Cluster Formation in Contracting Molecular Clouds

We explore, through a simplified, semi-analytic model, the formation of dense clusters containing massive stars. The parent cloud spawning the cluster is represented as an isothermal sphere. This sphere is in near force balance between self-gravity and turbulent pressure. Self-gravity, mediated by turbulent dissipation, drives slow contraction of the cloud, eventually leading to a sharp central spike in density and the onset of dynamical instability. We suggest that, in a real cloud, this transition marks the late and rapid production of massive stars. We also offer an empirical prescription, akin to the Schmidt law, for low-mass star formation in our contracting cloud. Applying this prescription to the Orion Nebula Cluster, we are able to reproduce the accelerating star formation previously inferred from the distribution of member stars in the HR diagram. The cloud turns about 10 percent of its mass into low-mass stars before becoming dynamically unstable. Over a cloud free-fall time, this figure drops to 1 percent, consistent with the overall star formation efficiency of molecular clouds in the Galaxy.Comment: To appear in ApJ Vol. 667, September 2

Cosmological constraints from the convergence 1-point probability distribution

We examine the cosmological information available from the 1-point probability distribution (PDF) of the weak-lensing convergence field, utilizing fast L-PICOLA simulations and a Fisher analysis. We find competitive constraints in the $\Omega_m$-$\sigma_8$ plane from the convergence PDF with $188\ arcmin^2$ pixels compared to the cosmic shear power spectrum with an equivalent number of modes ($\ell < 886$). The convergence PDF also partially breaks the degeneracy cosmic shear exhibits in that parameter space. A joint analysis of the convergence PDF and shear 2-point function also reduces the impact of shape measurement systematics, to which the PDF is less susceptible, and improves the total figure of merit by a factor of $2-3$, depending on the level of systematics. Finally, we present a correction factor necessary for calculating the unbiased Fisher information from finite differences using a limited number of cosmological simulations.Comment: 10 pages, 5 figure

Detecting Baryon Acoustic Oscillations in Dark Matter from Kinematic Weak Lensing Surveys

We investigate the feasibility of extracting Baryon Acoustic Oscillations (BAO) from cosmic shear tomography. We particularly focus on the BAO scale precision that can be achieved by future spectroscopy-based, kinematic weak lensing (KWL) surveys \citep[e.g.,][]{Huff13} in comparison to the traditional photometry-based weak lensing surveys. We simulate cosmic shear tomography data of such surveys with a few simple assumptions to focus on the BAO information, extract the spacial power spectrum, and constrain the recovered BAO feature. Due to the small shape noise and the shape of the lensing kernel, we find that a Dark Energy Task Force Stage IV version of such KWL survey can detect the BAO feature in dark matter by $3$-$\sigma$ and measure the BAO scale at the precision level of 4\% while it will be difficult to detect the feature in photometry-based weak lensing surveys. With a more optimistic assumption, a KWL-Stage IV could achieve a $\sim 2\%$ BAO scale measurement with $4.9$-$\sigma$ confidence. A built-in spectroscopic galaxy survey within such KWL survey will allow cross-correlation between galaxies and cosmic shear, which will tighten the constraint beyond the lower limit we present in this paper and therefore possibly allow a detection of the BAO scale bias between galaxies and dark matter.Comment: 18 pages, 10 figures; revised arguments in section 2, results unchange

Intrinsic alignments of group and cluster galaxies in photometric surveys

Intrinsic alignments of galaxies have been shown to contaminate weak gravitational lensing observables on linear scales, $r>$ 10 $h^{-1}$Mpc, but studies of alignments in the non-linear regime have thus far been inconclusive. We present an estimator for extracting the intrinsic alignment signal of galaxies around stacked clusters of galaxies from multiband imaging data. Our estimator removes the contamination caused by galaxies that are gravitationally lensed by the clusters and scattered in redshift space due to photometric redshift uncertainties. It uses posterior probability distributions for the redshifts of the galaxies in the sample and it is easily extended to obtain the weak gravitational lensing signal while removing the intrinsic alignment contamination. We apply this algorithm to groups and clusters of galaxies identified in the Sloan Digital Sky Survey `Stripe 82' coadded imaging data over $\sim 150$ deg$^2$. We find that the intrinsic alignment signal around stacked clusters in the redshift range $0.1<z<0.4$ is consistent with zero. In terms of the tidal alignment model of Catelan et al. (2001), we set joint constraints on the strength of the alignment and the bias of the lensing groups and clusters on scales between 0.1 and $10\,h^{-1}$ Mpc, $b_LC_1\rho_{\rm crit} = -2_{-14}^{+14} \times 10^{-4}$. This constrains the contamination fraction of alignment to lensing signal to the range between $[-18,23]$ per cent below scales of 1 $h^{-1}$ Mpc at 95 per cent confidence level, and this result depends on our photometric redshift quality and selection criteria used to identify background galaxies. Our results are robust to the choice of photometric band in which the shapes are measured ($i$ and $r$) and to centring on the Brightest Cluster Galaxy or on the geometrical centre of the clusters.Comment: 30 pages, 16 figures, published in MNRA