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A direct comparison between hydrodynamical simulations and observations is needed to improve the physics included in the former and to test biases in the latter. Post-processing radiative transfer and synthetic observations are now the standard way to do this. We report on the first application of the SKIRT radiative-transfer code to simulations of a star-forming cloud. The synthetic observations are then analyzed following traditional observational workflows. We find that in the early stages of the simulation, stellar radiation is inefficient in heating dust to the temperatures that are observed in Galactic clouds, thus the addition of an interstellar radiation field is necessary. The spectral energy distribution of the cloud settles rather quickly after ∼3 Myr of evolution from the onset of star formation, but its morphology continues to evolve for ∼8 Myr due to the expansion of H ii regions and the respective creation of cavities, filaments, and ridges. Modeling synthetic Herschel fluxes with one- or two-component modified blackbodies underestimates total dust masses by a factor of ∼2. However, spatially resolved fitting recovers up to about 70% of the intrinsic value. This “missing mass” is located in a very cold dust component with temperatures below 10 K, which does not contribute appreciably to the far-infrared flux. This effect could bias real observations if this dust exists in large amounts. Finally, we tested observational calibrations of the SFR based on infrared fluxes and concluded that they are in agreement when compared to the intrinsic SFR of the simulation averaged over ∼100 Myr.

Galaxy kinematics and gravitational lensing are two complementary ways to constrain the distribution of dark matter on galaxy scales. The typical dark matter density profiles adopted in dynamical studies cannot easily be adopted in lensing studies. Ideally, a mass model should be used that has the global characteristics of realistic dark matter distributions, and that allows for an analytical calculation of the magnifications and deflection angles. A simple model with these properties, the broken-power-law (BPL) model, has very recently been introduced. We examine the dynamical structure of the family of BPL models. We derive simple closed expressions for basic dynamical properties, and study the distribution function under the assumption of velocity isotropy. We find that none of the BPL models with realistic parameters has an isotropic distribution function that is positive over the entire phase space, implying that the BPL models cannot be supported by an isotropic velocity distribution, or models with a more radially anisotropic orbital structure. This result limits the attractiveness of the BPL family as a tool for lensing studies to some degree. More generally, we find that not all members of the general family of double power-law or Zhao models, often used to model dark matter haloes, can be supported by an isotropic or radially anisotropic distribution function. In other words, the distribution function may become negative even for spherically symmetric models with a well-behaved density profile.

Core-collapse supernovae are expected to be efficient producers of dust, and recent Herschel and ALMA observations have revealed up to 1 M ⊙ of cold dust in the inner ejecta of SN 1987A. The formation time scale, spatial distribution and clumpiness, and the importance of the different heating sources of the dust remain poorly understood. We have started a project to make detailed 3D dust radiative transfer models for SN 1987A, based on a combination of the latest observational constraints and input from 3D hydrodynamical models and dust formation models. Preliminary results seem to indicate the need for large, micron-sized dust grains, and a relatively large dust mass.

(Context) Monte Carlo radiative transfer (MCRT) is a widely used technique to model the interaction between radiation and a medium, and plays an important role in astrophysical modelling and when comparing those models with observations. (Aims) In this work, we present a novel approach to MCRT that addresses the challenging memory access patterns of traditional MCRT algorithms, which hinder optimal performance of MCRT simulations on modern hardware with a complex memory architecture. (Methods) We reformulate the MCRT photon packet life cycle as a task-based algorithm, whereby the computation is broken down into small tasks that are executed concurrently. Photon packets are stored in intermediate buffers, and tasks propagate photon packets through small parts of the computational domain, moving them from one buffer to another in the process. (Results) Using the implementation of the new algorithm in the photoionization MCRT code CMacIonize 2.0, we show that the decomposition of the MCRT grid into small parts leads to a significant performance gain during the photon packet propagation phase, which constitutes the bulk of an MCRT algorithm, as a result of better usage of memory caches. Our new algorithm is a factor 2 to 4 faster than an equivalent traditional algorithm and shows good strong scaling up to 30 threads. We briefly discuss how our new algorithm could be adjusted or extended to other astrophysical MCRT applications. (Conclusions) We show that optimising the memory access patterns of a memory-bound algorithm such as MCRT can yield significant performance gains.

Context: The Monte Carlo method is probably the most widely used approach to solve the radiative transfer problem, especially in a general 3D geometry. The physical processes of emission, absorption, and scattering are easily incorporated in the Monte Carlo framework. Net stimulated emission, or absorption with a negative cross section, does not fit this method, however. Aims: We explore alterations to the standard photon packet life cycle in Monte Carlo radiative transfer that allow the treatment of net stimulated emission without loss of generality or efficiency. Methods: We present the explicit absorption technique that allows net stimulated emission to be handled efficiently. It uses the scattering rather than the extinction optical depth along a photon packet's path to randomly select the next interaction location, and offers a separate, deterministic treatment of absorption. We implemented the technique in a special-purpose Monte Carlo code for a two-stream 1D radiative transfer problem and in the fully featured 3D code SKIRT, and we studied its overall performance using quantitative statistical tests. Results: Our special-purpose code is capable of recovering the analytical solutions to the two-stream problem in all regimes, including the one of strong net stimulated emission. The implementation in SKIRT is straightforward, as the explicit absorption technique easily combines with the variance reduction and acceleration techniques already incorporated. In general, explicit absorption tends to improve the efficiency of the Monte Carlo routine in the regime of net absorption. Conclusions: Explicit absorption allows the treatment of net stimulated emission in Monte Carlo radiative transfer, it interfaces smoothly with... (abridged)

Context: Properly modelling scattering by interstellar dust grains requires a good characterisation of the scattering phase function. The Henyey-Greenstein phase function has become the standard for describing anisotropic scattering by dust grains, but it is a poor representation of the real scattering phase function outside the optical range. Aims: We investigate alternatives for the Henyey-Greenstein phase function that would allow the scattering properties of dust grains to be described. Our goal is to find a balance between realism and complexity: the scattering phase function should be flexible enough to provide an accurate fit to the scattering properties of dust grains over a wide wavelength range, and it should be simple enough to be easy to handle, especially in the context of radiative transfer calculations. Methods: We fit various analytical phase functions to the scattering phase function corresponding to the BARE-GR-S model, one of the most popular and commonly adopted models for interstellar dust. We weigh the accuracy of the fit against the number of free parameters in the analytical phase functions. Results: We confirm that the Henyey-Greenstein phase functions poorly describe scattering by dust grains, particularly at ultraviolet (UV) wavelengths, with relative differences of up to 50%. The Draine phase function alleviates this problem at near-infrared (NIR) wavelengths, but not in the UV. The two-term Reynolds-McCormick phase function, recently advocated in the context of light scattering in nanoscale materials and aquatic media, describes the BARE-GR-S data very well, but its five free parameters are degenerate. We propose a simpler phase function, the two-term ultraspherical-2 (TTU2) phase function, that also provides an excellent fit to the BARE-GR-S phase function over the entire UV-NIR wavelength range. (Abridged)

Computer simulations of photon transport through an absorbing and/or scattering medium form an important research tool in astrophysics. Nearly all software codes performing such simulations for three-dimensional geometries employ the Monte Carlo radiative transfer method, including various forms of biasing to accelerate the calculations. Because of the probabilistic nature of the Monte Carlo technique, the outputs are inherently noisy, but it is often assumed that the average values provide the physically correct result. We show that this assumption is not always justified. Specifically, we study the intensity of radiation penetrating an infinite, uniform slab of material that absorbs and scatters the radiation with equal probability. The basic Monte Carlo radiative transfer method, without any biasing mechanisms, starts to break down for transverse optical depths above ~20 because so few of the simulated photon packets reach the other side of the slab. When including biasing techniques such as absorption/scattering splitting and path length stretching, the simulated photon packets do reach the other side of the slab but the biased weights do not necessarily add up to the correct solution. While the noise levels seem to be acceptable, the average values sometimes severely underestimate the correct solution. Detecting these anomalies requires the judicious application of statistical tests, similar to those used in the field of nuclear particle transport, possibly in combination with convergence tests employing consecutively larger numbers of photon packets. In any case, for transverse optical depths above ~75 the Monte Carlo methods used in our study fail to solve the one-dimensional slab problem, implying the need for approximations such as a modified random walk.

Simple but flexible dynamical models are useful for many purposes, including serving as the starting point for more complex models or numerical simulations of galaxies, clusters, or dark matter haloes. We present SpheCow, a new light-weight and flexible code that allows one to easily explore the structure and dynamics of any spherical model. Assuming an isotropic or Osipkov-Merritt anisotropic orbital structure, the code can automatically calculate the dynamical properties of any model with either an analytical density profile or an analytical surface density profile as starting point. We have extensively validated SpheCow using a combination of comparisons to analytical and high-precision numerical calculations, as well as the calculation of inverse formulae. SpheCow contains readily usable implementations for many standard models, including the Plummer, Hernquist, NFW, Einasto, Sérsic, and Nuker models. The code is publicly available as a set of C++ routines and as a Python module, and it is designed to be easily extendable, in the sense that new models can be added in a straightforward way. We demonstrate this by adding two new families of models in which either the density slope or the surface density slope is described by an algebraic sigmoid function. We advocate the use of the SpheCow code to investigate the full dynamical structure for models for which the distribution function cannot be expressed analytically and to explore a much wider range of models than is possible using analytical models alone.

Context. 3D numerical simulations of radiative transfer are crucial for understanding complex astrophysical objects. For Monte Carlo radiative transfer, the spatial grid design is critical yet complex. Common grids include hierarchical octree and unstructured Voronoi grids, each with its own strengths and weaknesses. Tetrahedral grids, widely used in ray-tracing graphics, are a potential alternative. Aims. We explore the possibilities, advantages, and limitations of tetrahedral grids for Monte Carlo radiative transfer, comparing their performance with other grid structures. Method. We integrated a tetrahedral grid structure, using the TetGen library, into the SKIRT Monte Carlo radiative transfer code. Tetrahedral grids can be imported or adaptively constructed and refined within SKIRT. We implemented an efficient grid traversal method using Plücker coordinates and Plücker products. Results. We validated the tetrahedral grid construction and traversal algorithm with 2D radiative transfer benchmarks. In a simple 3D model, we compared the performance of tetrahedral, octree, and Voronoi grids. The octree grid outperformed the others in traversal speed, while the tetrahedral grid had the lowest grid quality. Overall, tetrahedral grids performed worse than octree and Voronoi grids. Conclusion. While tetrahedral grids may not be ideal for most astrophysical simulations, they offer a viable unstructured alternative to Voronoi grids for specific applications, such as post-processing hydrodynamical simulations on tetrahedral or unstructured grids.

We present the new open source C++-based Python library CosTuuM that can be used to generate infrared absorption and emission coefficients for arbitrary mixtures of spheroidal dust grains that are (partially) aligned with a magnetic field. We outline the algorithms underlying the software, demonstrate the accuracy of our results using benchmarks from literature, and use our tool to investigate some commonly used approximative recipes. We find that the linear polarization fraction for a partially aligned dust grain mixture can be accurately represented by an appropriate linear combination of perfectly aligned grains and grains that are randomly oriented, but that the commonly used picket fence alignment breaks down for short wavelengths. We also find that for a fixed dust grain size, the absorption coefficients and linear polarization fraction for a realistic mixture of grains with various shapes cannot both be accurately represented by a single representative grain with a fixed shape, but that instead an average over an appropriate shape distribution should be used. Insufficient knowledge of an appropriate shape distribution is the main obstacle in obtaining accurate optical properties. CosTuuM is available as a standalone Python library and can be used to generate optical properties to be used in radiative transfer applications.