most citedUsing graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

3 citations · 3 across the 1 of their papers we have counts for

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2 papers

physics.ins-det2024★ 3 cited

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

M. Aamir, G. Adamov, T. Adams +568

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…

physics.ins-det2023

Characterization, Simulation and Test Beam Data Analysis of Stitched Passive CMOS Strip Sensors

I. Zatocilova, J. -H. Arling, M. Baselga +19

In the passive CMOS Strips Project, strip sensors were designed at the University of Bonn and produced by LFoundry in 150 nm technology, with an additional backside processing from…