78 research outputs found

    Q+\mathcal{Q}^{+}: Characterising the structure of young star clusters

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    Many young star clusters appear to be fractal, i.e. they appear to be concentrated in a nested hierarchy of clusters within clusters. We present a new algorithm for statistically analysing the distribution of stars to quantify the level of sub-structure. We suggest that, even at the simplest level, the internal structure of a fractal cluster requires the specification of three parameters. (i) The 3D fractal dimension, D\mathcal{D}, measures the extent to which the clusters on one level of the nested hierarchy fill the volume of their parent cluster. (ii) The number of levels, L\mathcal{L}, reflects the finite ratio between the linear size of the large root-cluster at the top of the hierarchy, and the smallest leaf-clusters at the bottom of the hierarchy. (iii) The volume-density scaling exponent, C=dln[δn]/dln[L]\mathcal{C}=-\textrm{d}\ln[\delta n]/\textrm{d}\ln[L] measures the factor by which the excess density, δn\delta n, in a structure of scale LL, exceeds that of the background formed by larger structures; it is similar, but not exactly equivalent, to the exponent in Larson's scaling relation between density and size for molecular clouds. We describe an algorithm which can be used to constrain the values of (D,L,C)({\cal D},{\cal L},{\cal C}) and apply this method to artificial and observed clusters. We show that this algorithm is able to reliably describe the three dimensional structure of an artificial star cluster from the two dimensional projection, and quantify the varied structures observed in real and simulated clusters.Comment: Accepted by MNRA

    Star Formation triggered by cloud-cloud collisions

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    We present the results of SPH simulations in which two clouds, each having mass Mo ⁣= ⁣500MM_{_{\rm{o}}}\!=\!500\,{\rm M}_{_\odot} and radius Ro ⁣= ⁣2pcR_{_{\rm{o}}}\!=\!2\,{\rm pc}, collide head-on at relative velocities of Δvo=2.4,  2.8,  3.2,  3.6  and  4.0kms1\Delta v_{_{\rm{o}}} =2.4,\;2.8,\;3.2,\;3.6\;{\rm and}\;4.0\,{\rm km}\,{\rm s}^{-1}. There is a clear trend with increasing Δvo\Delta v_{_{\rm{o}}}. At low Δvo\Delta v_{_{\rm{o}}}, star formation starts later, and the shock-compressed layer breaks up into an array of predominantly radial filaments; stars condense out of these filaments and fall, together with residual gas, towards the centre of the layer, to form a single large-NN cluster, which then evolves by competitive accretion, producing one or two very massive protostars and a diaspora of ejected (mainly low-mass) protostars; the pattern of filaments is reminiscent of the hub and spokes systems identified recently by observers. At high Δvo\Delta v_{_{\rm{o}}}, star formation occurs sooner and the shock-compressed layer breaks up into a network of filaments; the pattern of filaments here is more like a spider's web, with several small-NN clusters forming independently of one another, in cores at the intersections of filaments, and since each core only spawns a small number of protostars, there are fewer ejections of protostars. As the relative velocity is increased, the {\it mean} protostellar mass increases, but the {\it maximum} protostellar mass and the width of the mass function both decrease. We use a Minimal Spanning Tree to analyse the spatial distributions of protostars formed at different relative velocities.Comment: 10 pages, 11 figure

    J plots: a new method for characterizing structures in the interstellar medium

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    Large-scale surveys have brought about a revolution in astronomy. To analyse the resulting wealth of data, we need automated tools to identify, classify, and quantify the important underlying structures. We present here a method for classifying and quantifying a pixelated structure, based on its principal moments of inertia. The method enables us to automatically detect, and objectively compare, centrally condensed cores, elongated filaments, and hollow rings. We illustrate the method by applying it to (i) observations of surface density from Hi-GAL, and (ii) simulations of filament growth in a turbulent medium. We limit the discussion here to 2D data; in a future paper, we will extend the method to 3D data

    Synthetic C18O observations of fibrous filaments: the problems of mapping from PPV to PPP

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    Molecular-line observations of filaments in star-forming regions have revealed the existence of elongated coherent features within the filaments; these features are termed fibres. Here we caution that, since fibres are traced in PPV space, there is no guarantee that they represent coherent features in PPP space. We illustrate this contention using simulations of the growth of a filament from a turbulent medium. Synthetic C18^{18}O observations of the simulated filaments reveal the existence of fibres very similar to the observed ones, i.e. elongated coherent features in the resulting PPV data-cubes. Analysis of the PPP data-cubes (i.e. 3D density fields) also reveals elongated coherent features, which we term sub-filaments. Unfortunately there is very poor correspondence between the fibres and the sub-filaments in the simulations. Both fibres and sub-filaments derive from inhomogeneities in the turbulent accretion flow onto the main filament. As a consequence, fibres are often affected by line-of-sight confusion. Similarly, sub-filaments are often affected by large velocity gradients, and even velocity discontinuities. These results suggest that extreme care should be taken when using velocity coherent features to constrain the underlying substructure within a filament.Comment: 15 pages + appendices, 26 figures. Accepted to MNRA

    The Hi-GAL compact source catalogue – I. The physical properties of the clumps in the inner Galaxy (−71. ◦ 0 < ℓ < 67.◦ 0)

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    Hi-GAL (Herschel InfraRed Galactic Plane Survey) is a large-scale survey of the Galactic plane, performed with Herschel in five infrared continuum bands between 70 and 500 µm. We present a band-merged catalogue of spatially matched sources and their properties derived from fits to the spectral energy distributions (SEDs) and heliocentric distances, based on the photometric catalogues presented in Molinari et al., covering the portion of Galactic plane −71.◦ 0 < ℓ < 67.◦ 0. The band-merged catalogue contains 100 922 sources with a regular SED, 24 584 of which show a 70-µm counterpart and are thus considered protostellar, while the remainder are considered starless. Thanks to this huge number of sources, we are able to carry out a preliminary analysis of early stages of star formation, identifying the conditions that characterize different evolutionary phases on a statistically significant basis. We calculate surface densities to investigate the gravitational stability of clumps and their potential to form massive stars. We also explore evolutionary status metrics such as the dust temperature, luminosity and bolometric temperature, finding that these are higher in protostellar sources compared to pre-stellar ones. The surface density of sources follows an increasing trend as they evolve from pre-stellar to protostellar, but then it is found to decrease again in the majority of the most evolved clumps. Finally, we study the physical parameters of sources with respect to Galactic longitude and the association with spiral arms, finding only minor or no differences between the average evolutionary status of sources in the fourth and first Galactic quadrants, or between 'on-arm' and 'interarm' positions

    Star formation triggered by cloud–cloud collisions

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