Digital Calorimetry Using Pixel Sensors

M. Reicher

Research output: ThesisDoctoral thesis 1 (Research UU / Graduation UU)


The subject of this thesis is a new type of electromagnetic calorimeter, which is not based on proportionality of deposited energy, but instead on counting the number of showering particles. This calorimeter is a proof of principle for a proposed upgrade of the ALICE experiment at the Large Hadron Collider.

This thesis starts with giving the reader an understanding of the fundamental processes governing the development of electromagnetic showers, in order to correctly comprehend the effects underlying the performance of the calorimeter. It also aims to explain how the different choices in detector construction in combination with these processes affect the measurements of particles.

Next, the choice of detector components is explained as well as the working of these components. This is followed by the explanation of the software used and the different steps in both data processing and analysis are examined piece by piece and should give a prospective user of this software an understanding of the underlying principles.

This is followed by a discussion the simulation software used and the additions made to this software to fully model the behaviour of the sensors used in the prototype. The results of several analyses done on the data obtained from beamtests at both DESY and CERN, as well as compare these results with simulations done are discussed. This will test both the validity of the simulations as the quality of the beamtest results.

The conclusions drawn from the analyses will be used to give a final impression based on all results. A number of suggestions for future improvements to the prototype and detectors derived from the prototype will also be given.
Original languageEnglish
Awarding Institution
  • Utrecht University
  • Peitzmann, Thomas, Primary supervisor
  • Nooren, G.J.L., Co-supervisor
Award date7 Mar 2016
Print ISBNs978-94-028-0039-5
Publication statusPublished - 7 Mar 2016


  • Calorimetry
  • High Energy Physics
  • High Granularity
  • Particle Counting
  • CERN


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