Sample variance in the local measurements of the Hubble constant

The current $>3\sigma$ tension between the Hubble constant $H_0$ measured from local distance indicators and from cosmic microwave background is one of the most highly debated issues in cosmology, as it possibly indicates new physics or unknown systematics. In this work, we explore whether this tension can be alleviated by the sample variance in the local measurements, which use a small fraction of the Hubble volume. We use a large-volume cosmological $N$-body simulation to model the local measurements and to quantify the variance due to local density fluctuations and sample selection. We explicitly take into account the inhomogeneous spatial distribution of type Ia supernovae. Despite the faithful modelling of the observations, our results confirm previous findings that sample variance in the local Hubble constant $(H_0^{\rm loc})$ measurements is small; we find $\sigma(H_0^{\rm loc})=0.31\,{\rm km\ s^{-1}Mpc^{-1}}$, a nearly negligible fraction of the$\sim6\,{\rm km\ s^{-1}Mpc^{-1}}$necessary to explain the difference between the local and the global$H_0$measurements. While the$H_0$tension could in principle be explained by our local neighbourhood being a underdense region of radius$\sim 150 \,\rm Mpc$, the extreme required underdensity of such a void$(\delta\simeq -0.8)$makes it very unlikely in a$\Lambda$CDM universe, and it also violates existing observational constraints. Therefore, sample variance in a$\Lambda$CDM universe cannot appreciably alleviate the tension in$H_0$ measurements even after taking into account the inhomogeneous selection of type Ia supernovae.Comment: 10 pages, 6 figures, 1 table; main result in Figure 3; replaced to match published versio

Optical Selection Bias and Projection Effects in Stacked Galaxy Cluster Weak Lensing

Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale dependence and is approximately 20–60 per cent for ΔΣ at large scales. This selection bias largely originates from spurious member galaxies within ±20–60 h−1Mpc along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy–halo connection models

Modelling Galaxy Cluster Triaxiality in Stacked Cluster Weak Lensing Analyses

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude ln (A) is boosted from the lowest to highest orientation bin with a significance of 14σ, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark haloes in different orientation bins resemble a ‘bottleneck’ shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology – miscentering and projection – and find a null correlation. The resulting mass bias predicted from our templates confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters

Clustering Assisted Fundamental Matrix Estimation

In computer vision, the estimation of the fundamental matrix is a basic problem that has been extensively studied. The accuracy of the estimation imposes a significant influence on subsequent tasks such as the camera trajectory determination and 3D reconstruction. In this paper we propose a new method for fundamental matrix estimation that makes use of clustering a group of 4D vectors. The key insight is the observation that among the 4D vectors constructed from matching pairs of points obtained from the SIFT algorithm, well-defined cluster points tend to be reliable inliers suitable for fundamental matrix estimation. Based on this, we utilizes a recently proposed efficient clustering method through density peaks seeking and propose a new clustering assisted method. Experimental results show that the proposed algorithm is faster and more accurate than currently commonly used methods.Comment: 12 pages, 8 figures, 3 tables, Second International Conference on Computer Science and Information Technology (COSIT 2015) March 21~22, 2015, Geneva, Switzerlan

Early Embryos Reprogram DNA Methylation in Two Steps

While DNA cytosine methylation is relatively stable in somatic tissues, it is highly dynamic during preimplantation development. A recent study in Nature by Meissner and colleagues (Smith et al., 2012) now reveals dramatic shifts in DNA methylation during the earliest stages of mouse embryogenesis at genome scale and base resolution