A New Monte Carlo Method for Time-Dependent Neutrino Radiation Transport
Ernazar Abdikamalov (1), Adam Burrows (2), Christian D. Ott (1), Frank, L\"offler (3), Evan O'Connor (1), Joshua C. Dolence (2), and Erik Schnetter, (4) ((1) Caltech, (2) Princeton, (3) LSU, (4) Perimeter Institute)

TL;DR
This paper develops and tests a new Monte Carlo method for simulating neutrino transport in core-collapse supernovae, combining implicit and discrete-diffusion schemes to improve efficiency and accuracy in complex, multi-dimensional astrophysical models.
Contribution
It generalizes existing Monte Carlo schemes to energy, time, and velocity dependence for neutrino transport, enabling larger timesteps and faster computations in supernova simulations.
Findings
Implicit scheme allows larger timesteps without losing accuracy.
Discrete-diffusion method speeds up calculations at high optical depth.
The combined approach is robust for supernova neutrino transport modeling.
Abstract
Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck & Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger…
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