Constructing angular distributions of neutrinos in core collapse supernova from zero-th and first moments calibrated by full Boltzmann neutrino transport
arXiv:2104.05729 · doi:10.1103/PhysRevD.103.123025
Abstract
Two-moment neutrino transport methods have been widely used for developing theoretical models of core-collapse supernova (CCSN), since they substantially reduce the computational burden inherent in the multi-dimensional neutrino-radiation hydrodynamical simulations. The approximation, however, comes at a price; the detailed structure of angular distribution of neutrinos is sacrificed, that is the main drawback of this approach. In this paper, we develop a novel method by which to construct angular distributions of neutrinos from the zero-th and first angular moments. In our method, the angular distribution is expressed with two quadratic functions of the neutrino angle in a piecewise fashion. We determine the best parameters in the fitting function by comparing to the neutrino data in a spherically symmetric CCSN model with full Boltzmann neutrino transport. We demonstrate the capability of our method by using our recent 2D CCSN model. We find that the essential features of the angular distributions can be well reconstructed, whereas the angular distributions of incoming neutrinos tend to have large errors that increase with flux factor (). This issue originates from the insensitiveness of incoming neutrinos to , that is an intrinsic limitation in moment methods. Based on the results of the demonstration, we assess the reliability of ELN-crossing searches with two-moment neutrino transport. This analysis is complementary to our another paper that scrutinizes the limitation of crossing searches with a few moments. We find that the systematic errors of angular distributions for incoming neutrinos lead to misjudgements of the crossing at . This casts doubt on the results of ELN-crossing searches based on two-moment methods in some previous studies.
arXiv commentMinor corrections were made in Figs. (Accepted to PRD)
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