Precision meets sustainability at the LHC : extraction of fundamental parameters of the Standard Model and machine learning techniques in the simulation / vorgelegt von Valentina Guglielmi. Hamburg, 2025
Inhalt
- Introduction
- The Standard Model and its parameters
- Standard Model of particle physics
- Quantum chromodynamics
- Unified electroweak theory
- EW symmetry breaking and mass generation
- The stability of the electroweak vacuum
- Phenomenology of hadronic collisions
- Physics at hadron colliders
- Constraining PDFs from experimental data
- Monte Carlo simulations
- Jets and S
- The top quark mass and width
- CMS at the LHC
- The Large Hadron Collider
- The Compact Muon Solenoid experiment
- The event reconstruction in CMS
- The High Luminosity LHC upgrade
- The CPU demand and sustainability
- ML techniques to reweight simulated events at the LHC
- Machine learning
- Reweighting techniques
- Deep neural network using classification for tuning and reweighting (DCTR)
- Reweighting of systematics uncertainties
- Reweighting to alternative model
- Implementation in CMS software framework
- Conclusions and prospects
- Measurement of the top quark mass and width from tt +tW events
- Theoretical predictions for tt +tW process
- Analysis strategy
- Data set, event selection, and MC simulation
- Systematic uncertainties
- Unfolding and cross section measurement
- Extraction of the top quark mass and width
- Extraction of S and illustration of its running by using inclusive jet production
- The xFitter framework for QCD analyses
- Data used in the QCD analysis
- Theoretical predictions for inclusive jets
- QCD analysis
- Results on PDFs and S (mZ)
- Running of S
- Summary and conclusions