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تسجيل مستخدم جديدFirst Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Survey Overview and Supernova Spectroscopy
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We present spectroscopy from the first three seasons of the Dark Energy Survey Supernova Program (DES-SN). We describe the supernova spectroscopic program in full: strategy, observations, data reduction, and classification. We have spectroscopically confirmed 307 supernovae, including 251 type Ia supernovae (SNe Ia) over a redshift range of $0.017 < z < 0.85$. We determine the effective spectroscopic selection function for our sample, and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. We also provide a full overview of the strategy, observations, and data products of DES-SN, which has discovered 12,015 likely supernovae during these first three seasons. The data presented here are used for the first cosmology analysis by DES-SN (DES-SN3YR), the results of which are given in DES Collaboration (2018a).
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We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from the first t
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We present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified type Ia supernovae (SNe Ia) from the first three years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift ran
ge of 0.017<$z$<0.849. We combine the DES-SN sample with an external sample of 122 low-redshift ($z$<0.1) SNe Ia, resulting in a DES-SN3YR sample of 329 SNe Ia. Our cosmological analyses are blinded: after combining our DES-SN3YR distances with constraints from the Cosmic Microwave Background (CMB; Planck Collaboration 2016), our uncertainties in the measurement of the dark energy equation-of-state parameter, $w$, are .042 (stat) and .059 (stat+syst) at 68% confidence. We provide a detailed systematic uncertainty budget, which has nearly equal contributions from photometric calibration, astrophysical bias corrections, and instrumental bias corrections. We also include several new sources of systematic uncertainty. While our sample is <1/3 the size of the Pantheon sample, our constraints on $w$ are only larger by 1.4$times$, showing the impact of the DES SN Ia light curve quality. We find that the traditional stretch and color standardization parameters of the DES SNe Ia are in agreement with earlier SN Ia samples such as Pan-STARRS1 and the Supernova Legacy Survey. However, we find smaller intrinsic scatter about the Hubble diagram (0.077 mag). Interestingly, we find no evidence for a Hubble residual step ( 0.007 $pm$ 0.018 mag) as a function of host galaxy mass for the DES subset, in 2.4$sigma$ tension with previous measurements. We also present novel validation methods of our sample using simulated SNe Ia inserted in DECam images and using large catalog-level simulations to test for biases in our analysis pipelines.
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 s
imulations 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.
We present improved photometric measurements for the host galaxies of 206 spectroscopically confirmed type Ia supernovae discovered by the Dark Energy Survey Supernova Program (DES-SN) and used in the first DES-SN cosmological analysis. Fitting spect
ral energy distributions to the $griz$ photometric measurements of the DES-SN host galaxies, we derive stellar masses and star-formation rates. For the DES-SN sample, when considering a 5D ($z$, $x_1$, $c$, $alpha$, $beta$) bias correction, we find evidence of a Hubble residual `mass step, where SNe Ia in high mass galaxies ($>10^{10} textrm{M}_{odot}$) are intrinsically more luminous (after correction) than their low mass counterparts by $gamma=0.040pm0.019$mag. This value is larger by $0.031$mag than the value found in the first DES-SN cosmological analysis. This difference is due to a combination of updated photometric measurements and improved star formation histories and is not from host-galaxy misidentification. When using a 1D (redshift-only) bias correction the inferred mass step is larger, with $gamma=0.066pm0.020$mag. The 1D-5D $gamma$ difference for DES-SN is $0.026pm0.009$mag. We show that this difference is due to a strong correlation between host galaxy stellar mass and the $x_1$ component of the 5D distance-bias correction. To better understand this effect, we include an intrinsic correlation between light-curve width and stellar mass in simulated SN Ia samples. We show that a 5D fit recovers $gamma$ with $-9$mmag bias compared to a $+2$mmag bias for a 1D fit. This difference can explain part of the discrepancy seen in the data. Improvements in modeling correlations between galaxy properties and SN is necessary to determine the implications for $gamma$ and ensure unbiased precision estimates of the dark energy equation-of-state as we enter the era of LSST.
Calibration uncertainties have been the leading systematic uncertainty in recent analyses using type Ia Supernovae (SNe Ia) to measure cosmological parameters. To improve the calibration, we present the application of Spectral Energy Distribution (SE
D)-dependent chromatic corrections to the supernova light-curve photometry from the Dark Energy Survey (DES). These corrections depend on the combined atmospheric and instrumental transmission function for each exposure, and they affect photometry at the 0.01 mag (1%) level, comparable to systematic uncertainties in calibration and photometry. Fitting our combined DES and low-z SN Ia sample with Baryon Acoustic Oscillation (BAO) and Cosmic Microwave Background (CMB) priors for the cosmological parameters $Omega_{rm m}$ (the fraction of the critical density of the universe comprised of matter) and w (the dark energy equation of state parameter), we compare those parameters before and after applying the corrections. We find the change in w and $Omega_{rm m}$ due to not including chromatic corrections are -0.002 and 0.000, respectively, for the DES-SN3YR sample with BAO and CMB priors, consistent with a larger DES-SN3YR-like simulation, which has a w-change of 0.0005 with an uncertainty of 0.008 and an $Omega_{rm m}$ change of 0.000 with an uncertainty of 0.002 . However, when considering samples on individual CCDs we find large redshift-dependent biases (approximately 0.02 in distance modulus) for supernova distances.
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