Abstract

Context. The size and chemical composition of interstellar dust grains are critical in setting the dynamical, physical, and chemical evolution of all the media in which they are present. Thanks to facilities such as the Atacama Large Millimeter/submillimeter Array (ALMA) and, in the future, the Square Kilometer Array (SKA), thermal emission in the (sub)millimetre to centimetre domain has become a very convenient way to trace grain properties. Aims. Our aim is to understand the influence of the composition and size distribution of dust grains on the shape of their spectral energy distribution (peak position, spectral index) in dense interstellar regions such as molecular clouds, prestellar cores, young stellar objects, and protoplanetary discs. Methods. Starting from the optical constants defined in The Heterogeneous dust Evolution Model for Interstellar Solids (THEMIS) for amorphous hydrogenated carbon grains and amorphous silicates in addition to water ice, we defined six material mixtures that we believe are representative of the expected dust composition in dense interstellar regions. The optical properties of 0.01 μm to 10 cm grains were then calculated with effective medium and Mie theories. The corresponding spectral energy distributions were subsequently calculated for isolated clouds either externally heated by the standard interstellar radiation field alone or in addition to an internal source. Results. The three main outcomes of this study are as follows. Firstly, the dust mass absorption coefficient strongly depends on both grain composition and size distribution potentially leading to errors in dust mass estimates by factors up to ~3 and 20, respectively. Secondly, it appears almost impossible to retrieve the grain composition from the (sub)millimetre to centimetre thermal emission shape alone as its spectral index for λ ≳ 3 mm does not depend on dust composition. Thirdly, using the “true” dust opacity spectral index to estimate grain sizes may lead to erroneous findings as the observed spectral index can be highly modified by the dust temperature distribution along the line of sight, which depends on the specific heating source and on the geometry of the studied interstellar region. Conclusions. Based on the interpretation of only the spectral shape of (sub)millimetre to centimetre observational data, the determination of the dust masses, compositions, and sizes are highly uncertain.

Highlights

  • Interstellar grains constantly evolve throughout the interstellar medium (ISM) in response to their local environment

  • Spectral indices in Atacama Large Millimeter/submillimeter Array (ALMA) and VLA bands that we have a clear picture of the shape of the dust spectral energy distribution (SED) and of its variations in optically thick regions, we present the spectral indices calculated between ALMA and VLA bands in Fig. 10 for the same dust and cloud characteristics as in the previous Sect. 4.2

  • The aim of this paper is to understand the influence of the grain composition and size distribution on the shape of their SED in dense interstellar regions such as molecular clouds, prestellar cores, young stellar objects (YSOs), and protoplanetary discs

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Summary

Introduction

Interstellar grains constantly evolve throughout the interstellar medium (ISM) in response to their local environment. Mishchenko et al (2016a,b) performed exhaustive studies of the applicability of the Maxwell Garnett mixing rule to heterogeneous particles These latter authors showed that this rule can provide accurate estimates of the scattering matrix and absorption cross-section of heterogeneous grains at short wavelengths (typically up to the visible for a 0.1 μm grain and to the mid-infrared (MIR) for a 10 μm grain) if two criteria are met: both the size parameter of the inclusions and the refractive index contrast between the host material and the inclusions 1 See http://www.ias.u-psud.fr/themis/ 2 For the full details of the model see: Jones (2012a,b,c); Jones et al (2013, 2016); Köhler et al (2014, 2015); Ysard et al (2016, 2018). These theoretical and experimental results lead us to choose log-normal distributions rather than the more common power-laws which we do use for comparison purposes several times in this study

Dust emission
10-8 Mix 1:ice
G G GG G G G
Conclusion
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