Speaker
Description
Since the discovery of the Higgs boson in 2012 at the CERN LHC, the Standard Model has been proven to describe most of the observed phenomena up to the TeV scale. However, there are still important aspects of modern science that are not covered by this theory, such as dark matter and the nature of gravity. Many beyond-the-Standard Model (BSM) theories attempt to include these aspects by predicting additional spin-0 or spin-2 particles coupling to the HH/HY. This presentation will introduce various analyses of the resonance decays to double Higgs at the CMS experiment.
Machine learning methods have now been widely applied. The Diffusion model can be used to simulate the energy deposition distribution of high-energy electrons or photons in electromagnetic calorimeters. By incorporating the Diffusion model into simulations, it is possible to predict the energy deposition distribution more quickly and accurately, thereby improving the efficiency of Monte Carlo (MC) generation.
