Related papers: Improving Posterior Inference of Galaxy Properties…
Galaxy clustering and galaxy-galaxy lensing probe the connection between galaxies and their dark matter haloes in complementary ways. On one hand, the halo occupation statistics inferred from the observed clustering properties of galaxies…
We introduce Statistical Flow Matching (SFM), a novel and mathematically rigorous flow-matching framework on the manifold of parameterized probability measures inspired by the results from information geometry. We demonstrate the…
Understanding how galaxies interact with the circumgalactic medium (CGM) requires determining how galaxies morphological and stellar properties correlate with their CGM properties. We report an analysis of 66 well-imaged galaxies detected…
We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the algorithm using the S-PLUS optical photometry up to $r$=21,…
A notorious problem in astronomy is the recovery of the true shape and spectral energy distribution (SED) of a galaxy despite attenuation by interstellar dust embedded in the same galaxy. This problem has been solved for a few hundred…
Galaxy spectral energy distribution (SED) modelling is a powerful tool, but constraining how well it is able to infer the true values for galaxy properties (e.g. the star formation rate, SFR) is difficult because independent determinations…
With the dramatic rise in high-quality galaxy data expected from Euclid and Vera C. Rubin Observatory, there will be increasing demand for fast high-precision methods for measuring galaxy fluxes. These will be essential for inferring the…
In this investigation, we leverage the combination of Dark Energy Spectroscopic Instrument Legacy imaging Surveys Data Release 9 (DESI LS DR9), Survey Validation 3 (SV3), and Year 1 (Y1) data sets to estimate the conditional luminosity and…
We present a novel method to estimate galaxy physical properties from spectral energy distributions (SEDs), alternate to template fitting techniques and based on self-organizing maps (SOM) to learn the high-dimensional manifold of a…
One of the most important properties of a galaxy is the total stellar mass, or equivalently the stellar mass-to-light ratio (M/L). It is not directly observable, but can be estimated from stellar population synthesis. Currently, a galaxy's…
Following from our recent work, we present a detailed analysis of star-formation and interstellar medium (ISM) scaling relations, done on a representative sample of nearby galaxies. H$\alpha$ images are analysed in order to derive the…
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…
Estimating properties of star clusters from unresolved broadband photometry is a challenging problem that is classically tackled by spectral energy distribution (SED) fitting methods that are based on simple stellar population models.…
Conditional Flow Matching (CFM) models can generate high-quality samples from a non-informative prior, but they can be slow, often needing hundreds of network evaluations (NFE). To address this, we propose Implicit Dynamical Flow Fusion…
We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for $\sim 8$ million galaxies in the Hyper Suprime-Cam (HSC) Wide survey with $z \leq 0.75$ and $m \leq…
We explore galaxy properties and their link with environment and clustering using a population of ~1000 galaxies formed in a high resolution hydrodynamic simulation of the Lambda CDM cosmology. At the redshift we concentrate on, z=1, the…
(Abridged) We explore the dependence of galaxy stellar population properties derived from broad-band SED-fitting - such as age, stellar mass, dust reddening, etc. - on a variety of parameters, such as SFHs, metallicity, IMF, dust reddening…
The primary method for inferring the stellar mass ($M_*$) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history and dust attenuation law…
Conditional flow matching (CFM) stands out as an efficient, simulation-free approach for training flow-based generative models, achieving remarkable performance for data generation. However, CFM is insufficient to ensure accuracy in…
The measurement of galaxy morphological parameters from astronomical images features in a wide range of modern analyses, including galaxy evolution and cosmological weak lensing studies. The precision and accuracy of morphological parameter…