相关论文: A Comparison of Approaches in Fitting Continuum SE…
Traditional spectral energy distribution (SED) fitting techniques face uncertainties due to assumptions in star formation histories and dust attenuation curves. We propose an advanced machine learning-based approach that enhances…
Traditional spectral energy distribution (SED) fitting codes used to derive galaxy physical properties are often uncertain at the factor of a few level owing to uncertainties in galaxy star formation histories and dust attenuation curves.…
The study of galaxy evolution hinges on our ability to interpret multi-wavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models which allow us to infer physical…
Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time,…
The spectral energy distribution (SED) of a galaxy contains information on the galaxy's physical properties, and multi-wavelength observations are needed in order to measure these properties via SED fitting. In planning these surveys,…
Traditional spectral energy distribution (SED)-fitting methods for stellar mass estimation face persistent challenges including systematic biases and computational constraints. We present a controlled comparison of machine learning (ML) and…
We introduce the Dense Basis method for Spectral Energy Distribution (SED) fitting. It accurately recovers traditional SED parameters, including M$_*$, SFR and dust attenuation, and reveals previously inaccessible information about the…
For high-redshift submillimetre or millimetre sources detected with single dish telescopes, interferometric follow-up has shown that many are multiple submm galaxies blended together. Confusion-limited Herschel observations of such targets…
Fitting the multi-wavelength spectral energy distributions (SEDs) of galaxies is a widely used technique to extract information about the physical properties of galaxies. However, a major difficulty lies in the numerous uncertainties…
Spectral Energy Distribution (SED) fitting is a well-developed astrophysical tool that has recently been applied to high-redshift Lyman Alpha-emitting galaxies. If rest-frame ultraviolet through near-infrared photometry is available, it…
State-of-the-art spectral energy distribution (SED) analyses use a Bayesian framework to infer the physical properties of galaxies from observed photometry or spectra. They require sampling from a high-dimensional space of SED model…
Simulated annealing (SA) was inspired from annealing in metallurgy, a technique involving heating and controlled cooling of a material to increase the size of its crystals and reduce their defects, both are attributes of the material that…
We present a method to analyze the spectral energy distributions (SEDs) of young stellar objects (YSOs). Our approach is to fit data with pre-computed 2-D radiation transfer models spanning a large region of parameter space. This allows us…
We present Starduster, a supervised deep learning model that predicts the multi-wavelength SED from galaxy geometry parameters and star formation history by emulating dust radiative transfer simulations. The model is comprised of three…
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…
Sophisticated spectral energy distribution (SED) models describe dust attenuation and emission using geometry parameters. This treatment is natural since dust effects are driven by the underlying star-dust geometry in galaxies. An example…
We present a hierarchical Bayesian method for fitting infrared spectral energy distributions (SEDs) of dust emission to observed fluxes. Under the standard assumption of optically thin single temperature (T) sources the dust SED as…
Derivation of physical properties of galaxies using spectral energy distribution (SED) fitting is a powerful method, but can suffer from various systematics arising from model assumptions. Previously, such biases were mostly studied in the…
This article presents a new dust SED model, named HerBIE, aimed at eliminating the noise-induced correlations and large scatter obtained when performing least-squares fits. The originality of this code is to apply the hierarchical Bayesian…
Diffusion models have achieved remarkable success in generative tasks but suffer from high computational costs due to their iterative sampling process and quadratic attention costs. Existing training-free acceleration strategies that reduce…