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Effective Field Theory And Machine Learning Approaches To Controlling Nonperturbative Uncertainties In Flavor Physics, Ayesh Gunawardana

Wayne State University Dissertations

The radiative decay $\bar{B}\to X_s\gamma$ and semileptonic heavy meson decay $D\to \pi l \nu$ are important flavor physics probes of new physics. However, these decays are plagued with nonperturbative uncertainties that are needed to be controlled to obtain a theoretically clean description. In this dissertation, we provide effective field theory and machine learning approaches to controlling these uncertainties.\par

In $\bar B\to X_s\gamma$, the largest uncertainty on the total rate and the CP asymmetry arises from resolved photon contributions. These appear first at order $1/m_b$ and are related to operators other than $Q_{7\gamma}$ in the effective weak Hamiltonian. One of the …