Annu. Rev. Astron. Astrophys. 2013. 51:63-104 Copyright © 2013 by Annual Reviews. All rights reserved

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Abstract: Cosmic dust is present in many astrophysical objects, and recent observations across the electromagnetic spectrum show that the dust distribution is often strongly three-dimensional (3D). Dust grains are effective in absorbing and scattering ultraviolet (UV)/optical radiation, and they re-emit the absorbed energy at infrared wavelengths. Understanding the intrinsic properties of these objects, including the dust itself, therefore requires 3D dust radiative transfer (RT) calculations. Unfortunately, the 3D dust RT problem is nonlocal and nonlinear, which makes it one of the hardest challenges in computational astrophysics. Nevertheless, significant progress has been made in the past decade, with an increasing number of codes capable of dealing with the complete 3D dust RT problem. We discuss the complexity of this problem, the two most successful solution techniques [ray-tracing (RayT) and Monte Carlo (MC)], and the state of the art in modeling observational data using 3D dust RT codes. We end with an outlook on the bright future of this field.

Keywords: scattering, Monte Carlo, ray tracing, computational astrophysics, numerical algorithms

Table of Contents

• INTRODUCTION
• THE THREE-DIMENSIONAL DUST RADIATIVE TRANSFER PROBLEM
• The Radiative Transfer Equation
• Primary Emission and Absorption
• Including Scattering
• Radiative Transfer in Dust Mixtures
• Including Dust Emission
• Radiative Transfer of Polarized Radiation
• THE DISCRETE THREE-DIMENSIONAL DUST RADIATIVE TRANSFER PROBLEM
• Spatial Grids
• Local mean intensity storage grids
• Density and source grids
• Solution grids
• Direction Grid
• Wavelength and Dust Grain Grids
• THE RAY-TRACING SOLUTION METHOD
• Ray-Tracing Solution for a Single Ray
• Beyond the spatial grid resolution
• High optical depths
• Ray location and global solution of the RTE
• Thermal emission
• Including scattered radiation
• Ray-Tracing Error Analysis
• THE MONTE CARLO SOLUTION METHOD
• Simple MC RT
• Step 1: birth.
• Step 2: determination of the interaction point.
• Step 3: absorption and scattering.
• Weighted MC RT
• Biased emission.
• Absorption-scattering split.
• Forced scattering
• Peel-off technique.
• Continuous absorption.
• Instantaneous dust emission.
• High optical depths.
• Polychromatism.
• Uncertainties for Monte Carlo
• CHALLENGES IN MODELING OBSERVATIONS
• Model Choice
• Gridding
• Comparison of Models and Data
• Exploration of the Parameter Space
• Error Analysis
• Inverse RT
• CODES AND BENCHMARKS
• Available 3D codes
• Benchmark efforts
• THE FUTURE OF THE FIELD
• Present Status
• General Trends
• Future Benchmarks
• Data Modeling Future
• Future Connections to Nondust Radiative Transfer Codes
• Future Algorithms
• Input Physics Improvements
• Challenges
• REFERENCES