Limits on the parameter space of (3+2) sterile neutrino scenario by IceCube data
Emilse Cabrera, Arman Esmaili, Alexander A. Quiroga

TL;DR
This paper investigates the constraints on a (3+2) sterile neutrino model using IceCube atmospheric neutrino data, providing limits on the parameter space and facilitating combined analyses with short baseline experiments.
Contribution
It presents the first comprehensive analysis of IceCube data to set bounds on models with two sterile neutrinos, including systematic uncertainties and flux variations.
Findings
Limits on (3+2) sterile neutrino parameters derived from IceCube data.
Provided $hi^2$ tables for joint analysis with other experiments.
Enhanced understanding of sterile neutrino effects on high-energy atmospheric neutrinos.
Abstract
The neutrino sector of the standard model of particles can contain more than one sterile neutrino states. Generally, existence of more sterile states leads to better, or at least equally good, fit to the short baseline anomalous data due to the larger number of parameters and interferences which create features in the oscillation pattern. However, for experiments like IceCube, where the sterile states distort the oscillation pattern of high energy atmospheric neutrinos through parametric and MSW resonances, addition of more sterile states leads to a more intense effect. Although the limits on one additional sterile neutrino state by IceCube data have been studied in the literature, bounds on the models with more sterile states are lacking. We analyze the one-year data set of atmospheric neutrinos collected by IceCube during the 2011-2012 and derive the limits on the parameter space of…
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.
Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Neutrino Physics Research · Computational Physics and Python Applications
