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The properties of unresolved protostars and their local environment (e.g., disk, envelope and outflow characteristics) are frequently inferred from spectral energy distributions (SEDs) through comparison with idealized model SEDs. However,…
The meaningful comparison of models of galaxy evolution to observations is critically dependent on the accurate treatment of dust attenuation. To investigate dust absorption and emission in galaxies we have assembled a sample of ~1000…
We present a new numerical code which is designed to derive a spectral energy distribution (SED) for an arbitrary spatial distribution of stellar and gaseous components in a dusty starburst galaxy. We apply a ray tracing method to numerical…
The wavelength-coverage and sensitivity of JWST now enables us to probe the rest-frame UV - optical spectral energy distributions (SEDs) of galaxies at high-redshift ($z>4$). From these SEDs it is, in principle, through SED fitting possible…
The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We present a deep-learning framework for spectral…
We introduce a non-parametric approach, the Stellar Population Synthesis with Equivalent Widths (SEW) method, to reconstruct spectrally-resolved attenuation curves for 169,568 star-forming galaxies from the Sloan Digital Sky Survey Data…
Bridging theory and observations is a key task to understand galaxy formation and evolution. With the advent of state-of-the-art observational facilities, an accurate modelling of galaxy observables through radiative transfer simulations…
We present simulations of Far Infrared (FIR) emission by dust in spiral galaxies, based on the Monte Carlo radiative transfer code of Bianchi, Ferrara & Giovanardi (1996). The radiative transfer is carried out at several wavelength in the…
(abridged) Context: Both observations and simulations of embedded protostars have progressed rapidly in recent years. Bringing them together is an important step in advancing our knowledge about the earliest phases of star formation. Aims:…
A simple, fully connected neural network with a single hidden layer is used to estimate stellar masses for star-forming galaxies. The model is trained on broad-band photometry - from far-ultraviolet to mid-infrared wavelengths - generated…
We present the Empirical Dust Attenuation (EDA) framework -- a flexible prescription for assigning realistic dust attenuation to simulated galaxies based on their physical properties. We use the EDA to forward model synthetic observations…
We present the basic features and preliminary results of the interface between our spectro-photometric model GRASIL (that calculates galactic SED from the UV to the sub-mm with a detailed computation of dust extinction and thermal…
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…
Circumstellar disks are characteristic for star formation and vanish during the first few Myr of stellar evolution. During this time planets are believed to form in the dense midplane by growth, sedimentation and aggregation of dust.…
Fitting model spectral energy distributions (SED) to galaxy photometric data is a widely used method to recover galaxy parameters from galaxy surveys. However, the parameter space used to describe galaxies is wide and interdependent, and…
We present detailed modeling of the spectral energy distribution (SED) of the spiral galaxies NGC 891, NGC 4013, and NGC 5907 in the far-infrared and submm wavelengths. The model takes into account the emission produced by the diffuse dust…
Robust estimation of star formation rates (SFRs) at higher redshifts (z>1) using UV-optical-NIR photometry is contingent on the ability of spectral energy distribution (SED) fitting to simultaneously constrain the dust attenuation, stellar…
We present a cosmology analysis of simulated weak lensing convergence maps using the Neural Field Scattering Transform (NFST) to constrain cosmological parameters. The NFST extends the Wavelet Scattering Transform (WST) by incorporating…
The spectral energy distribution (SED) of observed stars in wide-field images is crucial for chromatic point spread function (PSF) modelling methods, which use unresolved stars as integrated spectral samples of the PSF across the field of…
We have thoroughly characterized the ultraviolet to near-infrared (0.15 - 2.2 micron) spectral energy distribution (SED) of the central parsec of the M33 nucleus through new infrared photometry and optical/near-infrared spectroscopy,…