Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userCharting nearby dust clouds using Gaia data only
93
0
0.0
(
0
)
Added by
Reimar Heinrich Leike
Publication date
2019
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Aims: Highly resolved maps of the local Galactic dust are an important ingredient for sky emission models. In nearly the whole electromagnetic spectrum one can see imprints of dust, many of which originate from dust clouds within 300pc. Having a detailed 3D reconstruction of these local dust clouds enables detailed studies, helps to quantify the impact on other observables and is a milestone necessary to enable larger reconstructions, as every sightline for more distant objects will pass through the local dust. Methods: To infer the dust density we use parallax and absorption estimates published by the Gaia collaboration in their second data release. We model the dust as a log-normal process using a hierarchical Bayesian model. We also infer non-parametrically the kernel of the log-normal process, which corresponds to the physical spatial correlation power spectrum of the log-density. Results: Using only Gaia data of the second Gaia data release, we reconstruct the 3D dust density and its spatial correlation spectrum in a 600pc cube centered on the Sun. We report a spectral index of the logarithmic dust density of $3.1$ on Fourier scales with wavelengths between 2pc and 125pc. The resulting 3D dust map as well as the power spectrum and posterior samples are publicly available for download.
rate research
Read More
Aims: Mapping the interstellar medium in 3D provides a wealth of insights into its inner working. The Milky Way is the only galaxy for which detailed 3D mapping can be achieved in principle. In this paper, we reconstruct the dust density in and around the local super-bubble. Methods: The combined data from surveys such as Gaia, 2MASS, PANSTARRS, and ALLWISE provide the necessary information to make detailed maps of the interstellar medium in our surrounding. To this end, we used variational inference and Gaussian processes to model the dust extinction density, exploiting its intrinsic correlations. Results: We reconstructed a highly resolved dust map, showing the nearest dust clouds at a distance of up to 400pc with a resolution of 1pc. Conclusions: Our reconstruction provides insights into the structure of the interstellar medium. We compute summary statistics of the spectral index and the 1-point function of the logarithmic dust extinction density, which may constrain simulations of the interstellar medium that achieve a similar resolution.
The SFiNCs (Star Formation in Nearby Clouds) project is an X-ray/infrared study of the young stellar populations in 22 star forming regions with distances <=1 kpc designed to extend our earlier MYStIX survey of more distant clusters. Our central goal is to give empirical constraints on cluster formation mechanisms. Using parametric mixture models applied homogeneously to the catalog of SFiNCs young stars, we identify 52 SFiNCs clusters and 19 unclustered stellar structures. The procedure gives cluster properties including location, population, morphology, association to molecular clouds, absorption, age (AgeJX), and infrared spectral energy distribution (SED) slope. Absorption, SED slope, and AgeJX are age indicators. SFiNCs clusters are examined individually, and collectively with MYStIX clusters, to give the following results. (1) SFiNCs is dominated by smaller, younger, and more heavily obscured clusters than MYStIX. (2) SFiNCs cloud-associated clusters have the high ellipticities aligned with their host molecular filaments indicating morphology inherited from their parental clouds. (3) The effect of cluster expansion is evident from the radius-age, radius-absorption, and radius-SED correlations. Core radii increase dramatically from ~0.08 to ~0.9 pc over the age range 1--3.5 Myr. Inferred gas removal timescales are longer than 1 Myr. (4) Rich, spatially distributed stellar populations are present in SFiNCs clouds representing early generations of star formation. An Appendix compares the performance of the mixture models and nonparametric Minimum Spanning Tree to identify clusters. This work is a foundation for future SFiNCs/MYStIX studies including disk longevity, age gradients, and dynamical modeling.
Planck allows unbiased mapping of Galactic sub-millimetre and millimetre emission from the most diffuse regions to the densest parts of molecular clouds. We present an early analysis of the Taurus molecular complex, on line-of-sight-averaged data and without component separation. The emission spectrum measured by Planck and IRAS can be fitted pixel by pixel using a single modified blackbody. Some systematic residuals are detected at 353 GHz and 143 GHz, with amplitudes around -7 % and +13 %, respectively, indicating that the measured spectra are likely more complex than a simple modified blackbody. Significant positive residuals are also detected in the molecular regions and in the 217 GHz and 100 GHz bands, mainly caused by to the contribution of the J=2-1 and J=1-0 12CO and 13CO emission lines. We derive maps of the dust temperature T, the dust spectral emissivity index beta, and the dust optical depth at 250 microns tau. The temperature map illustrates the cooling of the dust particles in thermal equilibrium with the incident radiation field, from 16-17 K in the diffuse regions to 13-14 K in the dense parts. The distribution of spectral indices is centred at 1.78, with a standard deviation of 0.08 and a systematic error of 0.07. We detect a significant T-beta anti-correlation. The dust optical depth map reveals the spatial distribution of the column density of the molecular complex from the densest molecular regions to the faint diffuse regions. We use near-infrared extinction and HI data at 21-cm to perform a quantitative analysis of the spatial variations of the measured dust optical depth at 250 microns per hydrogen atom tau/NH. We report an increase of tau/NH by a factor of about 2 between the atomic phase and the molecular phase, which has a strong impact on the equilibrium temperature of the dust particles.
We explore the relation between the stellar mass surface density and the mass surface density of molecular hydrogen gas in twelve nearby molecular clouds that are located at $<$1.5 kpc distance. The sample clouds span an order of magnitude range in mass, size, and star formation rates. We use thermal dust emission from $Herschel$ maps to probe the gas surface density and the young stellar objects from the most recent $Spitzer$ Extended Solar Neighborhood Archive (SESNA) catalog to probe the stellar surface density. Using a star-sampled nearest neighbor technique to probe the star-gas surface density correlations at the scale of a few parsecs, we find that the stellar mass surface density varies as a power-law of the gas mass surface density, with a power-law index of $sim$2 in all the clouds. The consistent power-law index implies that star formation efficiency is directly correlated with gas column density, and no gas column density threshold for star formation is observed. We compare the observed correlations with the predictions from an analytical model of thermal fragmentation, and with the synthetic observations of a recent hydrodynamic simulation of a turbulent star-forming molecular cloud. We find that the observed correlations are consistent for some clouds with the thermal fragmentation model and can be reproduced using the hydrodynamic simulations.
Dust is the usual minor component of the interstellar medium. Its dynamic role in the contraction of the diffuse gas into molecular clouds is commonly assumed to be negligible because of the small mass fraction, $f simeq 0.01$. However, as shown in this study, the collective motion of dust grains with respect to the gas may considerably contribute to the destabilisation of the medium on scales $lambda lesssim lambda_J$, where $lambda_J$ is the Jeans length-scale. The linear perturbations of the uniform self-gravitating gas at rest are marginally stable at $lambda simeq lambda_J$, but as soon as the drift of grains is taken into account, they begin growing at a rate approximately equal to $(f tau)^{1/3} t^{-1}_{ff}$, where $tau$ is the stopping time of grains expressed in units of the free fall time of the cloud, $t_{ff}$. The physical mechanism responsible for such a weak dependence of the growth rate on $f$ is the resonance of heavy sound waves stopped by the self-gravity of gas with weak gravitational attraction caused by perturbations of the dust fraction. Once there is stationary subsonic bulk drift of the dust, the growing gas-dust perturbations at $lambda < lambda_J$ become waves propagating with the drift velocity projected onto the wavevector. Their growth has a resonant nature as well and the growth rate is substantially larger than that of the recently discovered resonant instability of gas-dust mixture in the absence of self-gravity. The new instabilities can facilitate gravitational contraction of cold interstellar gas into clouds and additionally produce dusty domains of sub-Jeans size at different stages of molecular cloud formation and evolution.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
