Název anglicky / Title English: Machine learning application for the Electron Ion Collider
Osnova / Outline:
The Electron Ion Collider (EIC) is planned to address fundamental questions on internal structure of protons and nuclei as well as on many aspects of electromagnetic and nuclear forces . One of key features of the EIC is its ability to detect electrons scattered at very small angles . In such a case the detection and reconstruction requires the use of machine learning methods.
The thesis will focus on introduction to the methods, their testing in detector simulations  and potential further development. The course of the thesis will be coordinated with a dedicated working group within the EIC project.
Říjen/Listopad: General introduction to the EIC project and detector simulations
Listopad/Prosinec: Introduction to simulation tools, reproduction of several basic results
Prosinec/Leden: Writing down first parts of the thesis, talk at the winter workshop
Únor/Duben: Application of the machine learning to several scenarios, evaluation and potential development
Duben/Květen: Writing down the thesis
Literatura / reference:
 R. Abdul Khalek et al.: Science Requirements and Detector Concepts
for the Electron-Ion Collider: EIC Yellow Report,
 J. Adam: GETaLM: A generator for electron tagger and luminosity
monitor for electron - proton and ion collisions,
Comput.Phys.Commun. 272 (2022) 108251, arXiv:2105.10570
 C. Grupen, B. Shwartz, Particle detectors, Cambridge University