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Constructing Data-Driven Predictions at the Far Detector for NOvA's Neutrino Oscillation Analysis.

Conference ·
DOI:https://doi.org/10.2172/2405962· OSTI ID:2405962
NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters using $$\nu_\mu \ (\bar{\nu}_\mu)$$ disappearance and $$\nu_e \ (\bar{\nu}_e)$$ appearance data. The Neutrinos at Main Injector (NuMI) beamline at Fermilab provides a high purity 900 KW intense beam of neutrinos and anti-neutrinos to NOvA. The NOvA Near Detector, located 100m underground and 1km away from the beam source, observes the un-oscillated $$\nu_\mu \ (\bar{\nu}_\mu)$$ and beam $$\nu_e \ (\bar{\nu}_e)$$ event spectrum. The Far Detector, located in Ash River, MN, USA, is 809 km from the ND and records the oscillated $$\nu_e \ (\bar{\nu}_e)$$ and the un-oscillated $$\nu_\mu \ (\bar{\nu}_\mu)$$ event spectrum. NOvA uses a data-driven technique called extrapolation to predict the expected number of $$\nu_\mu \ (\bar{\nu}_\mu)$$ and $$\nu_e \ (\bar{\nu}_e)$$ events at the Far Detector using the Near Detector data. The use of data from a functionally equivalent Near Detector provides a powerful constraint on the systematic uncertainties in NOvA neutrino oscillation analyses. As NOvA continues to add data statistics, a robust constraint on systematics becomes more crucial for neutrino oscillation analysis. The details of the NOvA neutrino oscillation analysis framework and how it constrains dominant systematic uncertainties using the Near Detector data will be discussed in this poster.
Research Organization:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Contributing Organization:
NOvA
DOE Contract Number:
AC02-07CH11359
OSTI ID:
2405962
Report Number(s):
FERMILAB-POSTER-24-0137-PPD; oai:inspirehep.net:2808133
Country of Publication:
United States
Language:
English

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