Simulated observations of star formation regions: infrared evolution of globally collapsing clouds

TL;DR

This study uses radiative transfer simulations to compare star-forming cloud models with observations, revealing biases in dust mass estimates and confirming infrared-based star formation rate calibrations.

Contribution

First application of SKIRT radiative transfer to star-forming cloud simulations, analyzing synthetic observations with traditional workflows.

Findings

Infrared heating is insufficient without interstellar radiation field.

Spectral energy distribution stabilizes after ~3 Myr, morphology evolves over ~8 Myr.

Modified black body fits underestimate dust mass by a factor of 2.

Abstract

The direct comparison between hydrodynamical simulations and observations is needed to improve the physics included in the former and test biases in the latter. Post-processing radiative transfer and synthetic observations are now the standard way to do this. We report on the first application of the \texttt{SKIRT} radiative transfer code to simulations of a star-forming cloud. The synthetic observations are then analyzed following traditional observational workflows. We find that in the early stages of the simulation, stellar radiation is inefficient in heating dust to the temperatures observed in Galactic clouds, thus the addition of an interstellar radiation field is necessary. The spectral energy distribution of the cloud settles rather quickly after $\sim3$ Myr of evolution from the onset of star formation, but its morphology continues to evolve for $\sim8$ Myr due to the expansion of \textsc{Hii} regions and the respective creation of cavities, filaments, and ridges. Modeling synthetic \textit{Herschel} fluxes with 1- or 2-component modified black bodies underestimates total dust masses by a factor of $\sim2$. Spatially-resolved fitting recovers up to about $70\%$ of the intrinsic value. This ``missing mass'' is located in a very cold dust component with temperatures below $10$ K, which does not contribute appreciably to the far-infrared flux. This effect could bias real observations if such dust exists in large amounts. Finally, we tested observational calibrations of the SFR based on infrared fluxes and concluded that they are in agreement when compared to the intrinsic SFR of the simulation averaged over $\sim100$ Myr.