SIMBAD references

Context. Understanding the details of the formation process of massive (i.e. M≥8-10M_☉) stars is a long-standing problem in astrophysics. They form and evolve very quickly, and almost their entire formation process takes place deeply embedded in their parental clumps. Together with the fact that these objects are rare and at a relatively large distance, this makes observing them very challenging.
Aims. We present a method for deriving accurate timescales of the evolutionary phases of the high-mass star formation process.
Methods. We modelled a representative number of massive clumps of the ATLASGAL-TOP100 sample that cover all the evolutionary stages. The models describe an isothermal collapse and the subsequent warm-up phase, for which we followed the chemical evolution. The timescale of each phase was 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 (CH₃CCH), acetonitrile (CH₃CN), formaldehyde (H₂CO), and methanol (CH₃OH).
Results. We find that the molecular tracers we chose are affected by the thermal evolution of the clumps, showing steep ice evaporation gradients from 10³ to 10⁵AU during the warm-up phase. We succeed in reproducing the observed column densities of CH₃CCH and CH₃CN, but H₂CO and CH₃OH agree less with the observed values. The total (massive) star formation time is found to be ∼5.2x10⁵yr, which is defined by the timescales of the individual evolutionary phases of the ATLASGAL-TOP100 sample: ∼5x10⁴yr for 70-µm weak, ∼1.2x10⁵yr for mid-IR weak, ∼2.4x10⁵yr for mid-IR bright, and ∼1.1x10⁵yr for HII-region phases.
Conclusions. With an appropriate selection of molecular tracers that can act as chemical clocks, our model allows obtaining robust estimates of the duration of the individual phases of the high-mass star formation process. It also has the advantage of being capable of including additional tracers aimed at increasing the accuracy of the estimated timescales.