Stimulated neutrino transformation through turbulence on a changing density profile and application to supernovae
Kelly M. Patton, James P. Kneller, Gail C. McLaughlin

TL;DR
This paper develops a model to predict stimulated neutrino transitions caused by turbulence in supernovae, explaining how turbulence parameters influence neutrino flavor transformations and applying it to simulation data.
Contribution
It introduces a method to predict neutrino transition locations in turbulent supernova environments and analyzes how turbulence spectrum parameters affect these transitions.
Findings
The model accurately predicts transition locations compared to numerical calculations.
Large amplitude turbulence increases both the number and amplitude of neutrino transitions.
Long wavelength turbulence suppresses neutrino transitions, explaining minimal effects in supernova simulations.
Abstract
We apply the model of stimulated neutrino transitions to neutrinos traveling through turbulence on a non-constant density profile. We describe a method to predict the location of large amplitude transitions and demonstrate the effectiveness of this method by comparing to numerical calculations using a model supernova (SN) profile. The important wavelength scales of turbulence, both those that stimulate neutrino transformations and those that suppress them, are presented and discussed. We then examine the effects of changing the parameters of the turbulent spectrum, specifically the root-mean-square amplitude and cutoff wavelength, and show how the stimulated transitions model offers an explanation for the increase in both the amplitude and number of transitions with large amplitude turbulence, as well as a suppression or absence of transitions for long cutoff wavelengths. The method can…
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