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Register a new userType Ia Supernova Rate Measurements to Redshift 2.5 from CANDELS : Searching for Prompt Explosions in the Early Universe
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The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) was a multi-cycle treasury program on the Hubble Space Telescope (HST) that surveyed a total area of ~0.25 deg^2 with ~900 HST orbits spread across 5 fields over 3 years. Within these survey images we discovered 65 supernovae (SN) of all types, out to z~2.5. We classify ~24 of these as Type Ia SN (SN Ia) based on host-galaxy redshifts and SN photometry (supplemented by grism spectroscopy of 6 SN). Here we present a measurement of the volumetric SN Ia rate as a function of redshift, reaching for the first time beyond z=2 and putting new constraints on SN Ia progenitor models. Our highest redshift bin includes detections of SN that exploded when the universe was only ~3 Gyr old and near the peak of the cosmic star-formation history. This gives the CANDELS high-redshift sample unique leverage for evaluating the fraction of SN Ia that explode promptly after formation (<500 Myr). Combining the CANDELS rates with all available SN Ia rate measurements in the literature we find that this prompt SN Ia fraction is fP=0.53 +0.09 -0.10 (stat) +0.10 -0.26 (sys), consistent with a delay time distribution that follows a simple t^{-1} power law for all times t>40 Myr. However, a mild tension is apparent between ground-based low-z surveys and space-based high-z surveys. In both CANDELS and the sister HST program CLASH, we find a low rate of SN Ia at z>1. This could be a hint that prompt progenitors are in fact relatively rare, accounting for only ~20% of all SN Ia explosions -- though further analysis and larger samples will be needed to examine that suggestion.
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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 $<20,M_{odot}$.
Supernova (SN) rates are potentially powerful diagnostics of metal enrichment and SN physics, particularly in galaxy clusters with their deep, metal-retaining potentials and relatively simple star-formation histories. We have carried out a survey for supernovae (SNe) in galaxy clusters, at a redshift range 0.5<z<0.9, using the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope. We reimaged a sample of 15 clusters that were previously imaged by ACS, thus obtaining two to three epochs per cluster, in which we discovered five likely cluster SNe, six possible cluster SNe Ia, two hostless SN candidates, and several background and foreground events. Keck spectra of the host galaxies were obtained to establish cluster membership. We conducted detailed efficiency simulations, and measured the stellar luminosities of the clusters using Subaru images. We derive a cluster SN rate of 0.35 SNuB +0.17/-0.12 (statistical) pm0.13 (classification) pm0.01 (systematic) [where SNuB = SNe (100 yr 10^10 L_B_sun)^-1] and 0.112 SNuM +0.055/-0.039 (statistical) pm0.042 (classification) pm0.005 (systematic) [where SNuM = SNe (100 yr 10^10 M_sun)^-1]. As in previous measurements of cluster SN rates, the uncertainties are dominated by small-number statistics. The SN rate in this redshift bin is consistent with the SN rate in clusters at lower redshifts (to within the uncertainties), and shows that there is, at most, only a slight increase of cluster SN rate with increasing redshift. The low and fairly constant SN Ia rate out to z~1 implies that the bulk of the iron mass in clusters was already in place by z~1. The recently observed doubling of iron abundances in the intracluster medium between z=1 and 0, if real, is likely the result of redistribution of existing iron, rather than new production of iron.
We present a measurement of the volumetric Type Ia supernova (SN Ia) rate based on data from the Sloan Digital Sky Survey II (SDSS-II) Supernova Survey. The adopted sample of supernovae (SNe) includes 516 SNe Ia at redshift z lesssim 0.3, of which 270 (52%) are spectroscopically identified as SNe Ia. The remaining 246 SNe Ia were identified through their light curves; 113 of these objects have spectroscopic redshifts from spectra of their host galaxy, and 133 have photometric redshifts estimated from the SN light curves. Based on consideration of 87 spectroscopically confirmed non-Ia SNe discovered by the SDSS-II SN Survey, we estimate that 2.04+1.61-0.95 % of the photometric SNe Ia may be misidentified. The sample of SNe Ia used in this measurement represents an order of magnitude increase in the statistics for SN Ia rate measurements in the redshift range covered by the SDSS-II Supernova Survey. If we assume a SN Ia rate that is constant at low redshift (z < 0.15), then the SN observations can be used to infer a value of the SN rate of rV = (2.69+0.34+0.21-0.30-0.01) x10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} at a mean redshift of ~ 0.12, based on 79 SNe Ia of which 72 are spectroscopically confirmed. However, the large sample of SNe Ia included in this study allows us to place constraints on the redshift dependence of the SN Ia rate based on the SDSS-II Supernova Survey data alone. Fitting a power-law model of the SN rate evolution, r_V(z) = A_p x ((1 + z)/(1 + z0))^{ u}, over the redshift range 0.0 < z < 0.3 with z0 = 0.21, results in A_p = (3.43+0.15-0.15) x 10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} and u = 2.04+0.90-0.89.
We present a measurement of the volumetric Type Ia supernova (SN Ia) rate (SNR_Ia) as a function of redshift for the first four years of data from the Canada-France-Hawaii Telescope (CFHT) Supernova Legacy Survey (SNLS). This analysis includes 286 spectroscopically confirmed and more than 400 additional photometrically identified SNe Ia within the redshift range 0.1<z<1.1. The volumetric SNR_Ia evolution is consistent with a rise to z~1.0 that follows a power-law of the form (1+z)^alpha, with alpha=2.11+/-0.28. This evolutionary trend in the SNLS rates is slightly shallower than that of the cosmic star-formation history over the same redshift range. We combine the SNLS rate measurements with those from other surveys that complement the SNLS redshift range, and fit various simple SN Ia delay-time distribution (DTD) models to the combined data. A simple power-law model for the DTD (i.e., proportional to t^-beta) yields values from beta=0.98+/-0.05 to beta=1.15+/-0.08 depending on the parameterization of the cosmic star formation history. A two-component model, where SNR_Ia is dependent on stellar mass (Mstellar) and star formation rate (SFR) as SNR_Ia(z)=AxMstellar(z) + BxSFR(z), yields the coefficients A=1.9+/-0.1 SNe/yr/M_solar and B=3.3+/-0.2 SNe/yr/(M_solar/yr). More general two-component models also fit the data well, but single Gaussian or exponential DTDs provide significantly poorer matches. Finally, we split the SNLS sample into two populations by the light curve width (stretch), and show that the general behavior in the rates of faster-declining SNe Ia (0.8<s<1.0) is similar, within our measurement errors, to that of the slower objects (1.0<s<1.3) out to z~0.8.
Supernova rates are directly coupled to high mass stellar birth and evolution. As such, they are one of the few direct measures of the history of cosmic stellar evolution. In this paper we describe an probabilistic technique for identifying supernovae within spectroscopic samples of galaxies. We present a study of 52 type Ia supernovae ranging in age from -14 days to +40 days extracted from a parent sample of simeq 50,000 spectra from the SDSS DR5. We find a Supernova Rate (SNR) of 0.472^{+0.048}_{-0.039}(Systematic)^{+0.081}_{-0.071}(Statistical)SNu at a redshift of <z> = 0.1. This value is higher than other values at low redshift at the 1{sigma}, but is consistent at the 3{sigma} level. The 52 supernova candidates used in this study comprise the third largest sample of supernovae used in a type Ia rate determination to date. In this paper we demonstrate the potential for the described approach for detecting supernovae in future spectroscopic surveys.
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