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Register a new userImplication for the core collapse supernova rate from 21 years of data of the Large Volume Detector
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The Large Volume Detector (LVD) has been continuously taking data since 1992 at the INFN Gran Sasso National Laboratory. LVD is sensitive to neutrino bursts from gravitational stellar collapses with full detection probability over the Galaxy. We have searched for neutrino bursts in LVD data taken in 7335 days of operation. No evidence of neutrino signals has been found between June 1992 and December 2013. The 90% C.L. upper limit on the rate of core-collapse and failed supernova explosions out to distances of 25 kpc is found to be 0.114/y.
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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) x 10**(-4)/(yr Mpc**3) at a mean redshift of 0.072 +/- 0.009. We measure the CCSN luminosity function from the data and consider the implications on the star formation history.
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 curves and good efficiency for supernovae brighter than $i^primesim24$. Using host photometric redshifts, we measure the supernova absolute magnitude distribution down to luminosities $4.5 {rm mag}$ fainter than normal SNIa. Using spectroscopy and light-curve fitting to discriminate against SNIa, we find a sample of 117 core-collapse supernova candidates with redshifts $z<0.4$ (median redshift of 0.29) and measure their rate to be larger than the type Ia supernova rate by a factor $4.5pm0.8(stat.) pm0.6 (sys.)$. This corresponds to a core-collapse rate at $z=0.3$ of $[1.42pm 0.3(stat.) pm0.3(sys.)]times10^{-4}yr^{-1}(h_{70}^{-1}Mpc)^{-3}$.
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.
The KM3NeT research infrastructure is under construction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at the GeV-PeV energy scale. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given.
The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and Cluster Lensing And Supernova survey with Hubble (CLASH) multi-cycle treasury programs with the Hubble Space Telescope (HST) have provided new opportunities to probe the rate of core-collapse supernovae (CCSNe) at high redshift, now extending to $zapprox2.5$. Here we use a sample of approximately 44 CCSNe to determine volumetric rates, $R_{CC}$, in six redshift bins in the range $0.1<z<2.5$. Together with rates from our previous HST program, and rates from the literature, we trace a more complete history of $R_{CC}(z)$, with $R_{CC}=0.72pm0.06$ yr$^{-1}$ Mpc$^{-3}$ 10$^{-4}$ $h_{70}^{3}$ at $z<0.08$, and increasing to $3.7^{+3.1}_{-1.6}$ yr$^{-1}$ Mpc$^{-3}$ 10$^{-4}$ $h_{70}^{3}$ to $zapprox2.0$. The statistical precision in each bin is several factors better than than the systematic error, with significant contributions from host extinction, and average peak absolute magnitudes of the assumed luminosity functions for CCSN types. Assuming negligible time delays from stellar formation to explosion, we find these composite CCSN rates to be in excellent agreement with cosmic star formation rate density (SFRs) derived largely from dust-corrected rest-frame UV emission, with a scaling factor of $k=0.0091pm0.0017,M^{-1}_{odot}$, and inconsistent (to $>95%$ confidence) with SFRs from IR luminous galaxies, or with SFR models that include simple evolution in the initial mass function over time. This scaling factor is expected if the fraction of the IMF contributing to CCSN progenitors is in the 8 to 50 $M_{odot}$ range. It is not supportive, however, of an upper mass limit for progenitors at $<20,M_{odot}$.
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