43 research outputs found
Machine learning based data mining for Milky Way filamentary structures reconstruction
We present an innovative method called FilExSeC (Filaments Extraction,
Selection and Classification), a data mining tool developed to investigate the
possibility to refine and optimize the shape reconstruction of filamentary
structures detected with a consolidated method based on the flux derivative
analysis, through the column-density maps computed from Herschel infrared
Galactic Plane Survey (Hi-GAL) observations of the Galactic plane. The present
methodology is based on a feature extraction module followed by a machine
learning model (Random Forest) dedicated to select features and to classify the
pixels of the input images. From tests on both simulations and real
observations the method appears reliable and robust with respect to the
variability of shape and distribution of filaments. In the cases of highly
defined filament structures, the presented method is able to bridge the gaps
among the detected fragments, thus improving their shape reconstruction. From a
preliminary "a posteriori" analysis of derived filament physical parameters,
the method appears potentially able to add a sufficient contribution to
complete and refine the filament reconstruction.Comment: Proceeding of WIRN 2015 Conference, May 20-22, Vietri sul Mare,
Salerno, Italy. Published in Smart Innovation, Systems and Technology,
Springer, ISSN 2190-3018, 9 pages, 4 figure
The Herschel InfraRed Galactic Plane Survey: A Panoramic View of Star Formation in the Milky Way
Large-scale properties of the clump mass function
The mass function of molecular cloud clumps and cores is widely used to compare the results of numerical simulations with the observations adopting different prescriptions for star formation. However, our ability to test different theories relies critically on our ability to measure it accurately and interpret it confidently. From an observational perspective, mass functions are subject to uncertainties due to differences in the sample selection, data reduction, and analysis techniques. To reduce these and other biasing effects, in this work we discuss methods to construct clusters or groups of sources extracted from the Hi-GAL survey, which allows us to look at large clump populations in various clouds with different physical conditions. We then construct the clump mass function of each separate group, and we fit the clump mass functions with the two most widely used functional forms, power law, and lognormal. The best-fitting parameters show no correlation with distance and positional parameters of the groups, and the mass spectra appear to have similar shapes and overall widths, though with different intrinsic mass scales. The statistical invariance of the shape of the CMF suggests that no significant differences exist in the early phases between regions dominated by low- and high-mass star formation. Finally, we found that high-mass star formation is more likely to happen in groups where the range of clump mass is shifted towards the high-mass end
Chemical Diversity in Protoplanetary Disks and Its Impact on the Formation History of Giant Planets
Giant planets can interact with multiple and chemically diverse environments
in protoplanetary discs while they form and migrate to their final orbits. The
way this interaction affects the accretion of gas and solids shapes the
chemical composition of the planets and of their atmospheres. Here we
investigate the effects of different chemical structures of the host
protoplanetary disc on the planetary composition. We consider both scenarios of
molecular (inheritance from the pre-stellar cloud) and atomic (complete
chemical reset) initial abundances in the disc. We focus on four elemental
tracers of different volatility: C, O, N, and S. We explore the entire
extension of possible formation regions suggested by observations by coupling
the disc chemical scenarios with N-body simulations of forming and migrating
giant planets. The planet formation process produces giant planets with
chemical compositions significantly deviating from that of the host disc. We
find that the C/N, N/O, and S/N ratios follow monotonic trends with the extent
of migration. The C/O ratio shows a more complex behaviour, dependent on the
planet accretion history and on the chemical structure of the formation
environment. The comparison between S/N* and C/N* (where * indicates
normalisation to the stellar value), constrains the relative contribution of
gas and solids to the total metallicity. Giant planets whose metallicity is
dominated by the contribution of the gas are characterised by N/O* > C/O* >
C/N* and allow for constraining the disc chemical scenario. When the planetary
metallicity is instead dominated by the contribution of the solids we find that
C/N* > C/O* > N/O*.Comment: 27 pages, 10 figures, 1 table. Published in The Astrophysical Journa
Hi-fidelity multi-scale local processing for visually optimized far-infrared Herschel images
In the context of the "Hi-Gal" multi-band full-plane mapping program for the Galactic Plane, as imaged by the Herschel far-infrared satellite, we have developed a semi-automatic tool which produces high definition, high quality color maps optimized for visual perception of extended features, like bubbles and filaments, against the high background variations. We project the map tiles of three selected bands onto a 3-channel panorama, which spans the central 130 degrees of galactic longitude times 2.8 degrees of galactic latitude, at the pixel scale of 3.2", in cartesian galactic coordinates. Then we process this image piecewise, applying a custom multi-scale local stretching algorithm, enforced by a local multi-scale color balance. Finally, we apply an edge-preserving contrast enhancement to perform an artifact-free details sharpening. Thanks to this tool, we have thus produced a stunning giga-pixel color image of the far-infrared Galactic Plane that we made publicly available with the recent release of the Hi-Gal mosaics and compact source catalog. <P /
Identifying Young Stellar Objects in the Outer Galaxy: l = 224 deg Region in Canis Major
We study a very young star-forming region in the outer Galaxy that is the
most concentrated source of outflows in the Spitzer Space Telescope GLIMPSE360
survey. This region, dubbed CMa-l224, is located in the Canis Major OB1
association. CMa-l224 is relatively faint in the mid-infrared, but it shines
brightly at the far-infrared wavelengths as revealed by the Herschel Space
Observatory data from the Hi-GAL survey. Using the 3.6 and 4.5 m data from
the Spitzer/GLIMPSE360 survey, combined with the JHK 2MASS and the 70-500
m Herschel/Hi-GAL data, we develop a young stellar object (YSO) selection
criteria based on color-color cuts and fitting of the YSO candidates' spectral
energy distributions with YSO 2D radiative transfer models. We identify 293 YSO
candidates and estimate physical parameters for 210 sources well-fit with YSO
models. We select an additional 47 sources with GLIMPSE360-only photometry as
`possible YSO candidates'. The vast majority of these sources are associated
with high H column density regions and are good targets for follow-up
studies. The distribution of YSO candidates at different evolutionary stages
with respect to Herschel filaments supports the idea that stars are formed in
the filaments and become more dispersed with time. Both the supernova-induced
and spontaneous star formation scenarios are plausible in the environmental
context of CMa-l224. However, our results indicate that a spontaneous
gravitational collapse of filaments is a more likely scenario. The methods
developed for CMa-l224 can be used for larger regions in the Galactic plane
where the same set of photometry is available.Comment: Accepted for publication in the Astrophysical Journal Supplement
Series; 54 pages including appendice
Large-scale filaments associated with Milky Way spiral arms
The ubiquity of filamentary structure at various scales through out the
Galaxy has triggered a renewed interest in their formation, evolution, and role
in star formation. The largest filaments can reach up to Galactic scale as part
of the spiral arm structure. However, such large scale filaments are hard to
identify systematically due to limitations in identifying methodology (i.e., as
extinction features). We present a new approach to directly search for the
largest, coldest, and densest filaments in the Galaxy, making use of sensitive
Herschel Hi-GAL data complemented by spectral line cubes. We present a sample
of the 9 most prominent Herschel filaments, including 6 identified from a pilot
search field plus 3 from outside the field. These filaments measure 37-99 pc
long and 0.6-3.0 pc wide with masses (0.5-8.3), and
beam-averaged (, or 0.4-0.7 pc) peak H column densities of
(1.7-9.3). The bulk of the filaments are
relatively cold (17-21 K), while some local clumps have a dust temperature up
to 25-47 K. All the filaments are located within <~60 pc from the Galactic
mid-plane. Comparing the filaments to a recent spiral arm model incorporating
the latest parallax measurements, we find that 7/9 of them reside within arms,
but most are close to arm edges. These filaments are comparable in length to
the Galactic scale height and therefore are not simply part of a grander
turbulent cascade.Comment: Published 2015MNRAS.450.4043W; this version contains minor proof
corrections. FT-based background removal code at
https://github.com/esoPanda/FTbg SED fitting code at
http://hi-gal-sed-fitter.readthedocs.org 3D interactive visualization at
http://www.eso.org/~kwan
VIALACTEA knowledge base homogenizing access to Milky Way data
The VIALACTEA project has a work package dedicated to "Tools and Infrastructure" and, inside it, a task for the "Database and Virtual Observatory Infrastructure". This task aims at providing an infrastructure to store all the resources needed by the, more purposely, scientific work packages of the project itself. This infrastructure includes a combination of: storage facilities, relational databases and web services on top of them, and has taken, as a whole, the name of VIALACTEA Knowledge Base (VLKB). This contribution illustrates the current status of this VLKB. It details the set of data resources put together; describes the database that allows data discovery through VO inspired metadata maintenance; illustrates the discovery, cutout and access services built on top of the former two for the users to exploit the data content