No Arabic abstract
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.
In this paper, we propose a new test to the cosmic distance duality relation (CDDR), $D_L=D_A(1+z)^2$, where $D_L$ and $D_A$ are the luminosity and angular diameter distances, respectively. The data used correspond to 61 Type Ia Supernova luminosity distances and $Y_{SZE}-Y_X$ measurements of 61 galaxy clusters obtained by the {it Planck} mission and the deep XMM-Newton X-ray data, where $Y_{SZE}$ is the integrated comptonization parameter obtained via Sunyaev-Zeldovich effect observations and $Y_X$ is the X-ray counterpart. More precisely, we use the $Y_{SZE}D_{A}^{2}/C_{XSZE}Y_X$ scaling-relation and a deformed CDDR, such as $D_L/D_A(1+z)^2=eta(z)$, to verify if $eta(z)$ is compatible with the unity. Two $eta(z)$ functions are used, namely, $eta(z)=1+eta_0 z$ and $eta(z)=1+eta_0 z /(1+z)$. { We obtain that the CDDR validity ($eta_0=0$) is verified within $approx 1.5sigma$ c.l. for both $eta(z)$ functions.}.
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.
We carry out a test of the cosmic distance duality relation using a sample of 52 SPT-SZ clusters, along with X-ray measurements from XMM-Newton. To carry out this test, we need an estimate of the luminosity distance ($D_L$) at the redshift of the cluster. For this purpose, we use three independent methods: directly using $D_L$ from the closest Type Ia Supernovae from the Union 2.1 sample, non-parametric reconstruction of $D_L$ using the same Union 2.1 sample, and finally using $H(z)$ measurements from cosmic chronometers and reconstructing $D_L$ using Gaussian Process regression. We use four different functions to characterize the deviations from CDDR. All our results for these ($4 times 3$) analyses are consistent with CDDR to within 1$sigma$.
We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light curve analysis, and to determine bias corrections for SN~Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN~Ia model, incorporates information from observations (PSF, sky noise, zero point), and uses summary information (e.g., detection efficiency vs. signal to noise ratio) based on 10,000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05~mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue color, distance biases can reach 0.4~mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at https://des.ncsa.illinois.edu/releases/sn.
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.