Download or read book QCD+QED Simulations with C* Boundary Conditions written by Jens Lücke and published by . This book was released on 2023* with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Englische Version: Particle physics research employs two primary approaches for discoveries: direct and indirect searches. Direct searches aim to directly observe phenomena, while indirect searches seek discrepancies between theoretical predictions and experimental results. With the discovery of the Higgs boson, the standard model of particle physics was completed, shifting the focus towards indirect searches due to the lack of compelling evidence for new physics at current energy scales. These searches necessitate highly precise theoretical predictions, particularly for non-perturbative hadronic observables, which are calculated using lattice QCD simulations. The need for sub-percent precision has highlighted the importance of accounting for radiative and isospin-breaking corrections, leading to the simulation of fully dynamical QCD+QED. This thesis addresses the challenges of incorporating QED into lattice QCD, focusing on an approach that maintains gauge invariance, locality, and translational invariance using QED with C-parity boundary conditions (QED$_C$). It presents a comprehensive technical analysis of the first large-scale QCD+QED$_C$ simulations, detailing eight fully dynamical gauge field ensembles with various renormalized electric coupling values ($\alpha_\mathrm{R} \in \{0,1/137,0.04\}$), consistent pion mass ($m_\pi \approx 400$ MeV), and lattice spacing ($a\approx 0.05$ fm). The thesis examines the stability of the simulation algorithm, finite volume effects, and the behavior of different hadron masses. Furthermore, it elaborates on the tuning of input parameters for lattice simulations to replicate real-world physics accurately, focusing on the hadronic renormalization scheme used to fix bare quark masses. It introduces an optimized strategy for tuning QCD+QED parameters via mass reweighting, adapted for simulations using the RHMC algorithm, highlighting its development, implementation, and testing.