Astronomy and Astrophysics, volume 480, 445-458 (2008/3-3)
A Corona Australis cloud filament seen in NIR scattered light. I. Comparison with extinction of background stars.
JUVELA M., PELKONEN V.-M., PADOAN P. and MATTILA K.
Abstract (from CDS):
Using state-of-art near-infrared (NIR) instrumentation the near-infrared light scattered from interstellar clouds can be mapped over large areas. Measurement of the surface brightness provides information on the line-of-sight dust column density. Scattered light therefore provides an important tool to study the mass distribution of quiescent, interstellar clouds at high, even sub-arcsecond resolution. We test the assumption that light scattering is the dominant contributor to the surface brightness in all NIR bands. Furthermore, we want to show that scattered light can be used for an accurate estimation of dust column densities in clouds with extinction in the range AV=1-15m. We have obtained NIR images of a quiescent filament in the Corona Australis molecular cloud. The observations provide maps of diffuse surface brightness in the J, H, and Ks photometric bands. Assuming that the main contributor is indeed scattered light, we convert surface brightness data into a map of dust column density. The same observations provide colour excesses for a large number of background stars. These data are used to derive an extinction map of the cloud. The two, largely independent tracers of the cloud structure are compared. In regions where the extinction is below AV∼15m, both diffuse surface brightness and background stars lead to similar column density estimates. The existing differences can be explained as a result of normal observational errors and bias in the sampling of extinctions provided by the background stars. There is no indication that thermal dust-emission would have a significant contribution even in the Ks band. The results show that, below AV∼15mag, scattered light provides a reliable way to map cloud structure. Compared with the use of background stars, it can provide data of a significantly higher spatial resolution.