Measuring the Polarization Reconstruction Resolution of the ARIANNA Neutrino Detector with Cosmic Rays
ARIANNA Collaboration: A. Anker, P. Baldi, S. W. Barwick, J. Beise, D., Z. Besson, S. Bouma, M. Cataldo, P. Chen, G. Gaswint, C. Glaser, A. Hallgren,, S. Hallmann, J. C. Hanson, S. R. Klein, S. A. Kleinfelder, R. Lahmann, J., Liu, M. Magnuson, S. McAleer, Z. S. Meyers, J. Nam

TL;DR
This study evaluates the polarization reconstruction resolution of the ARIANNA neutrino detector using cosmic-ray air showers as proxies, demonstrating a resolution of around 2.5 degrees, improved to 1.3 degrees for certain event angles.
Contribution
It introduces a method to assess ARIANNA's polarization reconstruction capabilities using cosmic rays, providing empirical resolution measurements and insights into emission effects.
Findings
Polarization can be reconstructed with 2.5° resolution for high-quality cosmic-ray events.
Selecting events with zenith angles >70° reduces polarization uncertainty to 1.3°.
Simulation results agree with the measured performance of the detector.
Abstract
The ARIANNA detector is designed to detect neutrinos with energies above eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams for neutrino detectors. Some ARIANNA detector stations are equipped with antennas capable of detecting air showers. Since the radio emission properties of air showers are well understood, and the polarization of the radio signal can be predicted from the arrival direction, cosmic rays can be used as a proxy to assess the reconstruction capabilities of the ARIANNA neutrino detector. We report on dedicated efforts of reconstructing the polarization of cosmic-ray radio pulses. After correcting for difference in hardware, the two stations used in this study showed similar performance in terms of event rate and agreed with simulation. Subselecting high quality cosmic rays, the polarizations of these cosmic rays were…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
