A Data-Driven Method of Background Prediction at NOvA

NOvA is a long-baseline neutrino oscillation experiment that will use the NuMI beam originating at Fermilab. NOvA enables the study of two oscillation channels: \(\nu_{\mu}\) disappearance and \(\nu_{e}\) appearance. It consists of two functionally identical detectors, the near detector (ND) at Ferm...

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description NOvA is a long-baseline neutrino oscillation experiment that will use the NuMI beam originating at Fermilab. NOvA enables the study of two oscillation channels: \(\nu_{\mu}\) disappearance and \(\nu_{e}\) appearance. It consists of two functionally identical detectors, the near detector (ND) at Fermilab and the far detector (FD) near International Falls in Northern Minnesota. The ND will be used to study the neutrino beam spectrum and composition before oscillation, and measure background rate to the \(\nu_e\) appearance search. In this paper, I describe a data-driven technique to estimate the neutral current (NC) component of the ND spectrum. Using the \(\nu_{\mu}\) CC interactions where the reconstructed muon is removed from the event, we produce a well understood sample of hadronic showers that resemble NC interactions.
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title A Data-Driven Method of Background Prediction at NOvA
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