We compare the shapes and intrinsic alignments of galaxies in the MassiveBlack-II cosmological hydrodynamic simulation (MBII) to those in a dark matter-only (DMO) simulation performed with the same volume (100$h^{-1}$Mpc)$^{3}$, cosmological paramete
rs, and initial conditions. Understanding the impact of baryonic physics on galaxy shapes and alignments and their relation to the dark matter distribution should prove useful to map the intrinsic alignments of galaxies from hydrodynamic to dark matter-only simulations. We find that dark matter subhalos are typically rounder in MBII, and the shapes of stellar matter in low mass galaxies are more misaligned with the shapes of the dark matter of the corresponding subhalos in the DMO simulation. At $z=0.06$, the fractional difference in the mean misalignment angle between MBII and DMO simulations varies from $sim 28 % - 12 %$ in the mass range $10^{10.8} - 6.0 times 10^{14} h^{-1}M_{odot}$. We study the dark matter halo shapes and alignments as a function of radius, and find that while galaxies in MBII are more aligned with the inner parts of their dark matter subhalos, there is no radial trend in their alignments with the corresponding subhalo in the DMO simulation. This result highlights the importance of baryonic physics in determining the alignment of the galaxy with respect to the inner parts of the halo. Finally, we compare the ellipticity-direction (ED) correlation for galaxies to that for dark matter halos, finding that it is suppressed on all scales by stellar-dark matter misalignment. In the projected shape-density correlation ($w_{delta+}$), which includes ellipticity weighting, this effect is partially canceled by the higher mean ellipticities of the stellar component, but differences of order $30-40%$ remain on scales $> 1$ Mpc over a range of subhalo masses, with scale-dependent effects below $1$ Mpc.
We present a pedagogical review of the weak gravitational lensing measurement process and its connection to major scientific questions such as dark matter and dark energy. Then we describe common ways of parametrizing systematic errors and understand
ing how they affect weak lensing measurements. Finally, we discuss several instrumental systematics and how they fit into this context, and conclude with some future perspective on how progress can be made in understanding the impact of instrumental systematics on weak lensing measurements.
We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT
3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically-varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially-varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by $sim 1$ per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the S{e}rsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods results support the simple model in which additive shear biases depend linearly on PSF ellipticity.
In this review, I discuss the use of galaxy-galaxy weak lensing measurements to study the masses of dark matter halos in which galaxies reside. After summarizing how weak gravitational lensing measurements can be interpreted in terms of halo mass, I
review measurements that were used to derive the relationship between optical galaxy mass tracers, such as stellar mass or luminosity, and dark matter halo mass. Measurements of galaxy-galaxy lensing from the past decade have led to increasingly tight constraints on the connection between dark matter halo mass and optical mass tracers, including both the mean relationships between these quantities and the intrinsic scatter between them. I also review some of the factors that can complicate analysis, such as the choice of modeling procedure, and choices made when dividing up samples of lens galaxies.
The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is an image analysis competition that aims to test algorithms to measure weak gravitational lensing from astronomical images. The challenge started in October 2013 and ends 30 April 2014
. The challenge focuses on testing the impact on weak lensing measurements of realistically complex galaxy morphologies, realistic point spread function, and combination of multiple different exposures. It includes simulated ground- and space-based data. The details of the challenge are described in [15], and the challenge website and its leader board can be found at http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/, respectively.
A joint analysis of the clustering of galaxies and their weak gravitational lensing signal is well-suited to simultaneously constrain the galaxy-halo connection as well as the cosmological parameters by breaking the degeneracy between galaxy bias and
the amplitude of clustering signal. In a series of two papers, we perform such an analysis at the highest redshift ($zsim0.53$) in the literature using CMASS galaxies in the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey Eleventh Data Release (SDSS-III/BOSS DR11) catalog spanning 8300~deg$^2$. In this paper, we present details of the clustering and weak lensing measurements of these galaxies. We define a subsample of 400,916 CMASS galaxies based on their redshifts and stellar mass estimates so that the galaxies constitute an approximately volume-limited and similar population over the redshift range $0.47le zle 0.59$. We obtain a signal-to-noise ratio $S/Nsimeq 56$ for the galaxy clustering measurement. We also explore the redshift and stellar mass dependence of the clustering signal. For the weak lensing measurement, we use existing deeper imaging data from the CFHTLS with publicly available shape and photometric redshift catalogs from CFHTLenS, but only in a 105~deg$^2$ area which overlaps with BOSS. This restricts the lensing measurement to only 5,084 CMASS galaxies. After careful systematic tests, we find a highly significant detection of the CMASS weak lensing signal, with total $S/Nsimeq 26$. These measurements form the basis of the halo occupation distribution and cosmology analysis presented in More et al. (Paper II).
The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is the third in a series of image analysis challenges, with a goal of testing and facilitating the development of methods for analyzing astronomical images that will be used to measure w
eak gravitational lensing. This measurement requires extremely precise estimation of very small galaxy shape distortions, in the presence of far larger intrinsic galaxy shapes and distortions due to the blurring kernel caused by the atmosphere, telescope optics, and instrumental effects. The GREAT3 challenge is posed to the astronomy, machine learning, and statistics communities, and includes tests of three specific effects that are of immediate relevance to upcoming weak lensing surveys, two of which have never been tested in a community challenge before. These effects include realistically complex galaxy models based on high-resolution imaging from space; spatially varying, physically-motivated blurring kernel; and combination of multiple different exposures. To facilitate entry by people new to the field, and for use as a diagnostic tool, the simulation software for the challenge is publicly available, though the exact parameters used for the challenge are blinded. Sample scripts to analyze the challenge data using existing methods will also be provided. See http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/ for more information.
Nonlinear redshift-space distortions, the Finger-of-God (FoG) effect, can complicate the interpretation of the galaxy power spectrum. Here, we demonstrate the method proposed by Hikage et al. (2012) to use complimentary observations to directly const
rain this effect on the data. We use catalogs of Luminous Red Galaxies (LRGs) and photometric galaxies from the SDSS DR7 to measure the redshift-space power spectrum of LRGs, the cross-correlation of LRGs with the shapes of background photometric galaxies (galaxy-galaxy weak lensing), and the projected cross-correlation of LRGs with photometric galaxies having similar photometric redshifts to the LRG spectroscopic redshift. All of these measurements use a reconstructed halo field. While we use the position of each LRG for single LRG systems, we compare the measurements using different halo-center proxies for multiple-LRG systems (4.5 per cent of all the halos): the brightest LRG position (BLRG), the faintest LRG position (FLRG) and their arithmetical mean position (Mean), respectively, in each system. We find significant differences in the measured correlations of different centers, showing consistent off-centering effects in the three observables. By comparing the measurements with a halo model that treats the satellite photometric galaxies as being distributed according to a generalized NFW profile, we find that about 40 (70) per cent of BLRGs (FLRGs) are off-centered satellite galaxies in the multiple-LRG systems. The satellite LRGs have typical off-centering radius of about 400 kpc/h, and velocity dispersion of about 500 km/s in host halos with a mean mass of 1.6x10^14 Ms/h. We show that, if LRGs in the single LRG systems have similar offsets, the residual FoG contamination in the LRG power spectrum can be significant at k>0.1 h/Mpc, which may cause a bias in cosmological parameters such as the neutrino mass.
Recent studies have shown that the cross-correlation coefficient between galaxies and dark matter is very close to unity on scales outside a few virial radii of galaxy halos, independent of the details of how galaxies populate dark matter halos. This
finding makes it possible to determine the dark matter clustering from measurements of galaxy-galaxy weak lensing and galaxy clustering. We present new cosmological parameter constraints based on large-scale measurements of spectroscopic galaxy samples from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7). We generalise the approach of Baldauf et al. (2010) to remove small scale information (below 2 and 4 Mpc/h for lensing and clustering measurements, respectively), where the cross-correlation coefficient differs from unity. We derive constraints for three galaxy samples covering 7131 sq. deg., containing 69150, 62150, and 35088 galaxies with mean redshifts of 0.11, 0.28, and 0.40. We clearly detect scale-dependent galaxy bias for the more luminous galaxy samples, at a level consistent with theoretical expectations. When we vary both sigma_8 and Omega_m (and marginalise over non-linear galaxy bias) in a flat LCDM model, the best-constrained quantity is sigma_8 (Omega_m/0.25)^{0.57}=0.80 +/- 0.05 (1-sigma, stat. + sys.), where statistical and systematic errors have comparable contributions, and we fixed n_s=0.96 and h=0.7. These strong constraints on the matter clustering suggest that this method is competitive with cosmic shear in current data, while having very complementary and in some ways less serious systematics. We therefore expect that this method will play a prominent role in future weak lensing surveys. When we combine these data with WMAP7 CMB data, constraints on sigma_8, Omega_m, H_0, w_{de} and sum m_{ u} become 30--80 per cent tighter than with CMB data alone, since our data break several parameter degeneracies.
We present redshift probability distributions for galaxies in the SDSS DR8 imaging data. We used the nearest-neighbor weighting algorithm presented in Lima et al. 2008 and Cunha et al. 2009 to derive the ensemble redshift distribution N(z), and indiv
idual redshift probability distributions P(z) for galaxies with r < 21.8. As part of this technique, we calculated weights for a set of training galaxies with known redshifts such that their density distribution in five dimensional color-magnitude space was proportional to that of the photometry-only sample, producing a nearly fair sample in that space. We then estimated the ensemble N(z) of the photometric sample by constructing a weighted histogram of the training set redshifts. We derived P(z) s for individual objects using the same technique, but limiting to training set objects from the local color-magnitude space around each photometric object. Using the P(z) for each galaxy, rather than an ensemble N(z), can reduce the statistical error in measurements that depend on the redshifts of individual galaxies. The spectroscopic training sample is substantially larger than that used for the DR7 release, and the newly added PRIMUS catalog is now the most important training set used in this analysis by a wide margin. We expect the primary source of error in the N(z) reconstruction is sample variance: the training sets are drawn from relatively small volumes of space. Using simulations we estimated the uncertainty in N(z) at a given redshift is 10-15%. The uncertainty on calculations incorporating N(z) or P(z) depends on how they are used; we discuss the case of weak lensing measurements. The P(z) catalog is publicly available from the SDSS website.
