Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe Discovery of the Most Distant Known Type Ia Supernova at Redshift 1.914
231
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
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.
rate research
Read More
We present a measurement of the rate of distant Type Ia supernovae derived using 4 large subsets of data from the Supernova Cosmology Project. Within this fiducial sample, which surveyed about 12 square degrees, thirty-eight supernovae were detected at redshifts 0.25--0.85. In a spatially-flat cosmological model consistent with the results obtained by the Supernova Cosmology Project, we derive a rest-frame Type Ia supernova rate at a mean redshift $zsimeq0.55$ of $1.53 {^{+0.28}_{-0.25}} {^{+0.32}_{-0.31}} 10^{-4} h^3 {rm Mpc}^{-3} {rm yr}^{-1}$ or $0.58 {^{+0.10}_{-0.09}} {^{+0.10}_{-0.09}} h^2 {rm SNu}$ (1 SNu = 1 supernova per century per $10^{10}$Lbsun), where the first uncertainty is statistical and the second includes systematic effects. The dependence of the rate on the assumed cosmological parameters is studied and the redshift dependence of the rate per unit comoving volume is contrasted with local estimates in the context of possible cosmic star formation histories and progenitor models.
The rate evolution of subluminous Type Ia Supernovae is presented using data from the Supernova Legacy Survey. This sub-sample represents the faint and rapidly-declining light-curves of the observed supernova Ia (SN Ia) population here defined by low stretch values (s<0.8). Up to redshift z=0.6, we find 18 photometrically-identified subluminous SNe Ia, of which six have spectroscopic redshift (and three are spectroscopically-confirmed SNe Ia). The evolution of the subluminous volumetric rate is constant or slightly decreasing with redshift, in contrast to the increasing SN Ia rate found for the normal stretch population, although a rising behaviour is not conclusively ruled out. The subluminous sample is mainly found in early-type galaxies with little or no star formation, so that the rate evolution is consistent with a galactic mass dependent behavior: $r(z)=Atimes M_g$, with $A=(1.1pm0.3)times10^{-14}$ SNe per year and solar mass.
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.
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.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
