High-resolution mapping of interstellar clouds with near-infrared scattered light

¹ Helsinki University Observatory, 00014, University of Helsinki, Finland
² Department of Physics, University of California, San Diego, CASS/UCSD 0424, 9500 Gilman Drive, La Jolla, CA 92093-0424, USA e-mail: ppadoan@ucsd.edu

Received: 8 March 2006
Accepted: 27 June 2006

Abstract

Context.With current wide-field near-infrared (NIR) instruments the scattered light in the near-infrared can be mapped over large areas. Below  mag the surface brightness is directly proportional to the column density, and at slightly higher column densities the saturation of the intensity values can be corrected using the ratios of the intensity in different NIR bands. Therefore, NIR scattered light provides a promising new method for the mapping of quiescent interstellar clouds.

Aims.We develop a method to convert the observed near-infrared surface brightness into estimates of the column density. We study and quantify the effect that different error sources could have on the accuracy of such estimates. We also propose to reduce systematic errors by combining surface brightness data with extinction measurements derived from the near-infrared colour excess of background stars.

Methods.Our study is based on a set of three-dimensional magnetohydrodynamic turbulence simulations. Maps of near-infrared scattered light are obtained with radiative transfer calculations, and the maps are converted back into column density estimates using the proposed method. The results are compared with the true column densities. Extinction measurements are simulated using the same turbulence simulations, and are used as a complementary column density tracer.

Results.We find that NIR intensities can be converted into a reliable estimate of the column density in regions with A_V up to almost 20 mag. We show that the errors can be further reduced with detailed radiative transfer modelling and especially by using the lower resolution information available through the colour excess data.

Conclusions.We urge the observers to try this new method out in practice.