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Advection Algorithms for Quantum Neutrino Moment Transport

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arxiv 2501.07540 v2 pith:246TQ2ZV submitted 2025-01-13 astro-ph.HE hep-ph

classification astro-ph.HEhep-ph
keywords neutrinoflavortransportquantummomentsalgorithmscompactcomplex
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Neutrino transport in compact objects is an inherently challenging multi-dimensional problem. This difficulty is compounded if one includes flavor transformation -- an intrinsically quantum phenomenon requiring one to follow the coherence between flavors and thus necessitating the introduction of complex numbers. To reduce the computational burden, simulations of compact objects that include neutrino transport often make use of momentum-angle-integrated moments (the lowest order ones being commonly referred to as the energy density and flux) and these quantities can be generalized to include neutrino flavor, i.e., they become quantum moments. Numerous finite-volume approaches to solving the moment evolution equations for classical neutrino transport have been developed based on solving a Riemann problem at cell interfaces. In this paper we describe our generalization of a Riemann solver for quantum moments, specifically decomposing complex numbers in terms of a (signed) magnitude and phase instead of real and imaginary parts. We then test our new algorithm in numerous cases showing a neutrino fast flavor instability, varying from toy models with analytic solutions to snapshots from neutron star merger simulations. Compared to previous algorithms for neutrino transport with flavor mixing, we find uniformly smaller growth rates of the flavor transformation along with concomitantly larger length-scales, and that the results are a better match with the growth rates seen from multi-angle codes.

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Cited by 1 Pith paper

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  1. Predicting the outcome of collisional neutrino flavor conversion

    hep-ph 2025-05 conditional novelty 7.0 of 10

    Collisional neutrino flavor instabilities settle into a state at the edge of instability with nonzero flavor coherence, and explicit formulas predict this final state.

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