arXiv Open Access 2025

Rings of Light, Speed of AI: YOLO for Cherenkov Reconstruction

Martino Borsato Giovanni Laganà Maurizio Martinelli

Lihat Sumber

Abstrak

Cherenkov rings play a crucial role in identifying charged particles in high-energy physics (HEP) experiments. Most Cherenkov ring pattern reconstruction algorithms currently used in HEP experiments rely on a likelihood fit to the photo-detector response, which often consumes a significant portion of the computing budget for event reconstruction. We present a novel approach to Cherenkov ring reconstruction using YOLO, a computer vision algorithm capable of real-time object identification with a single pass through a neural network. We obtain a reconstruction efficiency above 95% and a pion misidentification rate below 5% across a wide momentum range for all particle species.

Topik & Kata Kunci

hep-ex

Penulis (3)

Martino Borsato

Giovanni Laganà

Maurizio Martinelli

Format Sitasi

APA MLA BibTeX

Borsato, M., Laganà, G., Martinelli, M. (2025). Rings of Light, Speed of AI: YOLO for Cherenkov Reconstruction. https://arxiv.org/abs/2509.26273

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓