Modelling Herschel observations of infrared-dark clouds in the Hi-GAL survey

TL;DR

This paper uses 3D radiative transfer modeling to analyze Herschel observations of infrared-dark clouds, helping to accurately determine their physical properties and understand early high-mass star formation.

Contribution

It demonstrates the application of the PHAETHON radiative transfer code to model IRDCs and compares simulated observations with real data, improving parameter estimation methods.

Findings

Radiative transfer modeling is essential for accurate IRDC parameter determination.

Simulated Herschel observations closely match real data after processing.

The method is applied to G29.55+00.18 and will be extended to more IRDCs.

Abstract

We demonstrate the use of the 3D Monte Carlo radiative transfer code PHAETHON to model infrared-dark clouds (IRDCs) that are externally illuminated by the interstellar radiation field (ISRF). These clouds are believed to be the earliest observed phase of high-mass star formation, and may be the high-mass equivalent of lower-mass prestellar cores. We model three different cases as examples of the use of the code, in which we vary the mass, density, radius, morphology and internal velocity field of the IRDC. We show the predicted output of the models at different wavelengths chosen to match the observing wavebands of Herschel and Spitzer. For the wavebands of the long- wavelength SPIRE photometer on Herschel, we also pass the model output through the SPIRE simulator to generate output images that are as close as possible to the ones that would be seen using SPIRE. We then analyse the images as if they were real observations, and compare the results of this analysis with the results of the radiative transfer models. We find that detailed radiative transfer modelling is necessary to accurately determine the physical parameters of IRDCs (e.g. dust temperature, density profile). This method is applied to study G29.55+00.18, an IRDC observed by the Herschel Infrared Galactic Plane survey (Hi-GAL), and in the future it will be used to model a larger sample of IRDCs from the same survey.