Near-infrared scattering as a dust diagnostic

Abstract

Context. Regarding the evolution of dust grains from diffuse regions of space to dense molecular cloud cores, many questions remain open. Scattering at near-infrared wavelengths, or “cloudshine”, can provide information on cloud structure, dust properties, and the radiation field that is complementary to mid-infrared “coreshine” and observations of dust emission at longer wavelengths. Aims. We examine the possibility of using near-infrared scattering to constrain the local radiation field and the dust properties, the scattering and absorption efficiency, the size distribution of the grains, and the maximum grain size. Methods. We use radiative transfer modelling to examine the constraints provided by the J, H, and K bands in combination with mid-infrared surface brightness at 3.6 μm. We use spherical one-dimensional and elliptical three-dimensional cloud models to study the observable effects of different grain size distributions with varying absorption and scattering properties. As an example, we analyse observations of a molecular cloud in Taurus, TMC-1N. Results. The observed surface brightness ratios of the bands change when the dust properties are changed. However, even a change of ±10% in the surface brightness of one band changes the estimated power-law exponent of the size distribution γ by up to ~30% and the estimated strength of the radiation field KISRF by up to ~60%. The maximum grain size Amax and γ are always strongly anti-correlated. For example, overestimating the surface brightness by 10% changes the estimated radiation field strength by ~20% and the exponent of the size distribution by ~15%. The analysis of our synthetic observations indicates that the relative uncertainty of the parameter distributions are on average Amax, γ ~ 25%, and the deviation between the estimated and correct values ΔQ < 15%. For the TMC-1N observations, a maximum grain size Amax > 1.5μm and a size distribution with γ > 4.0 have high probability. The mass weighted average grain size is ⟨am⟩ = 0.113μm. Conclusions. We show that scattered infrared light can be used to derive meaningful limits for the dust parameters. However, errors in the surface brightness data can result in considerable uncertainties on the derived parameters.