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Machine learning enhances data reconstruction for silicon sensors in high energy physics

By PulseAugur Editorial · [2 sources] ·

Researchers have developed machine learning techniques to improve data reconstruction and compression for resistive silicon sensors used in high energy physics. The study explores recurrent neural networks, specifically LSTM layers, for full-waveform reconstruction and considers their deployment on field-programmable gate arrays (FPGAs). Additionally, the work investigates transformer-based architectures that are topology-agnostic, aiming to maintain high position resolution and guide future sensor designs. AI

IMPACT This research could lead to more efficient data processing and improved spatial resolution in detectors for high energy physics experiments.

RANK_REASON The cluster contains an academic paper detailing novel research methods.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Machine learning enhances data reconstruction for silicon sensors in high energy physics

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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Alexander Aoki, Gaetano Barone, Leena Diehl, Gabriele Giacomini, Vagelis Gkougkousis, Hanshal Goyal, Rohan Kher, Daniel Li, Anna Macchiolo, Yevhenii Padnuik, Daria Senina, Samantha Sunnarborg, Jessica Tang, Alessandro Tricoli, Lixing Wang, Don C. Wong ·

    Machine Learning-Based Reconstruction for Resistive Silicon Sensors

    arXiv:2607.11585v1 Announce Type: cross Abstract: Low-Gain Avalanche Diodes (LGADs) and AC-coupled Low-Gain Avalanche Diodes (AC-LGADs) are promising technologies for precision timing and four-dimensional tracking. In AC-LGADs, the AC pad is coupled to the resistive n$^{+}$ layer…

  2. arXiv cs.LG TIER_1 English(EN) · Don C. Wong ·

    Machine Learning-Based Reconstruction for Resistive Silicon Sensors

    Low-Gain Avalanche Diodes (LGADs) and AC-coupled Low-Gain Avalanche Diodes (AC-LGADs) are promising technologies for precision timing and four-dimensional tracking. In AC-LGADs, the AC pad is coupled to the resistive n$^{+}$ layer through a dielectric layer, while the gain layer …

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