Energy reconstruction and particle identification in a high granularity semi-digital hadronic calorimeter
(2017)
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- Authors
- Supervisors
- Cortina, Eduardo
- Abstract
- This thesis presents studies on various energy reconstruction methods of hadronic showers and Particle identification within a Semi-Digital Hadronic CALorimeter (SDHCAL) proposed for the future electron-positron collider ILC. The SDHCAL technological prototype is the first of a series of new-generation detectors fulfilling almost all the ILC requirements. Beside its semi-digital readout, the main feature of SDHCAL is its high granularity allowing imaging capabilities required for the application of the particle flow algorithm (PFA) in order to improve the jet energy resolution. The SDHCAL technological prototype has been tested successfully in beam tests at CERN and shows good performance. An exhaustive study on the optimization of the energy reconstruction of hadronic showers using GEANT4 simulation is presented and confirms the important impact on energy resolution of a semi-digital readout. Different analytic methods have been developed for the energy reconstruction within the multi-threshold mode of SDHCAL. A further approach based on NeuralNetwork has been also studied. An analysis investigating the energy resolution of pion showers recorded in SDHCAL during beam tests at CERN, has been presented. A linear response and a good energy resolution are obtained for a large range of hadronic energies for both the Digital and the Semi-Digital modes of the SDHCAL prototype. The Semi-Digital mode shows however better performance at energies exceeding 30 GeV. Neural network technique provided a significant improvement of the energy resolution and linearity in comparison with the ones acquired with the analytic methods. Finally, a particle classifier based on Multivariate techniques and using informations provided by our high granularity calorimeter is developed in this work and shows promising results.
- Affiliations
Citations
Mannai, S. (2017). Energy reconstruction and particle identification in a high granularity semi-digital hadronic calorimeter. https://hdl.handle.net/2078.5/60205