kieseler, Anders Mikkelsen, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore,
• Abstract summary: We simulate hadrons impinging on a homogeneous lead-tungstate (PbWO4 calorimeter) Our model encodes temporal photon distributions as spike trains and employs a fully connected spiking neural network to estimate the total deposited energy. A potential nanophotonic implementation using III-V semiconductor nanowires is discussed.
• Score: 31.796916051138663
• License:
• Abstract: 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 by a neuromorphic computing system. Our model encodes temporal photon distributions as spike trains and employs a fully connected spiking neural network to estimate the total deposited energy, as well as the position and spatial distribution of the light emissions within the sensitive material. The extracted primitives offer valuable topological information about the shower development in the material, achieved without requiring a segmentation of the active medium. A potential nanophotonic implementation using III-V semiconductor nanowires is discussed. It can be both fast and energy efficient.

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