Investigating the Violation of Charge Parity Symmetry Through Top Quark Chromo-Electric Dipole Moments by Using Machine Learning Techniques

• Published in: arXiv.org 2023-06
• Main Authors: Işıldak, B, Hayreter, A, Hüdaverdi, M, Ilgın, F, Salva, S, E \c{S}imşek, Güyer, S
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Asymmetry; Cross-sections; Dipole moments; Electric dipoles; Large Hadron Collider; Machine learning; Parity; Quarks; Standard model (particle physics)
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2306.11683

There are a number of studies in the literature on search for Charge-Parity (CP) violating signals in top quark productions at the LHC. In most of these studies, ChromoMagnetic Dipole Moments (CMDM) and ChromoElectric Dipole Moments (CEDM) of top quarks is bounded either by deviations from the Standard Model (SM) cross sections or by T-odd asymmetries in di-muon channels. However, the required precision on these cross section values are far beyond from that of ATLAS or CMS experiments can reach. In this letter, the investigation of CEDM based asymmetries in the semileptonic top pair decays are presented as T-odd asymmetries in CMS experiment. Expected asymmetry values are determined at the detector level using MadGraph5, Pythia8 and Delphes softwares along with the discrimination of the signal and the background with Deep Neural Networks (DNN).