Estimation of high-resolution dust column density maps

Comparison of modified black-body fits and radiative transfer modelling

Department of Physics, PO Box 64, 00014, University of Helsinki, Finland
e-mail: mika.juvela@helsinki.fi

Received: 7 February 2013
Accepted: 25 March 2013

Abstract

Context. Sub-millimetre dust emission is routinely used to derive the column density N of dense interstellar clouds. The observations consist of data at several wavelengths but also, with increasing wavelength, of poorer resolution. Procedures have been proposed for deriving higher resolution maps of N. In this paper the main ones are called Methods A and B. Method A uses low-resolution temperature estimates combined with higher resolution intensity data. Method B is a combination of column density estimates obtained using different wavelength ranges.

Aims. Our aim is to determine the accuracy of the proposed methods relative to the true column densities and to the estimates that could be obtained with radiative transfer modelling.

Methods. We used magnetohydrodynamical simulations and radiative transfer calculations to simulate sub-millimetre surface brightness observations at the wavelengths of the Herschel Space Observatory. The synthetic observations were analysed with the proposed methods and the results compared to the true column densities and to the results obtained with simple 3D radiative transfer modelling of the observations.

Results. Both methods give relatively reliable column density estimates at the resolution of 250 μm data while also making use of the longer wavelengths. In case of high signal-to-noise data, the results of Method B are better correlated with the true column density, while Method A is less sensitive to noise. When the cloud has internal heating sources, Method B gives results that are consistent with those that would be obtained if high-resolution data were available at all wavelengths. Because of line-of-sight temperature variations, these underestimate the true column density, and because of a favourable cancellation of errors, Method A can sometimes give more correct values. Radiative transfer modelling, even with very simple 3D cloud models, usually provides more accurate results. However, the complexity of the models that are required for improved results increases rapidly with the complexity and opacity of the clouds.

Conclusions. Method B provides reliable estimates of the column density, although in the case of internal heating, Method A can be less biased because of fortuitous cancellation of errors. For clouds with a simple density structure, improved column density estimates can be obtained even with simple radiative transfer modelling.