4 papers
An investigation of fast simulation techniques for pion showers using kernel density estimators with the CALICE AHCAL Technological Prototype
CALICE Collaboration, A. Wilhahn, J. Utehs +29
In this article, the development and investigation of fast hadron shower simulation methods is presented. A test beam dataset has been recorded in 2018 at CERN with the AHCAL Techn…
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…
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…
Design, Construction and Commissioning of a Technological Prototype of a Highly Granular SiPM-on-tile Scintillator-Steel Hadronic Calorimeter
CALICE Collaboration
The CALICE collaboration is developing highly granular electromagnetic and hadronic calorimeters for detectors at future energy frontier electron-positron colliders. After successf…