Speaker
Description
Atmospheric neutrinos have yielded groundbreaking discoveries in particle
physics, providing compelling evidence for neutrino mass and emphasizing the
importance of probing neutrino oscillations in diverse environments. The Deep
Underground Neutrino Experiment (DUNE) boasts an extensive oscillation
program with atmospheric neutrinos, employing innovative, low threshold, high
spatial resolution detectors with great potential for high energy and angular
resolutions. As neutrinos traverse the Earth, the matter potential influences their
oscillation probabilities in intricate ways, enhancing and suppressing the
conversion of one neutrino's flavor to another along the propagation. The first
module of DUNE's Far Detectors (FD) is expected to begin operation in 2029 so
atmospheric neutrinos will be the first FD neutrino data of the collaboration.
Therefore, comprehending their behavior within Earth's complex density
profile, primarily described by the Preliminary Reference Earth Model (PREM),
is essential for accurately describing oscillations and determining expected
event rates in the FD. In this study, we address this challenge by considering an
ensemble of Earth models constrained by astronomical measurements of the
planet's mass and moment of inertia. We evaluate how variations in densities
and layer boundaries can affect oscillation probabilities and event rates, and
what implications this could have on various physics analyses. Thus, this work
not only enhances our understanding of atmospheric neutrino oscillations, but
also provides crucial information for future studies and experimental endeavors
in DUNE. This includes implications for oscillation physics, as uncertainties in
matter densities may directly impact sensitivity analyses, alongside BSM
searches, where atmospheric neutrinos serve as a primary source of background.
This work also serves as a starting point for a study of Neutrino Tomography of
the Earth, where we can count events in specific energy and angular bins while
making use of statistical methods to infer the density and composition of the
planet's layers.
