Signal and background discrimination for two-electron events in LDMX using a Boosted Decision Tree
The Light Dark Matter Experiment (LDMX) is a fixed target experiment that will search for dark matter, but is still in the development phase. An important aspect for the experiment is the discrimination of signal and background events. Here this signal and background discrimination is inspected using a machine learning technique called a Boosted Decision Tree (BDT). This is done using Monte Carlo