Particle Identification with MLPs and PINNs Using HADES Data

Marvin Kohls

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arXiv · 2509.17685

Particle Identification with MLPs and PINNs Using HADES Data

Marvin Kohls

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Abstract

In experimental nuclear and particle physics, the extraction of high-purity samples of rare events critically depends on the efficiency and accuracy of particle identification (PID). In this work, we present a PID method applied to HADES data at the level of fully reconstructed particle track candidates. The results demonstrate a significant improvement in PID performance compared to conventional techniques, highlighting the potential of physics-informed neural networks as a powerful tool for future data analyses.

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Marvin Kohls. 2025-09-22. Particle Identification with MLPs and PINNs Using HADES Data. https://arxiv.org/abs/2509.17685

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