Oral Presentation
What is a GMC? Are Observers and Simulators Discussing the Same Star-forming Clouds?
Observations and simulations have now reached the point where the giant molecular cloud (GMCs) populations can be studied over a whole galaxy. This is immensely helpful for understanding star formation, since the cloud properties set the conditions for new star birth. Yet, are these two groups really comparing the same objects? While simulators work in position-position-position (PPP) space, observers see projected properties along the line of sight, identifying clouds in position-position-velocity (PPV) space. If these methods do not identify the same objects, then the interpretation and comparisons between the data sets may be highly misleading.
In this research we generated PPV and PPP data for a high-resolution simulated galaxy and compared the identified clouds in both data sets. The results show that PPV- and PPP- clouds are similar in both number and physical properties. Moreover, 70% of the PPV- clouds have a single counterpart in PPP space. The scatter of mass, radius and velocity dispersion between the matched PPV- and PPP- clouds are typically within a factor of two. Hence, in an ideal minimal-noise situation, PPV and PPP agree on the molecular cloud population.
In the simulations, three types of GMCs are found, identified by their mass and surface density. The balance of such populations is determined by the galactic environment and governs the star formation rate, linking the two together. Indeed, it may explain the low star formation rate found in galactic bars. While in principal both PPV and PPP can find all three populations, PPV would struggle to identify the low-mass, transient cloud populations if measured through current fully operational interferometers. We discuss the possibility of observing this cloud spectrum with ALMA.
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