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Unfolding the W Boson Momentum: Neural Networks and Bayesian Iteration
In this article, we will discuss the current status of the W boson mass measurement, why we are interested in improving the measurement, and how we intend to do so. We propose two methods, neural networks and Bayesian iterations, which we have tested on both a toy model and Monte Carlo simulated dat...
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Lenguaje: | eng |
Publicado: |
2018
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Acceso en línea: | http://cds.cern.ch/record/2637818 |
Sumario: | In this article, we will discuss the current status of the W boson mass measurement, why we are interested in improving the measurement, and how we intend to do so. We propose two methods, neural networks and Bayesian iterations, which we have tested on both a toy model and Monte Carlo simulated data. Preliminary results show that these two methods in combination are promising for improving the W transverse momentum measurement. |
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