Search for Electroweak SUSY and Dark Higgs Boson with the CMS Experiment

Searches for new physics beyond the standard model are essential in understanding electroweak symmetry breaking and dark matter. Our analysis focuses on the signatures predicted by electroweak SUSY and dark Higgs models using the proton-proton collision data collected by the CMS detector. We present the current status of the analysis involving chargino or neutralino pair production and dark Higgs, which further decays to vector-boson pairs such as WW, WH, WZ, ZH, and ZZ, along with the missing energy. We utilize a machine learning algorithm based on graph neural networks, particleNet, to identify vector bosons and improve signal sensitivity to boosted topologies. We will discuss the tagger performance, various signal regions, and the background estimation strategy developed for this analysis.