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PhD. Topics

Institute of Experimental Physics

Topic
Study of top quark properties in proton-proton collisions in ATLAS experiment
PhD. program
Nuclear and subnuclear physics
Year of admission
2026
Name of the supervisor
RNDr. Pavol Stríženec, CSc.
Contact:
Receiving school
Faculty of Science, P.J. Safarik University
Annotation
Top quark, is the heaviest of all known quarks with extraordinary properties for analysis of processes which could reveal physics beyond Standard Model (SM), eventually they could predict SM parameters with higher precision. ATLAS detector is delivering top quark production and its decay products data at highest energies ever and with high statistics. There is a need to analyze these data for many processes (cross-sections, spin correlations, branching ratios,..), as well as to repeat the analyses with higher precision and at lower energies and smaller statistics. The PhD study will be focused on methodological tasks of ATLAS calorimetry (contribution to data quality improvement in the high luminosity environment of the future HL-LHC accelerator), as well as on some of these data analyses (according to the collaboration needs and ability). The work supposes to acquire knowledge of programming in the ROOT analysis environment and in the ATLAS software environment (python and C++). The understanding of theoretical SM prediction will also be needed, as well as good communication skills in English (frequent presentations on collaboration meetings). Visits to CERN and participation on international conferences and workshops is assumed during the study.

Refernces:
[1] ATLAS Collaboration Climbing to the Top of the ATLAS 13 TeV data,
https://arxiv.org/abs/2404.10674
[2] F. Deliot, N. Hadley, S. Parke, T. Schwarz, Properties of the Top Quark,
https://arxiv.org/pdf/1803.00656
[3] P. Ferreira da Silva, Physics of the Top Quark at the LHC, Annual Review of Nuclear and Particle Science, 2023.73:255-284
[4] The ATLAS Experiment at the CERN Large Hadron Collider: A Description of the Detector Configuration for Run 3, https://arxiv.org/pdf/2305.16623
[5] https://root.cern.ch/ data analysis framework