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Mapping supernovae to their progenitors is fundamental to understanding the collapse of massive stars. We investigate the red supergiant problem, which concerns why red supergiants with masses $sim16$-$30 M_odot$ have not been identified as progenitors of Type IIP supernovae, and the supernova rate problem, which concerns why the observed cosmic supernova rate is smaller than the observed cosmic star formation rate. We find key physics to solving these in the compactness parameter, which characterizes the density structure of the progenitor. If massive stars with compactness above $xi_{2.5} sim 0.2$ fail to produce canonical supernovae, (i) stars in the mass range $16$-$30 M_odot$ populate an island of stars that have high $xi_{2.5}$ and do not produce canonical supernovae, and (ii) the fraction of such stars is consistent with the missing fraction of supernovae relative to star formation. We support this scenario with a series of two- and three-dimensional radiation hydrodynamics core-collapse simulations. Using more than 300 progenitors covering initial masses $10.8$-$75 M_odot$ and three initial metallicities, we show that high compactness is conducive to failed explosions. We then argue that a critical compactness of $sim 0.2$ as the divide between successful and failed explosions is consistent with state-of-the-art three-dimensional core-collapse simulations. Our study implies that numerical simulations of core collapse need not produce robust explosions in a significant fraction of compact massive star initial conditions.
We use the Sloan Digital Sky Survey II Supernova Survey (SDSS-II SNS) data to measure the volumetric core collapse supernova (CCSN) rate in the redshift range (0.03<z<0.09). Using a sample of 89 CCSN we find a volume-averaged rate of (1.06 +/- 0.19)
We use three years of data from the Supernova Legacy Survey (SNLS) to study the general properties of core-collapse and type Ia supernovae. This is the first such study using the rolling search technique which guarantees well-sampled SNLS light curve
We investigate a method to construct parametrized progenitor models for core-collapse supernova simulations. Different from all modern core-collapse supernova studies, which rely on progenitor models from stellar evolution calculations, we follow the
How do massive stars explode? Progress toward the answer is driven by increases in compute power. Petascale supercomputers are enabling detailed three-dimensional simulations of core-collapse supernovae. These are elucidating the role of fluid instab
The recent discovery that the Fe-K line luminosities and energy centroids observed in nearby SNRs are a strong discriminant of both progenitor type and circumstellar environment has implications for our understanding of supernova progenitor evolution