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Contribution Poster accelerator

Poster (participating in poster prize competition)

Data-driven Techniques for $\nu_e$ Signal and Background Predictions in NO$\nu$A


  • Ms. Shiqi YU
  • Mr. Tomas NOSEK

Primary authors

  • Ms. Shiqi YU (Argonne National Lab/ Illinois Institute of Technology)
  • Mr. Tomas NOSEK (Charles University, Institute of Particle and Nuclear Physics)

Authorship annotation

for the NO$\nu$A collaboration

Session and Location

Wednesday Session, Poster Wall #80 (Auditorium Gallery Left)

Abstract content

NO$\nu$A is a long baseline neutrino oscillation experiment, using two functionally identical detectors to measure $\nu_e$ appearance and $\nu_\mu$ disappearance at the Far Detector (FD) with the NuMI Beam at Fermilab. The Near Detector (ND) measures the beam before oscillations, which will allow us to make a measurement of the signal flux before it has oscillated and the background components which can mimic $\nu_e$ at our FD. We use the ND in three different ways to predict the amount of signal and background expected at the FD to partially cancel systematic uncertainties. The background prediction has three components: Charged Current (CC) $\nu_\mu$, $\nu_e$ and Neutral Current (NC) events. We need to determine the fraction of the selected ND sample in each of these components because some oscillate significantly (CC $\nu_\mu$) and some do not oscillate at all (NC). This poster will present details of these three data-driven techniques for predicting the FD spectrum.

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