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Cluster Reconstruction in Electromagnetic Calorimeters Using Machine Learning Methods
Kalina Dimitrova, Venelin Kozhuharov, Ruslan Nastaev +1
Machine-learning-based methods can be developed for the reconstruction of clusters in segmented detectors for high energy physics experiments. Convolutional neural networks with au…
Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors
Kalina Dimitrova, Venelin Kozhuharov, Peicho Petkov
Machine learning methods are being introduced at all stages of data reconstruction and analysis in various high-energy physics experiments. We present the development and applicati…
Characterization of the large-size NDL EQR20 silicon photomultipliers
Yu. A. Melikyan, I. G. Bearden, V. Buchakchiev +3
Unlike most commercially available silicon photomultipliers (SiPMs), EQR20 SiPMs produced by the Novel Device Laboratory (NDL) avoid using individual resistors to quench the avalan…
Application of the VMM ASIC for SiPM-based calorimetry
I. Bearden, V. Buchakchiev, A. Buhl +10
Highly integrated multichannel readout electronics is crucial in contemporary particle physics experiments. A novel silicon photomultiplier readout system based on the VMM3a ASIC w…