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Authors
M. Juvela
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Thermal dust emission carries information on physical conditions and dust properties in many astronomical sources. Because observations represent a sum of emission along the line of sight, their interpretation often requires radiative transfer modelling. We describe a new radiative transfer program SOC for computations of dust emission and examine its performance in simulations of interstellar clouds with external and internal heating. SOC implements the Monte Carlo radiative transfer method as a parallel program for shared memory computers. It can be used to study dust extinction, scattering, and emission. We tested SOC with realistic cloud models and examined the convergence and noise of the dust temperature estimates and of the resulting surface brightness maps. SOC has been demonstrated to produces accurate estimates for dust scattering and for thermal dust emission. It performs well with both with CPUs and with GPUs, the latter providing up to an order of magnitude speed-up. In the test cases, ALI improved the convergence rates but also was sensitive to Monte Carlo noise. Run-time refinement of the hierarchical-grid models did not help in reducing the run times required for a given accuracy of solution. The use of a reference field, without ALI, works more robustly. It also allows the run time to be optimised if the number of photon packages is increased only as the iterations progress. The use of GPUs in radiative transfer computations should be investigated further.
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Radiative transfer modelling is part of many astrophysical simulations and is used to make synthetic observations and to assist analysis of observations. We concentrate on the modelling of the radio lines emitted by the interstellar medium. In connection with high-resolution models, this can be significant computationally challenge. Our goal is a line radiative transfer (RT) program that makes good use of multi-core CPUs and GPUs. Parallelisation is essential to speed up computations and to enable the tackling of large modelling tasks with personal computers. The program LOC is based on ray-tracing and uses standard accelerated lambda iteration (ALI) methods for faster convergence. The program works on 1D and 3D grids. The 1D version makes use of symmetries to speed up the RT calculations. The 3D version works with octree grids and, to enable calculations with large models, is optimised for low memory usage. Tests show that LOC gives results that are in agreement with other RT codes to within ~2%. This is typical of code-to-code differences, which often are related to different interpretations of the model set-up. LOC run times compare favourably with those of Monte Carlo codes. In 1D tests, LOC runs were by up to a factor ~20 faster on a GPU than on a single CPU core. In spite of the complex path calculations, up to ~10 speed-up was observed also for 3D models using octree discretisation. GPUs enable calculations of models with hundreds of millions of cells, as encountered in the context of large-scale simulations of interstellar clouds. LOC shows good performance and accuracy and and is able to handle many RT modelling tasks on personal computers. Being written in Python, with the computing-intensive parts implemented as compiled OpenCL kernels, it can also a serve as a platform for further experimentation with alternative RT implementations.
HYPERION is a new three-dimensional dust continuum Monte-Carlo radiative transfer code that is designed to be as generic as possible, allowing radiative transfer to be computed through a variety of three-dimensional grids. The main part of the code is problem-independent, and only requires an arbitrary three-dimensional density structure, dust properties, the position and properties of the illuminating sources, and parameters controlling the running and output of the code. HYPERION is parallelized, and is shown to scale well to thousands of processes. Two common benchmark models for protoplanetary disks were computed, and the results are found to be in excellent agreement with those from other codes. Finally, to demonstrate the capabilities of the code, dust temperatures, SEDs, and synthetic multi-wavelength images were computed for a dynamical simulation of a low-mass star formation region. HYPERION is being actively developed to include new features, and is publicly available (http://www.hyperion-rt.org).
We present Powderday, a flexible, fast, open-source dust radiative transfer package designed to interface with galaxy formation simulations. Powderday builds on FSPS population synthesis models, Hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, which allows for significant run-time flexibility in the assumed stellar physics. We include a model for nebular line emission that can employ either precomputed Cloudy lookup tables (for efficiency), or direct photoionization calculations for all young stars (for flexibility). The dust content follows either observationally-motivated prescriptions, direct modeling from galaxy formation simulations, or a novel approach that includes the dust content via learning-based algorithms from the SIMBA cosmological galaxy formation simulation. AGN can additionally be included via a range of prescriptions. The output of these models are broadband SEDs, as well as filter-convolved images. Powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models, and seamlessly interfaces with GIZMO, AREPO, GASOLINE, CHANGA, and ENZO. We demonstrate the capabilities of the code via three applications: a model for the star formation rate (SFR) - infrared luminosity relation in galaxies (including the impact of AGN); the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs; and the impact of galaxy inclination angle on dust attenuation laws.
We present a novel Lyman alpha (Ly$alpha$) radiative transfer code, SEURAT, where line scatterings are solved adaptively with the resolution of the smoothed particle hydrodynamics (SPH). The radiative transfer method implemented in SEURAT is based on a Monte Carlo algorithm in which the scattering and absorption by dust are also incorporated. We perform standard test calculations to verify the validity of the code; (i) emergent spectra from a static uniform sphere, (ii) emergent spectra from an expanding uniform sphere, and (iii) escape fraction from a dusty slab. Thereby we demonstrate that our code solves the Ly$alpha$ radiative transfer with sufficient accuracy. We emphasise that SEURAT can treat the transfer of Ly$alpha$ photons even in highly complex systems that have significantly inhomogeneous density fields. The high adaptivity of SEURAT is desirable to solve the propagation of Ly$alpha$ photons in the interstellar medium of young star-forming galaxies like Ly$alpha$ emitters (LAEs). Thus, SEURAT provides a powerful tool to model the emergent spectra of Ly$alpha$ emission, which can be compared to the observations of LAEs.
A one-dimensional method for reconstructing the structure of prestellar and protostellar clouds is presented. The method is based on radiative transfer computations and a comparison of theoretical and observed intensity distributions at both millimeter and infrared wavelengths. The radiative transfer of dust emission is modeled for specified parameters of the density distribution, central star, and external background, and the theoretical distribution of the dust temperature inside the cloud is determined. The intensity distributions at millimeter and IR wavelengths are computed and quantitatively compared with observational data. The best-fit model parameters are determined using a genetic minimization algorithm, which makes it possible to reveal the ranges of parameter degeneracy as well. The method is illustrated by modeling the structure of the two infrared dark clouds IRDC-320.27+029 (P2) and IRDC-321.73+005 (P2). The derived density and temperature distributions can be used to model the chemical structure and spectral maps in molecular lines.
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