Infrared darkness as a tracer of cloud evolution

Star formation takes place in the densest regions of cold molecular clouds. As these clouds evolve, a fraction of the gas become gravitationally unstable, collapses and starts forming protostars. One major difficulty in understanding the details of such an evolutionary sequence is linked to the fact that one cannot follow the evolution of individual clouds, timescales for that are far too long to see any change during humans’ short lifetimes. In practice, every observation of a star-forming cloud represents a snapshot of a few million year long movie. In order to reconstruct that movie, one needs to observe large numbers of molecular clouds and find a way to determine in what order these observations need to be put together.
The goal of this PhD project is to use the the infrared darkness of star-forming clouds as a tracer of their evolution (Peretto et al. 2009). This will then be used to determine how quickly/slowly star-forming clouds evolve, a major question of current star formation research. By identifying protostars in them, the student will also estimate the star formation efficiency of molecular clouds across the Milky Way.
The student will use Spitzer and Herschel data of the Milky Way to identify and characterise the infrared darkness of all star-forming clouds. He/she will also run simple numerical simulations in order to constrain the absolute timescale over which a cloud transition from infrared dark to infrared bright. Finally, a bayesian analysis will be used to constrain the star formation efficiency in the Galaxy.

This project will start on 01/10/2018