Search for Stop using Machine Learning : A Bachelors Project in Physics

Sammanfattning: In this thesis the application of machine learning algorithms as a tool in the search for top squark is studied. Two neural network models are trained with simulated stop events as signal against dileptonic and semi-leptonic top pair production events as background. There is a substantial class imbalance between the number of signal and background samples that are used. The performance of the neural network models are compared to the performance of a cut and count method. None of the models outperform the standard cut and count method.