Non-Radial Instabilities and Progenitor Asphericities in Core-Collapse Supernovae

Since core-collapse supernova simulations still struggle to produce robust neutrino-driven explosions in 3D, it has been proposed that asphericities caused by convection in the progenitor might facilitate shock revival by boosting the activity of non-radial hydrodynamic instabilities in the post-shock region. We investigate this scenario in depth using 42 relativistic 2D simulations with multi-group neutrino transport to examine the effects of velocity and density perturbations in the progenitor for different perturbation geometries that obey fundamental physical constraints (like the anelastic condition). As a framework for analysing our results, we introduce semi-empirical scaling laws relating neutrino heating, average turbulent velocities in the gain region, and the shock deformation in the saturation limit of non-radial instabilities. The squared turbulent Mach number, , reflects the violence of aspherical motions in the gain layer, and explosive runaway occurs for ~0.3, corresponding to a reduction of the critical neutrino luminosity by ~25% compared to 1D. In the light of this theory, progenitor asphericities aid shock revival mainly by creating anisotropic mass flux onto the shock: Differential infall efficiently converts velocity perturbations in the progenitor into density perturbations (Delta rho/rho) at the shock of the order of the initial convective Mach number Ma. The anisotropic mass flux and ram pressure deform the shock and thereby amplify post-shock turbulence. Large-scale (l=2,l=1) modes prove most conducive to shock revival, whereas small-scale perturbations require unrealistically high convective Mach numbers. Initial density perturbations in the progenitor are only of order Ma^2 and therefore play a subdominant role.Comment: revised version, 34 pages, 24 figure

Fuzzy audio similarity measures based on spectrum histograms and fluctuation patterns

Spectrum histograms and fluctuation patterns are representations of audio fragments. By comparing these representations, we can determine the similarity between the corresponding fragments. Traditionally, this is done using the Euclidian distance. We propose fuzzy similarity measures as an alternative. First we introduce some well-known fuzzy similarity measures, together with certain properties that can be desirable or useful in practice. In particular we present several forms of restrictability, which allow to reduce the computation time in practical applications. Next, we show that fuzzy similarity measures can be used to compare spectrum histograms and fluctuation patterns. Finally, we describe some experimental observations for this fuzzy approach of constructing audio similarity measures