Inference of bipolar neutrino flavor oscillations near a core-collapse supernova, based on multiple measurements at Earth
Eve Armstrong, Amol V. Patwardhan, A.A. Ahmetaj, M., Margarette Sanchez, Sophia Miskiewicz, Marcus Ibrahim, Ishaan Singh

TL;DR
This paper explores using statistical data assimilation to infer bipolar neutrino oscillations in supernovae from Earth-based measurements, demonstrating potential to detect and characterize such oscillations remotely.
Contribution
It introduces a cost-function based SDA approach to infer neutrino flavor evolution, including bipolar oscillations, from limited observational data in a simplified model.
Findings
SDA can determine if bipolar oscillations occurred in the supernova envelope.
Full amplitude sampling allows accurate prediction of oscillation amplitude.
Method complements numerical models by inferring inaccessible flavor evolution.
Abstract
Neutrinos in compact-object environments, such as core-collapse supernovae, can experience various kinds of collective effects in flavor space, engendered by neutrino-neutrino interactions. These include "bipolar" collective oscillations, which are exhibited by neutrino ensembles where different flavors dominate at different energies. Considering the importance of neutrinos in the dynamics and nucleosynthesis in these environments, it is desirable to ascertain whether an Earth-based detection could contain signatures of bipolar oscillations that occurred within a supernova envelope. To that end, we continue examining a cost-function formulation of statistical data assimilation (SDA) to infer solutions to a small-scale model of neutrino flavor transformation. SDA is an inference paradigm designed to optimize a model with sparse data. Our model consists of two mono-energetic neutrino…
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