Nuclear shell burning in the final stages of the lives of massive stars is accompanied by strong turbulent convection. The resulting fluctuations aid supernova explosion by amplifying the non-radial flow in the post-shock region. In this work, we inv
estigate the physical mechanism behind this amplification using a linear perturbation theory. We model the shock wave as a one-dimensional planar discontinuity and consider its interaction with vorticity and entropy perturbations in the upstream flow. We find that, as the perturbations cross the shock, their total turbulent kinetic energy is amplified by a factor of $sim!2$, while the average linear size of turbulent eddies decreases by about the same factor. These values are not sensitive to the parameters of the upstream turbulence and the nuclear dissociation efficiency at the shock. Finally, we discuss the implication of our results for the supernova explosion mechanism. We show that the upstream perturbations can decrease the critical neutrino luminosity for producing explosion by several percent.
The late collapse, core bounce, and the early postbounce phase of rotating core collapse leads to a characteristic gravitational wave (GW) signal. The precise shape of the signal is governed by the interplay of gravity, rotation, nuclear equation of
state (EOS), and electron capture during collapse. We explore the dependence of the signal on total angular momentum and its distribution in the progenitor core by means of a large set of axisymmetric general-relativistic core collapse simulations in which we vary the initial angular momentum distribution in the core. Our simulations include a microphysical finite-temperature EOS, an approximate electron capture treatment during collapse, and a neutrino leakage scheme for the postbounce evolution. We find that the precise distribution of angular momentum is relevant only for very rapidly rotating cores with T/|W|>~8% at bounce. We construct a numerical template bank from our baseline set of simulations, and carry out additional simulations to generate trial waveforms for injection into simulated advanced LIGO noise at a fiducial galactic distance of 10 kpc. Using matched filtering, we show that for an optimally-oriented source and Gaussian noise, advanced Advanced LIGO could measure the total angular momentum to within ~20%, for rapidly rotating cores. For most waveforms, the nearest known degree of precollapse differential rotation is correctly inferred by both our matched filtering analysis and an alternative Bayesian model selection approach. We test our results for robustness against systematic uncertainties by injecting waveforms from simulations using a different EOS and and variations in the electron fraction in the inner core. The results of these tests show that these uncertainties significantly reduce the accuracy with which the total angular momentum and its precollapse distribution can be inferred from observations.
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 t
o 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 timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.
