265 research outputs found
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 - plane from the convergence PDF with
pixels compared to the cosmic shear power spectrum with an
equivalent number of modes (). 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 , 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 - 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 BAO scale measurement with
- 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
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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, 10 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 deg. We find that the intrinsic alignment signal around
stacked clusters in the redshift range 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 Mpc, . This constrains the contamination fraction of
alignment to lensing signal to the range between per cent below
scales of 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 ( and ) and to centring
on the Brightest Cluster Galaxy or on the geometrical centre of the clusters.Comment: 30 pages, 16 figures, published in MNRA
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