1 citations · 1 across the 4 of their papers we have counts for
4 papers
Potential periodic signals in blazars: significance, forecasting, and deep learning
M. A. Hashad, A. Hammad, Amr A. EL-Zant
Blazars exhibit variable emission on diverse timescales. Some light curves show signs of quasiperiodic oscillations (QPOs), which may encode clues regarding the physical processes…
Deep learning approaches to top FCNC couplings to photons at the LHC
Benjamin Fuks, Sumit K. Garg, A. Hammad +1
We investigate the sensitivity of the LHC to flavour-changing neutral current interactions involving the top quark and a photon using a model-independent effective field theory fra…
Progress in violating top-Higgs coupling at the LHC with Machine Learning
A. Hammad, Adil Jueid
A precise measurement of the top-Higgs coupling is essential in particle physics, as it offers a powerful probe of potential new physics beyond the Standard Model (BSM), particular…
Testing CP properties of the Higgs boson coupling to leptons with heterogeneous graphs
W. Esmail, A. Hammad, M. Nojiri +1
We explore the feasibility of measuring the CP properties of the Higgs boson coupling to leptons at the High Luminosity Large Hadron Collider (HL-LHC). Employing detailed Monte…