New method for detecting fast neutrino flavor conversions in core-collapse supernova models with two-moment neutrino transport
arXiv:2106.02650 · doi:10.1103/PhysRevD.104.063014
Abstract
Fast-pairwise neutrino oscillations potentially affect many aspects of core-collapse supernova (CCSN): the explosion mechanism, neutrino signals, and nucleosynthesis in the ejecta. This particular mode of collective neutrino oscillations has a deep connection to the angular structure of neutrinos in momentum space; for instance, the appearance of electron neutrinos lepton number (ELN) angular crossings in momentum space is a good indicator of occurrences of the flavor conversions. However, many multi-dimensional (multi-D) CCSN simulations are carried out with approximate neutrino transport (such as two-moment methods), which limits the access to the angular distributions of neutrinos, i.e., inhibits ELN-crossing searches. In this paper, we develop a new method of ELN-crossing search in these CCSN simulations. The required data is the zero-th and first angular moments of neutrinos and matter profile, all of which are available in CCSN models with two-moment method. One of the novelties of our new method is to use a ray-tracing neutrino transport to determine ELNs in the direction of the stellar center. It is designed to compensate for shortcomings of the crossing searches only with the two angular moments. We assess the capability of the method by carrying out a detailed comparison to results of full Boltzmann neutrino transport in 1D and 2D CCSN models. We find that the ray-tracing neutrino transport improves the accuracy of crossing searches; indeed, the appearance/disappearance of the crossings is accurately detected even in the region of forward-peaked angular distributions. The new method is computationally cheap and has a benefit of efficient parallelization; hence, it will be useful for ELN-crossing searches in any CCSN models employed two-moment neutrino transport.
arXiv commentMinor update to match version published in PRD
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