Alina Kiessling

3D cosmic shear: cosmology from CFHTLenS

This paper presents the first application of 3D cosmic shear to a wide-field weak lensing survey. 3D cosmic shear is a technique that analyses weak lensing in three dimensions using a spherical harmonic approach, and does not bin data in the redshift direction. This is applied to CFHTLenS, a 154 square degree imaging survey with a median redshift of 0.7 and an effective number density of 11 galaxies per square arcminute usable for weak lensing. To account for survey masks we apply a 3D pseudo-Cl approach on weak lensing data, and to avoid uncertainties in the highly non-linear regime, we separately analyse radial wave numbers k<=1.5h/Mpc and k<=5.0h/Mpc, and angular wavenumbers l~400-5000. We show how one can recover 2D and tomographic power spectra from the full 3D cosmic shear power spectra and present a measurement of the 2D cosmic shear power spectrum, and measurements of a set of 2-bin and 6-bin cosmic shear tomographic power spectra; in doing so we find that using the 3D power in the calculation of such 2D and tomographic power spectra from data naturally accounts for a minimum scale in the matter power spectrum. We use 3D cosmic shear to constrain cosmologies with parameters OmegaM, OmegaB, sigma8, h, ns, w0, wa. For a non-evolving dark energy equation of state, and assuming a flat cosmology, lensing combined with WMAP7 results in h=0.78+/-0.12, OmegaM=0.252+/-0.079, sigma8=0.88+/-0.23 and w=-1.16+/-0.38 using only scales k<=1.5h/Mpc. We also present results of lensing combined with first year Planck results, where we find no tension with the results from this analysis, but we also find no significant improvement over the Planck results alone. We find evidence of a suppression of power compared to LCDM on small scales 1.5 < k < 5.0 h/Mpc in the lensing data, which is consistent with predictions of the effect of baryonic feedback on the matter power spectrum.

Galaxy Alignments: An Overview

The alignments between galaxies, their underlying matter structures, and the cosmic web constitute vital ingredients for a comprehensive understanding of gravity, the nature of matter, and structure formation in the Universe. We provide an overview on the state of the art in the study of these alignment processes and their observational signatures, aimed at a non-specialist audience. The development of the field over the past one hundred years is briefly reviewed. We also discuss the impact of galaxy alignments on measurements of weak gravitational lensing, and discuss avenues for making theoretical and observational progress over the coming decade.

COSMOS: Stochastic Bias from Measurements of Weak Lensing and Galaxy Clustering

In the theory of structure formation, galaxies are biased tracers of the underlying matter density field. The statistical relation between galaxy and matter density field is commonly referred to as galaxy bias. In this paper, we test the linear bias model with weak-lensing and galaxy clustering measurements in the 2 deg^2 COSMOS field. We estimate the bias of galaxies between redshifts z = 0.2 and z = 1 and over correlation scales between R = 0.2 h^(–1) Mpc and R = 15 h^(–1) Mpc. We focus on three galaxy samples, selected in flux (simultaneous cuts I_(814W) 2 h^(–1) Mpc, our measurements support a model of bias increasing with redshift. The Tinker et al. fitting function provides a good fit to the data. We find the best-fit mass of the galaxy halos to be log (M_(200)/h^(–1) M_☉) = 11.7^(+0.6)_(–1.3) and log (M_(200)/h^(–1) M_☉) = 12.4^(+0.2)_(–2.9), respectively, for the low and high stellar-mass samples. In the halo model framework, bias is scale dependent with a change of slope at the transition scale between the one and the two halo terms. We detect a scale dependence of bias with a turndown at scale R = 2.3 ± 1.5 h^(–1) Mpc, in agreement with previous galaxy clustering studies. We find no significant amount of stochasticity, suggesting that a linear bias model is sufficient to describe our data. We use N-body simulations to quantify both the amount of cosmic variance and systematic errors in the measurement.

Galaxy alignments: Observations and impact on cosmology

Galaxy shapes are not randomly oriented, rather they are statistically aligned in a way that can depend on formation environment, history and galaxy type. Studying the alignment of galaxies can therefore deliver important information about the physics of galaxy formation and evolution as well as the growth of structure in the Universe. In this review paper we summarise key measurements of galaxy alignments, divided by galaxy type, scale and environment. We also cover the statistics and formalism necessary to understand the observations in the literature. With the emergence of weak gravitational lensing as a precision probe of cosmology, galaxy alignments have taken on an added importance because they can mimic cosmic shear, the effect of gravitational lensing by large-scale structure on observed galaxy shapes. This makes galaxy alignments, commonly referred to as intrinsic alignments, an important systematic effect in weak lensing studies. We quantify the impact of intrinsic alignments on cosmic shear surveys and finish by reviewing practical mitigation techniques which attempt to remove contamination by intrinsic alignments.

Galaxy Alignments: Theory, Modelling & Simulations

The shapes of galaxies are not randomly oriented on the sky. During the galaxy formation and evolution process, environment has a strong influence, as tidal gravitational fields in the large-scale structure tend to align nearby galaxies. Additionally, events such as galaxy mergers affect the relative alignments of both the shapes and angular momenta of galaxies throughout their history. These “intrinsic galaxy alignments” are known to exist, but are still poorly understood. This review will offer a pedagogical introduction to the current theories that describe intrinsic galaxy alignments, including the apparent difference in intrinsic alignment between early- and late-type galaxies and the latest efforts to model them analytically. It will then describe the ongoing efforts to simulate intrinsic alignments using both N

SUNGLASS: a new weak-lensing simulation pipeline

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Hierarchical cosmic shear power spectrum inference

-body and hydrodynamic simulations. Due to the relative youth of this field, there is still much to be done to understand intrinsic galaxy alignments and this review summarises the current state of the field, providing a solid basis for future work.

Cosmological information in Gaussianized weak lensing signals

A new cosmic shear analysis pipeline sunglass (Simulated UNiverses for Gravitational Lensing Analysis and Shear Surveys) is introduced. sunglass is a pipeline that rapidly generates simulated universes for weak-lensing and cosmic shear analysis. The pipeline forms suites of cosmological N-body simulations and performs tomographic cosmic shear analysis using line-of-sight integration through these simulations while saving the particle lightcone information. Galaxy shear and convergence catalogues with realistic 3D galaxy redshift distributions are produced for the purposes of testing weak-lensing analysis techniques and generating covariance matrices for data analysis and cosmological parameter estimation. We present a suite of fast medium-resolution simulations with shear and convergence maps for a generic 100 deg2 survey out to a redshift of z= 1.5, with angular power spectra agreeing with the theory to better than a few per cent accuracy up to l= 103 for all source redshifts up to z= 1.5 and wavenumbers up to l= 2000 for the source redshifts z≥ 1.1. At higher wavenumbers, there is a failure of the theoretical lensing power spectrum reflecting the known discrepancy of the Smith et al. fitting formula at high physical wavenumbers. A two-parameter Gaussian likelihood analysis of σ8 and Ωm is also performed on the suite of simulations, demonstrating that the cosmological parameters are recovered from the simulations and the covariance matrices are stable for data analysis. We find that any residual bias in our calculation is below our uncertainty within the 1σ confidence limits. The sunglass pipeline should be an invaluable tool in weak-lensing analysis.

Metallicity gradients of disc stars for a cosmologically simulated galaxy

We develop a Bayesian hierarchical modelling approach for cosmic shear power spectrum inference, jointly sampling from the posterior distribution of the cosmic shear eld and its (tomographic) power spectra. Inference of the shear power spectrum is a powerful intermediate product for a cosmic shear analysis, since it requires very few model assumptions and can be used to perform inference on a wide range of cosmological models a posteriori without loss of information. We show that joint posterior for the shear map and power spectrum can be sampled eectively by Gibbs sampling, iteratively drawing samples from the map and power spectrum, each conditional on the other. This approach neatly circumvents diculties associated with complicated survey geometry and masks that plague frequentist power spectrum estimators, since the power spectrum inference provides prior information about the eld in masked regions at every sampling step. We demonstrate this approach for inference of tomographic shear E-mode, B-mode and EB-cross power spectra from a simulated galaxy shear catalogue with a number of important features; galaxies distributed on the sky and in redshift with photometric redshift uncertainties, realistic random ellipticity noise for every galaxy and a complicated survey mask. The obtained posterior distributions for the tomographic power spectrum coecients recover the underlying simulated power spectra for both E- and B-modes, where the latter are recovered at a level of 1-2 orders of magnitude below the ellipticity noise level.

Galaxy shapes and alignments in the MassiveBlack-II hydrodynamic and dark matter-only simulations

Gaussianizing the one-point distribution of the weak gravitational lensing convergence has recently been shown to increase the signal-to-noise ratio contained in two-point statistics. We investigate the information on cosmology that can be extracted from the transformed convergence fields. Employing Box–Cox transformations to determine optimal transformations to Gaussianity, we develop analytical models for the transformed power spectrum, including effects of noise and smoothing. We find that optimized Box–Cox transformations perform substantially better than an offset logarithmic transformation in Gaussianizing the convergence, but both yield very similar results for the signal-to-noise ratio. None of the transformations is capable of eliminating correlations of the power spectra between different angular frequencies, which we demonstrate to have a significant impact on the errors in cosmology. Analytic models of the Gaussianized power spectrum yield good fits to the simulations and produce unbiased parameter estimates in the majority of cases, where the exceptions can be traced back to the limitations in modelling the higher order correlations of the original convergence. In the ideal case, without galaxy shape noise, we find an increase in the cumulative signal-to-noise ratio by a factor of 2.6 for angular frequencies up to l= 1500, and a decrease in the area of the confidence region in the Ωm–σ8 plane, measured in terms of q-values, by a factor of 4.4 for the best performing transformation. When adding a realistic level of shape noise, all transformations perform poorly with little decorrelation of angular frequencies, a maximum increase in signal-to-noise ratio of 34 per cent, and even slightly degraded errors on cosmological parameters. We argue that to find Gaussianizing transformations of practical use, it will be necessary to go beyond transformations of the one-point distribution of the convergence, extend the analysis deeper into the non-linear regime and resort to an exploration of parameter space via simulations.