Search for Upward-Going Muons from Dark Matter in CMS

Some theories predict that dark matter could inelastically scatter off of atoms in the Earth and lose enough kinetic energy to become gravitationally trapped inside the Earth. Dark matter and dark anti-matter would then annihilate into dark photons which kinetically mix with Standard Model photons. These photons would produce pairs of fermions which would look to come up from underground. We present a search for these upward-going fermions, specifically muons, in Muon DT Chamber data collected by CMS during Cosmic runs. The search utilizes a Boosted Decision Tree (BDT) and Recurrent Neural Network (RNN) to increase background-signal discrimination. In this talk, we will present the current status and an estimated sensitivity of the search.