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On the character of turbulence in self-consistent models of core-collapse supernovae (2004.02055v1)

Published 5 Apr 2020 in astro-ph.SR and astro-ph.HE

Abstract: Neutrino-driven convection plays a crucial role in the development of core-collapse supernova (CCSN) explosions. However, the complex mechanism that triggers the shock revival and the subsequent explosion has remained inscrutable for many decades. Multidimensional simulations suggest that the growth of fluid instabilities and the development of turbulent convection will determine the morphology of the explosion. We have performed 3D simulations using spherical-polar coordinates covering a reduced angular extent (90 degree computational domain), and with angular resolutions of 2 degrees, 1 degree, 1/2 degree, and 1/4 degree, to study the development of turbulence in core-collapse supernova explosions on a time scale of order 100 ms. We have employed the multi-physics Chimera code that includes detailed nuclear physics and spectral neutrino transport. Coarse resolution models do not develop an inertial range, presumably due to the bottleneck effect, such that the energy is prevented from cascading down to small scales and tends to accumulate at large scales. High-resolution models instead, start to recover the k{-5/3} scaling of Kolmogorov's theory. Stochasticity and few simulation samples limit our ability to predict the development of explosions. Over the simulated time period, our models show no clear trend in improving (or diminishing) conditions for explosion as the angular resolution is increased. However, we find that turbulence provides an effective pressure behind the shock (approx. 40 - 50 % of the thermal pressure), which can contribute to the shock revival and be conducive for the development of the explosion. Finally, we show that the turbulent energy power spectrum of reduced angular extent and full 4 pi models are consistent, thus indicating that a 90 degree computational domain is an adequate configuration to study the character of turbulence in CCSNe.

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