Quasi-steady evolution of fast neutrino-flavor conversions

TL;DR

This paper investigates the quasi-steady evolution of fast neutrino-flavor conversions in astrophysical environments, proposing a new phenomenological model that aligns well with numerical simulations and enhances understanding of flavor dynamics.

Contribution

It introduces a novel phenomenological model for the quasi-steady evolution of fast neutrino-flavor conversions, supported by numerical simulations and analytical insights.

Findings

The new model accurately reproduces numerical simulation results.

The convolution term of spatial wave number is expressed in a concise analytical form.

The model provides insights into non-linear feedback mechanisms in flavor conversions.

Abstract

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions' effects in the theoretical modeling of CCSN and BNSM. Some phenomenological schemes have shown good performance in approximating asymptotic states of fast neutrino-flavor conversions (FFCs), known as one of the collective neutrino oscillation modes induced by neutrino self-interactions. However, a recent study showed that they would yield qualitatively different asymptotic states of FFC if the neutrino number is forced to evolve. It is not yet fully understood why the canonical phenomenological models fail to predict asymptotic states. In this paper, we perform detailed investigations through numerical simulations and then provide an intuitive explanation with a quasi-homogeneous analysis. Based on the analysis, we propose a new phenomenological model, in which the quasi-steady evolution of FFCs is analytically determined. The model also allows us to express the convolution term of spatial wave number as a concise form, which corresponds to useful information on analyses for the non-linear feedback from small-scale flavor conversions to large-scale ones. Our model yields excellent agreement with numerical simulations, which lends support to our interpretation.