activity
20172024
collaborators

6 papers

physics.ins-det2024

Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning

S. Lai, J. Utehs, A. Wilhahn +48

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to se…

physics.ins-det2024

Software Compensation for Highly Granular Calorimeters using Machine Learning

S. Lai, J. Utehs, A. Wilhahn +61

A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event in…

physics.ins-det2022

Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20300 GeV/c

B. Acar, G. Adamov, C. Adloff +454

The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimete…

physics.ins-det2017

Construction and Response of a Highly Granular Scintillator-based Electromagnetic Calorimeter

CALICE collaboration, J. Repond, L. Xia +78

A highly granular electromagnetic calorimeter with scintillator strip readout is being developed for future lepton collider experiments. A prototype of 21.5 depth and $180 \t…

nucl-ex2017

Determination of N* amplitudes from associated strangeness production in p+p collisions

R. Münzer, L. Fabbietti, E. Epple +65

We present the first determination of the energy-dependent production amplitudes of N resonances with masses between 1650 MeV/c and 1900 MeV/c for an excess energ…

physics.ins-det2017

Tracking within Hadronic Showers in the CALICE SDHCAL prototype using a Hough Transform Technique

The CALICE Collaboration

The high granularity of the CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) provides the capability to reveal the track segments present in hadronic showers. These segments are t…