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Register a new userThe Effect of Weak Lensing on Distance Estimates from Supernovae
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Using a sample of 608 Type Ia supernovae from the SDSS-II and BOSS surveys, combined with a sample of foreground galaxies from SDSS-II, we estimate the weak lensing convergence for each supernova line-of-sight. We find that the correlation between this measurement and the Hubble residuals is consistent with the prediction from lensing (at a significance of 1.7sigma. Strong correlations are also found between the residuals and supernova nuisance parameters after a linear correction is applied. When these other correlations are taken into account, the lensing signal is detected at 1.4sigma. We show for the first time that distance estimates from supernovae can be improved when lensing is incorporated by including a new parameter in the SALT2 methodology for determining distance moduli. The recovered value of the new parameter is consistent with the lensing prediction. Using CMB data from WMAP7, H0 data from HST and SDSS BAO measurements, we find the best-fit value of the new lensing parameter and show that the central values and uncertainties on Omega_m and w are unaffected. The lensing of supernovae, while only seen at marginal significance in this low redshift sample, will be of vital importance for the next generation of surveys, such as DES and LSST, which will be systematics dominated.
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Residual errors in shear measurements, after corrections for instrument systematics and atmospheric effects, can impact cosmological parameters derived from weak lensing observations. Here we combine convergence maps from our suite of ray-tracing simulations with random realizations of spurious shear. This allows us to quantify the errors and biases of the triplet $(Omega_m,w,sigma_8)$ derived from the power spectrum (PS), as well as from three different sets of non-Gaussian statistics of the lensing convergence field: Minkowski functionals (MF), low--order moments (LM), and peak counts (PK). Our main results are: (i) We find an order of magnitude smaller biases from the PS than in previous work. (ii) The PS and LM yield biases much smaller than the morphological statistics (MF, PK). (iii) For strictly Gaussian spurious shear with integrated amplitude as low as its current estimate of $sigma^2_{sys}approx 10^{-7}$, biases from the PS and LM would be unimportant even for a survey with the statistical power of LSST. However, we find that for surveys larger than $approx 100$ deg$^2$, non-Gaussianity in the noise (not included in our analysis) will likely be important and must be quantified to assess the biases. (iv) The morphological statistics (MF,PK) introduce important biases even for Gaussian noise, which must be corrected in large surveys. The biases are in different directions in $(Omega_m,w,sigma_8)$ parameter space, allowing self-calibration by combining multiple statistics. Our results warrant follow-up studies with more extensive lensing simulations and more accurate spurious shear estimates.
We consider the effects of weak gravitational lensing on observations of 196 spectroscopically confirmed Type Ia Supernovae (SNe Ia) from years 1 to 3 of the Dark Energy Survey (DES). We simultaneously measure both the angular correlation function and the non-Gaussian skewness caused by weak lensing. This approach has the advantage of being insensitive to the intrinsic dispersion of SNe Ia magnitudes. We model the amplitude of both effects as a function of $sigma_8$, and find $sigma_8 = 1.2^{+0.9}_{-0.8}$. We also apply our method to a subsample of 488 SNe from the Joint Light-curve Analysis (JLA) (chosen to match the redshift range we use for this work), and find $sigma_8 = 0.8^{+1.1}_{-0.7}$. The comparable uncertainty in $sigma_8$ between DES-SN and the larger number of SNe from JLA highlights the benefits of homogeneity of the DES-SN sample, and improvements in the calibration and data analysis.
We have proposed a method for measuring weak lensing using the Lyman-alpha forest. Here we estimate the noise expected in weak lensing maps and power spectra for different sets of observational parameters. We find that surveys of the size and quality of the ones being done today and ones planned for the future will be able to measure the lensing power spectrum at a source redshift of z~2.5 with high precision and even be able to image the distribution of foreground matter with high fidelity on degree scales. For example, we predict that Lyman-alpha forest lensing measurement from the Dark Energy Spectroscopic Instrument survey should yield the mass fluctuation amplitude with statistical errors of 1.5%. By dividing the redshift range into multiple bins some tomographic lensing information should be accessible as well. This would allow for cosmological lensing measurements at higher redshift than are accessible with galaxy shear surveys and correspondingly better constraints on the evolution of dark energy at relatively early times.
We use matter power spectra from cosmological hydrodynamic simulations to quantify the effect of baryon physics on the weak gravitational lensing shear signal. The simulations consider a number of processes, such as radiative cooling, star formation, supernovae and feedback from active galactic nuclei (AGN). Van Daalen et al. (2011) used the same simulations to show that baryon physics, in particular the strong feedback that is required to solve the overcooling problem, modifies the matter power spectrum on scales relevant for cosmological weak lensing studies. As a result, the use of power spectra from dark matter simulations can lead to significant biases in the inferred cosmological parameters. We show that the typical biases are much larger than the precision with which future missions aim to constrain the dark energy equation of state, w_0. For instance, the simulation with AGN feedback, which reproduces X-ray and optical properties of groups of galaxies, gives rise to a ~40% bias in w_0. We demonstrate that the modification of the power spectrum is dominated by groups and clusters of galaxies, the effect of which can be modelled. We consider an approach based on the popular halo model and show that simple modifications can capture the main features of baryonic feedback. Despite its simplicity, we find that our model, when calibrated on the simulations, is able to reduce the bias in w_0 to a level comparable to the size of the statistical uncertainties for a Euclid-like mission. While observations of the gas and stellar fractions as a function of halo mass can be used to calibrate the model, hydrodynamic simulations will likely still be needed to extend the observed scaling relations down to halo masses of 10 ^12 M_sun/h.
We study the feasibility of detecting weak lensing spatial correlations between Supernova (SN) Type Ia magnitudes with present (Dark Energy Survey, DES) and future (Large Synoptic Survey Telescope, LSST) surveys. We investigate the angular auto-correlation function of SN magnitudes (once the background cosmology has been subtracted) and cross-correlation with galaxy catalogues. We examine both analytical and numerical predictions, the latter using simulated galaxy catalogues from the MICE Grand Challenge Simulation. We predict that we will be unable to detect the SN auto-correlation in DES, while it should be detectable with the LSST SN deep fields (15,000 SNe on 70 deg^2) at ~6sigma level of confidence (assuming 0.15 magnitudes of intrinsic dispersion). The SN-galaxy cross-correlation function will deliver much higher signal-to-noise, being detectable in both surveys with an integrated signal-to-noise of ~100 (up to 30 arcmin separations). We predict joint constraints on the matter density parameter (Omega_m) and the clustering amplitude (sigma_8) by fitting the auto-correlation function of our mock LSST deep fields. When assuming a Gaussian prior for Omega_m, we can achieve a 25% measurement of sigma_8 from just these LSST supernovae (assuming 0.15 magnitudes of intrinsic dispersion). These constraints will improve significantly if the intrinsic dispersion of SNe Ia can be reduced.
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