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The evolutionary tracks of young massive star clusters

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 Publication date 2014
  fields Physics
and research's language is English




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Stars mostly form in groups consisting of a few dozen to several ten thousand members. For 30 years, theoretical models provide a basic concept of how such star clusters form and develop: they originate from the gas and dust of collapsing molecular clouds. The conversion from gas to stars being incomplete, the left over gas is expelled, leading to cluster expansion and stars becoming unbound. Observationally, a direct confirmation of this process has proved elusive, which is attributed to the diversity of the properties of forming clusters. Here we take into account that the true cluster masses and sizes are masked, initially by the surface density of the background and later by the still present unbound stars. Based on the recent observational finding that in a given star-forming region the star formation efficiency depends on the local density of the gas, we use an analytical approach combined with mbox{N-body simulations, to reveal} evolutionary tracks for young massive clusters covering the first 10 Myr. Just like the Hertzsprung-Russell diagram is a measure for the evolution of stars, these tracks provide equivalent information for clusters. Like stars, massive clusters form and develop faster than their lower-mass counterparts, explaining why so few massive cluster progenitors are found.



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Young massive clusters (YMCs) are the most intense regions of star formation in galaxies. Formulating a model for YMC formation whilst at the same time meeting the constraints from observations is highly challenging however. We show that forming YMCs requires clouds with densities $gtrsim$ 100 cm$^{-3}$ to collide with high velocities ($gtrsim$ 20 km s$^{-1}$). We present the first simulations which, starting from moderate cloud densities of $sim100$ cm$^{-3}$, are able to convert a large amount of mass into stars over a time period of around 1 Myr, to produce dense massive clusters similar to those observed. Such conditions are commonplace in more extreme environments, where YMCs are common, but atypical for our Galaxy, where YMCs are rare.
(Abridged) Understanding the details of the formation process of massive (i.e. M<8-10M$_odot$) stars is a long-standing problem in astrophysics. [...] We present a method to derive accurate timescales of the different evolutionary phases of the high-mass star formation process. We model a representative number of massive clumps of the ATLASGAL-TOP100 sample which cover all the evolutionary stages. The models describe an isothermal collapse and the subsequent warm-up phase, for which we follow their chemical evolution. The timescale of each phase is derived by comparing the results of the models with the properties of the sources of the ATLASGAL-TOP100 sample, taking into account the mass and luminosity of the clumps, and the column densities of methyl acetylene (CH$_3$CCH), acetonitrile (CH$_3$CN), formaldehyde (H$_2$CO) and methanol (CH$_3$OH). We find that the chosen molecular tracers are affected by the thermal evolution of the clumps, showing steep ice evaporation gradients from 10$^3$ to 10$^5$ AU during the warm-up phase. We succeed in reproducing the observed column densities of CH$_3$CCH and CH$_3$CN, while H$_2$CO and CH$_3$OH show a poorer agreement with the observed values. The total (massive) star formation time is found to be $sim5.2times10^5$ yr, which is defined by the timescales of the individual evolutionary phases of the ATLASGAL-TOP100 sample: $sim5times10^4$ yr for 70-$mu$m weak, $sim1.2times10^5$ yr for mid-IR weak, $sim2.4times10^5$ yr for mid-IR bright and $sim1.1times10^5$ yr for HII-regions phases. Our models, with an appropriate selection of molecular tracers that can act as chemical clocks, allow to get robust estimates of the duration of the individual phases of the high-mass star formation process, with the advantage of being capable to include additional tracers aimed at increasing the accuracy of the estimated timescales.
209 - Yichen Zhang 2013
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