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Register a new userRedshift evolution of the underlying type Ia supernova stretch distribution
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The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as survey statistics increase, the question of astrophysical systematic uncertainties arises, notably that of the evolution of SN Ia populations. We study the dependence on redshift of the SN Ia light-curve stretch, a purely intrinsic SN property, to probe its potential redshift drift. The SN stretch has been shown to be strongly correlated with the SN environment, notably with stellar age tracers. We modeled the underlying stretch distribution as a function of redshift, using the evolution of the fraction of young and old SNe Ia as predicted using the SNfactory dataset, and assuming a constant underlying stretch distribution for each age population consisting of Gaussian mixtures. We tested our prediction against published samples that were cut to have marginal magnitude selection effects so that any observed change is indeed astrophysical and not observational in origin. In this first study, there are indications that the underlying SN Ia stretch distribution evolves as a function of redshift, and that the age drifting model is a better description of the data than any time-constant model, including the sample-based asymmetric distributions that are often used to correct Malmquist bias at a significance higher than 5 $sigma$. The favored underlying stretch model is a bimodal one, composed of a high-stretch mode shared by both young and old environments, and a low-stretch mode that is exclusive to old environments. The precise effect of the redshift evolution of the intrinsic properties of a SN Ia population on cosmology remains to be studied. The astrophysical drift of the SN stretch distribution does affect current Malmquist bias corrections and hence the distances that are derived using SNe that are affected by observational selection effects. This bias increases with surveys covering larger redshift ranges.
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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 (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.
R-band intensity measurements along the light curve of Type Ia supernovae discovered by the Supernova Cosmology Project (SCP) are fitted in brightness to templates allowing a free parameter the time-axis width factor w = s(1+z). The data points are then individually aligned in the time-axis, normalized and K-corrected back to the rest frame, after which the nearly 1300 normalized intensity measurements are found to lie on a well-determined common rest-frame B-band curve which we call the ``composite curve. The same procedure is applied to 18 low-redshift Calan/Tololo SNe with z < 0.11; these nearly 300 B-band photometry points are found to lie on the composite curve equally well. The SCP search technique produces several measurements before maximum light for each supernova. We demonstrate that the linear stretch factor, s, which parameterizes the light-curve timescale appears independent of z,and applies equally well to the declining and rising parts of the light curve. In fact, the B-band template that best fits this composite curve fits the individual supernova photometry data when stretched by a factor s with chi^2/DoF approx = 1, thus as well as any parameterization can, given the current data sets. The measurement of the date of explosion, however, is model dependent and not tightly constrained by the current data. We also demonstrate the 1+z light-curve time-axis broadening expected from cosmological expansion. This argues strongly against alternative explanations, such as tired light, for the redshift of distant objects.
We present the discovery of a Type Ia supernova (SN) at redshift $z = 1.914$ from the CANDELS multi-cycle treasury program on the textit{Hubble Space Telescope (HST)}. This SN was discovered in the infrared using the Wide-Field Camera 3, and it is the highest-redshift Type Ia SN yet observed. We classify this object as a SN,Ia by comparing its light curve and spectrum with those of a large sample of Type Ia and core-collapse supernovae (SNe). Its apparent magnitude is consistent with that expected from the $Lambda$CDM concordance cosmology. We discuss the use of spectral evidence for classification of $z > 1.5$ SNe,Ia using {it HST} grism simulations, finding that spectral data alone can frequently rule out SNe,II, but distinguishing between SNe,Ia and SNe,Ib/c can require prohibitively long exposures. In such cases, a quantitative analysis of the light curve may be necessary for classification. Our photometric and spectroscopic classification methods can aid the determination of SN rates and cosmological parameters from the full high-redshift CANDELS SN sample.
We re-analyze the detectability of large scale dark flow (or local bulk flow) with respect to the CMB background based upon the redshift-distance relation for Type Ia supernovae (SN Ia). We made two independent analyses: one based upon identifying the three Cartesian velocity components; and the other based upon the cosine dependence of the deviation from Hubble flow on the sky. We apply these analyses to the Union2.1 SN Ia data and to the SDSS-II supernova survey. For both methods, results for low redshift, $z < 0.05$, are consistent with previous searches. We find a local bulk flow of $v_{rm bf} sim 300$ km s$^{-1}$ in the direction of $(l,b) sim (270, 35)^{circ}$. However, the search for a dark flow at $z>0.05$ is inconclusive. Based upon simulated data sets, we deduce that the difficulty in detecting a dark flow at high redshifts arises mostly from the observational error in the distance modulus. Thus, even if it exists, a dark flow is not detectable at large redshift with current SN Ia data sets. We estimate that a detection would require both significant sky coverage of SN Ia out to $z = 0.3$ and a reduction in the effective distance modulus error from 0.2 mag to $lesssim 0.02$ mag. We estimate that a greatly expanded data sample of $sim 10^4$ SN Ia might detect a dark flow as small as 300 km s$^{-1}$ out to $z = 0.3$ even with a distance modulus error of $0.2$ mag. This may be achievable in a next generation large survey like LSST.
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