Cluster Magnification & the Mass-Richness Relation in CFHTLenS

Gravitational lensing magnification is measured with a significance of 9.7 sigma on a large sample of galaxy clusters in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). This survey covers ~154 deg^2 and contains over 18,000 cluster candidates at redshifts 0.2 <= z <= 0.9, detected using the 3D-Matched Filter cluster-finder of Milkeraitis et al. (2010). We fit composite-NFW models to the ensemble, accounting for cluster miscentering, source-lens redshift overlap, as well as nearby structure (the 2-halo term), and recover mass estimates of the cluster dark matter halos in range of ~10^13 M_sun to 2*10^14 M_sun. Cluster richness is measured for the entire sample, and we bin the clusters according to both richness and redshift. A mass-richness relation M_200 = M_0 (N_200 / 20)^beta is fit to the measurements. For two different cluster miscentering models we find consistent results for the normalization and slope, M_0 = (2.3 +/- 0.2)*10^13 M_sun, beta = 1.4 +/- 0.1 and M_0 = (2.2 +/- 0.2)*10^13 M_sun, beta = 1.5 +/- 0.1. We find that accounting for the full redshift distribution of lenses and sources is important, since any overlap can have an impact on mass estimates inferred from flux magnification.Comment: 11 pages, 8 figures, Accepted to MNRA

CFHTLenS: A Weak Lensing Shear Analysis of the 3D-Matched-Filter Galaxy Clusters

We present the cluster mass-richness scaling relation calibrated by a weak lensing analysis of >18000 galaxy cluster candidates in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). Detected using the 3D-Matched-Filter cluster-finder of Milkeraitis et al., these cluster candidates span a wide range of masses, from the small group scale up to $\sim10^{15} M_{\odot}$, and redshifts 0.2 $\lesssim z\lesssim$ 0.9. The total significance of the stacked shear measurement amounts to 54$\sigma$. We compare cluster masses determined using weak lensing shear and magnification, finding the measurements in individual richness bins to yield 1$\sigma$ compatibility, but with magnification estimates biased low. This first direct mass comparison yields important insights for improving the systematics handling of future lensing magnification work. In addition, we confirm analyses that suggest cluster miscentring has an important effect on the observed 3D-MF halo profiles, and we quantify this by fitting for projected cluster centroid offsets, which are typically $\sim$ 0.4 arcmin. We bin the cluster candidates as a function of redshift, finding similar cluster masses and richness across the full range up to $z \sim$ 0.9. We measure the 3D-MF mass-richness scaling relation $M_{200} = M_0 (N_{200} / 20)^\beta$. We find a normalization $M_0 \sim (2.7^{+0.5}_{-0.4}) \times 10^{13} M_{\odot}$, and a logarithmic slope of $\beta \sim 1.4 \pm 0.1$, both of which are in 1$\sigma$ agreement with results from the magnification analysis. We find no evidence for a redshift-dependence of the normalization. The CFHTLenS 3D-MF cluster catalogue is now available at cfhtlens.org.Comment: 3D-MF cluster catalog is NOW AVAILABLE at cfhtlens.org. Magnification-shear mass comparison in Figure 10. 19 pages, 10 figures. Accepted to MNRA

Magnification by Galaxy Group Dark Matter Halos

We report on the detection of gravitational lensing magnification by a population of galaxy groups, at a significance level of 4.9 sigma. Using X-ray selected groups in the COSMOS 1.64 deg^2 field, and high-redshift Lyman break galaxies as sources, we measure a lensing-induced angular cross-correlation between the samples. After satisfying consistency checks that demonstrate we have indeed detected a magnification signal, and are not suffering from contamination by physical overlap of samples, we proceed to implement an optimally weighted cross-correlation function to further boost the signal to noise of the measurement. Interpreting this optimally weighted measurement allows us to study properties of the lensing groups. We model the full distribution of group masses using a composite-halo approach, considering both the singular isothermal sphere and Navarro-Frenk-White profiles, and find our best fit values to be consistent with those recovered using the weak-lensing shear technique. We argue that future weak-lensing studies will need to incorporate magnification along with shear, both to reduce residual systematics and to make full use of all available source information, in an effort to maximize scientific yield of the observations.Comment: 6 pages, 3 figures, Accepted by Ap

CFHTLenS: a weak lensing shear analysis of the 3D-Matched-Filter galaxy clusters

We present the cluster mass-richness scaling relation calibrated by a weak lensing analysis of ≳ 18000 galaxy cluster candidates in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). Detected using the 3D-Matched-Filter (MF) cluster-finder of Milkeraitis etal., these cluster candidates span a wide range of masses, from the small group scale up to∼1015 M⊙, and redshifts 0.2≲z≲0.9. The total significance of the stacked shear measurement amounts to 54σ. We compare cluster masses determined using weak lensing shear and magnification, finding the measurements in individual richness bins to yield 1σ compatibility, but with magnification estimates biased low. This first direct mass comparison yields important insights for improving the systematics handling of future lensing magnification work. In addition, we confirm analyses that suggest cluster miscentring has an important effect on the observed 3D-MF halo profiles, and we quantify this by fitting for projected cluster centroid offsets, which are typically∼0.4arcmin. We bin the cluster candidates as a function of redshift, finding similar cluster masses and richness across the full range up to z∼0.9. We measure the 3D-MF mass-richness scaling relation M200=M0(N200/20)β. We find a normalization $M_0 \sim (2.7^{+0.5}_{-0.4}) \times 10^{13} \,\mathrm{M}_{{\odot }}$, and a logarithmic slope of β∼1.4±0.1, both of which are in 1σ agreement with results from the magnification analysis. We find no evidence for a redshift dependence of the normalization. The CFHTLenS 3D-MF cluster catalogue is now available at cfhtlens.or

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

cluster-lensing: a new Python package for galaxy clusters & lensing

<p>Short demo and links to a newly released pure Python package called cluster-lensing. This package contains tools to calculate galaxy cluster halo properties and weak lensing shear and magnification profiles. The model can easily include the effects of possible cluster miscentering offsets, which would otherwise lead to biased mass or concentration estimates.</p

cluster-lensing: v0.1.2

<p>v0.1.2 release notes: clusters.ClusterEnsemble() accepts input cosmology as any astropy.cosmology object</p