Abstract
We define an appropriate problem for benchmarking dust emissivity calculations in the context of radiative transfer (RT) simulations, specifically including the emission from stochastically heated dust grains. Our aim is to provide a self-contained guide for implementors of such functionality, and to offer insights in the effects of the various approximations and heuristics implemented by the participating codes to accelerate the calculations. The benchmark problem definition includes the optical and calorimetric material properties, and the grain size distributions, for a typical astronomical dust mixture with silicate, graphite and PAH components; a series of analytically defined radiation fields to which the dust population is to be exposed; and instructions for the desired output. We process this problem using six RT codes participating in this benchmark effort, and compare the results to a reference solution computed with the publicly available dust emission code DustEM. The participating codes implement different heuristics to keep the calculation time at an acceptable level. We study the effects of these mechanisms on the calculated solutions, and report on the level of (dis)agreement between the participating codes. For all but the most extreme input fields, we find agreement within 10% across the important wavelength range from 3 to 1000 micron. We conclude that the relevant modules in RT codes can and do produce fairly consistent results for the emissivity spectra of stochastically heated dust grains.
Highlights
Dust substantially affects the radiation emerging from many astrophysical systems
We study the effects of these mechanisms on the calculated solutions and quantify the level ofagreement between the participating codes, with the objective of helping to inform the interpretation of radiative transfer (RT) simulation results that include stochastically heated dust grains (SHGs) dust emission calculations of the type presented here
The heuristics employed by DIRTY in calculating the dust emission from each grain size of each component exposed to the local radiation field at a point in the model space are as follows: failure of the stochastic heating algorithm and proceed to the grid in the model space
Summary
Dust substantially affects the radiation emerging from many astrophysical systems. To study the three-dimensional structure of these systems, it is often useful to numerically simulate the transport of radiation through a model that includes a dusty medium with appropriate characteristics. When calculating the emission spectrum for the dust grain population in a particular cell, the first task is to determine the temperature probability distribution of the grains, given the grain sizes and chemical compositions and given the radiation field in the cell. We compare the reference solutions with the dust emission spectra calculated by six distinct RT codes These codes determine the grain temperature distribution by solving a set of linear equations (Guhathakurta & Draine 1989). While this method is inherently faster (Guhathakurta & Draine 1989), it still becomes very expensive when the grains are in LTE with the radiation field.
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