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

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.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-194876
Date January 2021
CreatorsGautam, Daniel
PublisherStockholms universitet, Fysikum
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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