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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.

The scatter (σsSFR) of the specific star formation rates of galaxies is a measure of the diversity in their star formation histories (SFHs) at a given mass. In this paper, we employ the Evolution and Assembly of GaLaxies and their Environments (EAGLE) simulations to study the dependence of the σsSFR of galaxies on stellar mass (M⋆) through the σsSFR–M⋆ relation in z ∼ 0–4. We find that the relation evolves with time, with the dispersion depending on both stellar mass and redshift. The models point to an evolving U-shaped form for the σsSFR–M⋆ relation, with the scatter being minimal at a characteristic mass M⋆ of 109.5M⊙ and increasing both at lower and higher masses. This implies that the diversity of SFHs increases toward both the low- and high-mass ends. We find that feedback from active galactic nuclei is important for increasing the σsSFR for high-mass objects. On the other hand, we suggest that feedback from supernovae increases the σsSFR of galaxies at the low-mass end. We also find that excluding galaxies that have experienced recent mergers does not significantly affect the σsSFR–M⋆ relation. Furthermore, we employ the EAGLE simulations in combination with the radiative transfer code SKIRT to evaluate the effect of SFR/stellar mass diagnostics in the σsSFR–M⋆ relation, and find that the SFR/M⋆ methodologies (e.g., SED fitting, UV+IR, UV+IRX–β) widely used in the literature to obtain intrinsic properties of galaxies have a large effect on the derived shape and normalization of the σsSFR–M⋆ relation. [ABSTRACT FROM AUTHOR]

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 (MC) radiative transfer (RT) method, including various forms of biasing to accelerate the calculations. Because of the probabilistic nature of the MC 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 MCRT method, without any biasing mechanisms, starts to break down for transverse optical depths τ ≳ 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 τ ≳ 75 the MC methods used in our study fail to solve the one-dimensional slab problem, implying the need for approximations such as a modified random walk. [ABSTRACT FROM AUTHOR]