805 research outputs found
Accuracy of core mass estimates in simulated observations of dust emission
We study the reliability of mass estimates obtained for molecular cloud cores
using sub-millimetre and infrared dust emission. We use magnetohydrodynamic
simulations and radiative transfer to produce synthetic observations with
spatial resolution and noise levels typical of Herschel surveys. We estimate
dust colour temperatures using different pairs of intensities, calculate column
densities and compare the estimated masses with the true values. We compare
these results to the case when all five Herschel wavelengths are available. We
investigate the effects of spatial variations of dust properties and the
influence of embedded heating sources. Wrong assumptions of dust opacity and
its spectral index beta can cause significant systematic errors in mass
estimates. These are mainly multiplicative and leave the slope of the mass
spectrum intact, unless cores with very high optical depth are included.
Temperature variations bias colour temperature estimates and, in quiescent
cores with optical depths higher than for normal stable cores, masses can be
underestimated by up to one order of magnitude. When heated by internal
radiation sources the observations recover the true mass spectra. The shape,
although not the position, of the mass spectrum is reliable against
observational errors and biases introduced in the analysis. This changes only
if the cores have optical depths much higher than expected for basic
hydrostatic equilibrium conditions. Observations underestimate the value of
beta whenever there are temperature variations along the line of sight. A bias
can also be observed when the true beta varies with wavelength. Internal
heating sources produce an inverse correlation between colour temperature and
beta that may be difficult to separate from any intrinsic beta(T) relation of
the dust grains. This suggests caution when interpreting the observed mass
spectra and the spectral indices.Comment: Revised version, 17 pages, 17 figures, submitted to A&
Scaling relations of supersonic turbulence in star-forming molecular clouds
We present a direct numerical and analytical study of driven supersonic MHD
turbulence that is believed to govern the dynamics of star-forming molecular
clouds. We describe statistical properties of the turbulence by measuring the
velocity difference structure functions up to the fifth order. In particular,
the velocity power spectrum in the inertial range is found to be close to E(k)
\~ k^{-1.74}, and the velocity difference scales as ~ L^{0.42}. The
results agree well with the Kolmogorov--Burgers analytical model suggested for
supersonic turbulence in [astro-ph/0108300]. We then generalize the model to
more realistic, fractal structure of molecular clouds, and show that depending
on the fractal dimension of a given molecular cloud, the theoretical value for
the velocity spectrum spans the interval [-1.74 ... -1.89], while the
corresponding window for the velocity difference scaling exponent is [0.42 ...
0.78].Comment: 17 pages, 6 figures include
Multivariate Nonparametric Estimation of the Pickands Dependence Function using Bernstein Polynomials
Many applications in risk analysis, especially in environmental sciences,
require the estimation of the dependence among multivariate maxima. A way to do
this is by inferring the Pickands dependence function of the underlying
extreme-value copula. A nonparametric estimator is constructed as the sample
equivalent of a multivariate extension of the madogram. Shape constraints on
the family of Pickands dependence functions are taken into account by means of
a representation in terms of a specific type of Bernstein polynomials. The
large-sample theory of the estimator is developed and its finite-sample
performance is evaluated with a simulation study. The approach is illustrated
by analyzing clusters consisting of seven weather stations that have recorded
weekly maxima of hourly rainfall in France from 1993 to 2011
A Corona Australis cloud filament seen in NIR scattered light I. Comparison with extinction of background stars
With current near-infrared (NIR) instruments the near-infrared light
scattered from interstellar clouds can be mapped over large areas. The surface
brightness carries information on the line-of-sight dust column density.
Therefore, scattered light could provide an important tool to study mass
distribution in quiescent interstellar clouds at a high, even sub-arcsecond
resolution. We wish to confirm the assumption that light scattering dominates
the surface brightness in all NIR bands. Furthermore, we want to show that
scattered light can be used for an accurate estimation of dust column densities
in clouds with Av in the range 1-15mag. We have obtained NIR images of a
quiescent filament in the Corona Australis molecular cloud. The observations
provide maps of diffuse surface brightness in J, H, and Ks bands. Using the
assumption that signal is caused by scattered light we convert surface
brightness data into a map of dust column density. The same observations
provide colour excesses for a large number of background stars. These data are
used to derive an extinction map of the cloud. The two, largely independent
tracers of the cloud structure are compared. Results. In regions below Av=15m
both diffuse surface brightness and background stars lead to similar column
density estimates. The existing differences can be explained as a result of
normal observational errors and bias in the sampling of extinctions provided by
the background stars. There is no indication that thermal dust emission would
have a significant contribution even in the Ks band. The results show that,
below Av=15mag, scattered light does provide a reliable way to map cloud
structure. Compared with the use of background stars it can also in practice
provide a significantly higher spatial resolution.Comment: 14 pages, 15 figures, accepted to A&A, the version includes small
changes in the text and an added appendi
The pressure distribution in thermally bistable turbulent flows
We present a systematic numerical study of the effect of turbulent velocity
fluctuations on the thermal pressure distribution in thermally bistable flows.
The simulations employ a random turbulent driving generated in Fourier space
rather than star-like heating. The turbulent fluctuations are characterized by
their rms Mach number M and the energy injection wavenumber, k_for. Our results
are consistent with the picture that as either of these parameters is
increased, the local ratio of turbulent crossing time to cooling time
decreases, causing transient structures in which the effective behavior is
intermediate between the thermal-equilibrium and adiabatic regimes. As a
result, the effective polytropic exponent gamma_ef ranges between ~0.2 to ~1.1.
The fraction of high-density zones with P>10^4 Kcm^-3 increases from roughly
0.1% at k_for=2 and M=0.5 to roughly 70% for k_for=16 and M=1.25. A preliminary
comparison with the pressure measurements of Jenkins (2004) favors our case
with M=0.5 and k_for=2. In all cases, the dynamic range of the pressure summed
over the entire density range, typically spans 3-4 orders of magnitude. The
total pressure histogram widens as the Mach number is increased, and develops
near-power-law tails at high (resp.low) pressures when gamma_ef<~ 0.5 (resp.
gamma_ef>~ 1), which occurs at k_for=2 (resp.k_for=16) in our simulations. The
opposite side of the pressure histogram decays rapidly, in an approx. lognormal
form. Our results show that turbulent advection alone can generate large
pressure scatters, with power-law high-P tails for large-scale driving, and
provide validation for approaches attempting to derive the shape of the
pressure histogram through a change of variable from the known form of the
density histogram, such as that performed by MacLow et al.(2004).Comment: to be published in Ap
Simulating Supersonic Turbulence in Magnetized Molecular Clouds
We present results of large-scale three-dimensional simulations of weakly
magnetized supersonic turbulence at grid resolutions up to 1024^3 cells. Our
numerical experiments are carried out with the Piecewise Parabolic Method on a
Local Stencil and assume an isothermal equation of state. The turbulence is
driven by a large-scale isotropic solenoidal force in a periodic computational
domain and fully develops in a few flow crossing times. We then evolve the flow
for a number of flow crossing times and analyze various statistical properties
of the saturated turbulent state. We show that the energy transfer rate in the
inertial range of scales is surprisingly close to a constant, indicating that
Kolmogorov's phenomenology for incompressible turbulence can be extended to
magnetized supersonic flows. We also discuss numerical dissipation effects and
convergence of different turbulence diagnostics as grid resolution refines from
256^3 to 1024^3 cells.Comment: 10 pages, 3 figures, to appear in the proceedings of the DOE/SciDAC
2009 conferenc
Structure Function Scaling in Compressible Super-Alfvenic MHD Turbulence
Supersonic turbulent flows of magnetized gas are believed to play an
important role in the dynamics of star-forming clouds in galaxies.
Understanding statistical properties of such flows is crucial for developing a
theory of star formation. In this letter we propose a unified approach for
obtaining the velocity scaling in compressible and super--Alfv\'{e}nic
turbulence, valid for arbitrary sonic Mach number, \ms. We demonstrate with
numerical simulations that the scaling can be described with the
She--L\'{e}v\^{e}que formalism, where only one parameter, interpreted as the
Hausdorff dimension of the most intense dissipative structures, needs to be
varied as a function of \ms. Our results thus provide a method for obtaining
the velocity scaling in interstellar clouds once their Mach numbers have been
inferred from observations.Comment: published in Physical Review Letter
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