The CMS high granularity calorimeter (HGCAL) is an upgrade project for the High-Luminosity LHC (HL-LHC) that will provide unprecedented 5D imagining capabilities for particle showers with a total of 6 million channels. Beam tests with up to 12 thousand channels were performed at CERN in 2018. This talk will briefly describe the calorimeter project and give a glance on how the test beam data can be analysed with the python pandas framework.
Artur Lobanov is a Marie Curie Postdoctoral Fellow at LLR École Polytechnique, working on novel techniques for particle detectors – high granularity imaging calorimeters for future colliders. He is currently co-convening the (HGCAL) system tests working group, leading an international team of young researchers. He is also working on novel algorithms for particle reconstruction and identification, as well as evaluating electronics for detector readout.
Jonas Rembser
