Calibration of the Advanced Spectral Leakage scheme for neutron star merger simulations, and extension to smoothed-particle hydrodynamics

We calibrate a neutrino transport approximation, called Advanced Spectral Leakage (ASL), with the purpose of modelling neutrino-driven winds in neutron star mergers. Based on a number of snapshots, we gauge the ASL parameters by comparing against both the two-moment (M1) scheme implemented in the flash code and the Monte Carlo neutrino code sedonu. The ASL scheme contains three parameters, the least robust of which results to be a blocking parameter for electron neutrinos and antineutrinos. The parameter steering the angular distribution of neutrino heating is recalibrated compared to the earlier work. We also present a new, fast and mesh-free algorithm for calculating spectral optical depths, which, when using smoothed-particle hydrodynamics (SPH), makes the neutrino transport completely particle-based. We estimate a speed-up of a factor of greater than or similar to 100 in the optical depth calculation when comparing to a grid-based approach. In the suggested calibration we recover luminosities and mean energies within . A comparison of the rates of change of internal energy and electron fraction in the neutrino-driven wind suggests comparable accuracies of ASL and M1, but a higher computational efficiency of the ASL scheme. We estimate that the ratio between the CPU hours spent on the ASL neutrino scheme and those spent on the hydrodynamics is less than or similar to 0.8 per time-step when considering the SPH code MAGMA2 as source code for the Lagrangian hydrodynamics, to be compared with a factor of 10 from the M1 in flash.

Automated summary

The study focuses on calibrating an ASL neutrino transport approximation for modeling neutrino-driven winds in neutron star mergers. By comparing with other neutrino simulation methods, the study finds ASL to be more computationally efficient and provide comparable accuracy in predicting luminosities and mean energies. Additionally, a new particle-based algorithm for calculating spectral optical depths is proposed, showing a significant speed-up compared to grid-based approaches.