Related papers: Starduster: A multi-wavelength SED model based on …
The treatment of dust attenuation is crucial in order to compare the predictions of galaxy formation models with multiwavelength observations. Most past studies have either used simple analytic prescriptions or else full radiative transfer…
The translation from direct observables to physical properties of galaxies is a key step in reconstructing their evolutionary histories. Star-dust geometry and inhomogeneous stellar populations can induce spatial variations in the…
Determining the dust properties of high-redshift galaxies from their far-infrared continuum emission is challenging due to limited multi-frequency data. As a result, the dust spectral energy distribution (SED) is often modeled as a…
We use SDSS photometry of 73 million stars to simultaneously obtain best-fit main-sequence stellar energy distribution (SED) and amount of dust extinction along the line of sight towards each star. Using a subsample of 23 million stars with…
We present a semi-empirical model for the infrared emission of dust around star-forming sites in galaxies. Our approach combines a simple model of radiative transfer in dust clouds with a state-of-the-art model of the microscopic optical…
Recent efforts on the modeling of the infrared spectral energy distributions (SEDs) of dwarf galaxies are summarised here. The characterisation of the dust properties in these low metallicity environments is just unfolding, as a result of…
In this study, we introduce SEDust, a pipeline designed to identify the best-fitting spectral energy distributions from the outputs of the DUSTY code and compare them to observational data. The pipeline incorporates a grid of 24000 models,…
In this paper, we present spectrophotometric models for galaxies of different morphological type whose spectral energy distributions (SEDs) take into account the effect of dust in absorbing UV-optical light and re-emitting it in the…
The spectral energy distributions (SEDs) of dusty high-redshift galaxies are poorly sampled in frequency and spatially unresolved. Their form is crucially important for estimating the large luminosities of these galaxies accurately, for…
Reproducing color-magnitude diagrams (CMDs) of star-resolved galaxies is one of the most precise methods for measuring the star formation history (SFH) of nearby galaxies back to the earliest time. The upcoming big data era poses challenges…
We use a sample of 149 spectroscopically confirmed UV-selected galaxies at $z\sim 2$ to investigate the relative dust attenuation of the stellar continuum and the nebular emission lines. For each galaxy in the sample, at least one…
A code computing consistently the evolution of stars, gas and dust, as well as the energy they radiate, is required to derive reliably the history of galaxies by fitting synthetic SEDs to multiwavelength observations. The new code…
[Abridged] We present a new approach to investigate the content and spatial distribution of dust in structurally unresolved star-forming galaxies from the observed dependence of integrated spectral properties on galaxy inclination. We…
We infer the large-scale source parameters of dusty galaxies from their observed spectral energy distributions (SEDs) using the analytic radiative transfer methodology presented in Chakrabarti & McKee (2005). For local ultra-luminous…
To understand how the evolution of grain size distribution in galaxies affects observed dust properties, we apply a post-processing dust evolution model to galaxy merger trees from the IllustrisTNG cosmological hydrodynamical simulation.…
We present model spectral energy distribution (SED) fits to ultraviolet/optical/infrared observations for the 258 nearby galaxies in the Local Volume Legacy survey, a sample dominated by lower-luminosity dwarf irregular systems. The data…
The spectral energy distributions (SEDs) of dust-enshrouded galaxies with powerful restframe far-infrared emission have been constrained by a range of ground-based and space-borne surveys. The IRAS catalog provides a reasonably complete…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
We present the first radiative transfer (RT) model of a non-edge-on disk galaxy in which the large-scale geometry of stars and dust is self-consistently derived through fitting of multiwavelength imaging observations from the UV to the…
Forward-modeling observables from galaxy simulations enables direct comparisons between theory and observations. To generate synthetic spectral energy distributions (SEDs) that include dust absorption, re-emission, and scattering, Monte…