English

From oscillation dip to oscillation valley in atmospheric neutrino experiments

High Energy Physics - Phenomenology 2021-03-10 v2 High Energy Physics - Experiment Instrumentation and Detectors

Abstract

Atmospheric neutrino experiments can show the "oscillation dip" feature in data, due to their sensitivity over a large L/EL/E range. In experiments that can distinguish between neutrinos and antineutrinos, like INO, oscillation dips can be observed in both these channels separately. We present the dip-identification algorithm employing a data-driven approach -- one that uses the asymmetry in the upward-going and downward-going events, binned in the reconstructed L/EL/E of muons -- to demonstrate the dip, which would confirm the oscillation hypothesis. We further propose, for the first time, the identification of an "oscillation valley" in the reconstructed (EμE_\mu,cosθμ\,\cos\theta_\mu) plane, feasible for detectors like ICAL having excellent muon energy and direction resolutions. We illustrate how this two-dimensional valley would offer a clear visual representation and test of the L/EL/E dependence, the alignment of the valley quantifying the atmospheric mass-squared difference. Owing to the charge identification capability of the ICAL detector at INO, we always present our results using μ\mu^{-} and μ+\mu^{+} events separately. Taking into account the statistical fluctuations and systematic errors, and varying oscillation parameters over their currently allowed ranges, we estimate the precision to which atmospheric neutrino oscillation parameters would be determined with the 10-year simulated data at ICAL using our procedure.

Keywords

Cite

@article{arxiv.2006.14529,
  title  = {From oscillation dip to oscillation valley in atmospheric neutrino experiments},
  author = {Anil Kumar and Amina Khatun and Sanjib Kumar Agarwalla and Amol Dighe},
  journal= {arXiv preprint arXiv:2006.14529},
  year   = {2021}
}

Comments

27 pages, 11 figures, 5 tables, comments are welcome. Matches with the published version