Machine Learning Multi-Stage Classification and Regression in the Search for Vector-like Quarks and the Neyman Construction in Signal Searches

Machine Learning Multi-Stage Classification and Regression in the Search for Vector-like Quarks and the Neyman Construction in Signal Searches

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A search for vector-like quarks (VLQs) decaying to a Z boson using multi-stage machine learning was compared to a search using a standard square cuts search strategy. VLQs are predicted by several new theories beyond the Standard Model. The searches used 20.3 inverse femtobarns of proton-proton coll...

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Bibliographic Details
Main Author: Leone, Robert Matthew
Other Authors: Cheu, Elliot C.
Language:en_US
Published: The University of Arizona. 2016
Subjects:
Learning Algorithm
Machine Learning
Multi-Stage
Neyman Construction
Vector-like Quark
Physics
Boosted Decision Trees
Online Access:http://hdl.handle.net/10150/621827
http://arizona.openrepository.com/arizona/handle/10150/621827

Internet

http://hdl.handle.net/10150/621827
http://arizona.openrepository.com/arizona/handle/10150/621827

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