Related papers: SEW: A full-spectrum linear fitting with stellar p…
Strong convergence rates for time-discrete numerical approximations of semilinear stochastic evolution equations (SEEs) with smooth and regular nonlinearities are well understood in the literature. Weak convergence rates for time-discrete…
The HELP project focuses on the data from ESA's Herschel mission, which covered over 1300$deg^2$ and is preparing to publish a multi-wavelength catalogue of millions of objects. Our main goal is to find the best approach to simultaneously…
Taking advantage of recent important advances in the calculation of high-resolution spectral grids of stellar atmospheres at short wavelengths, and their implementation for population synthesis models, we briefly review here some special…
Galactic dust emission is often accounted for in cosmic microwave background (CMB) analyses by fitting a simple two-parameter modified blackbody (MBB) model in each pixel, which nominally accounts for the temperature and opacity of the…
We performed a near-infrared (NIR, $\sim$1.0$\mu$m-2.4$\mu$m) stellar population study in a sample of early type galaxies. The synthesis was performed using five different evolutionary population synthesis libraries of models. Our main…
Understanding the impact of dust on the spectral energy distributions (SEDs) of galaxies is crucial for inferring their physical properties and for studying the nature of interstellar dust. We analyze dust attenuation curves for $\sim 6400$…
This article investigates the problem of estimating stellar atmospheric parameters from spectra. Feature extraction is a key procedure in estimating stellar parameters automatically. We propose a scheme for spectral feature extraction and…
We present Stellar Locus Regression (SLR), a method of directly adjusting the instrumental broadband optical colors of stars to bring them into accord with a universal stellar color-color locus, producing accurately calibrated colors for…
Dust attenuation shapes the spectral energy distribution of galaxies. It is particularly true for dusty galaxies in which stars experience a heavy attenuation. The combination of UV-to-IR photometry with the spectroscopic measurement of the…
We present model spectra of stellar populations with variable chemical composition. We derived the [alpha/Fe] abundance ratio of the stars of the most important libraries (ELODIE, CFLIB and MILES) using full spectrum fitting and we…
We present piXedfit, pixelized spectral energy distribution (SED) fitting, a Python package that provides tools for analyzing spatially resolved properties of galaxies using multiband imaging data alone or in combination with integral field…
We test the predictions of spectral synthesis models based on seven different massive-star prescriptions against Legacy ExtraGalactic UV Survey (LEGUS) observations of eight young massive clusters in two local galaxies, NGC 1566 and NGC…
(Abridged) In a recent work we explored the dependence of galaxy stellar population properties derived from broad-band spectral energy distribution fitting on the fitting parameters, e.g. SFHs, age grid, metallicity, IMF, dust reddening,…
Stellar population synthesis is a crucial methodology in astrophysics, enabling the interpretation of the integrated light of galaxies and stellar clusters. By combining empirical and/or theoretical libraries of the spectral energy…
A method is developed for fitting theoretically predicted astronomical spectra to an observed spectrum. Using a hierarchical Bayesian principle, the method takes both systematic and statistical measurement errors into account, which has not…
I present a simple self-consistent dust spectral energy distribution (SED) model that has been applied to fit the well-sampled observed UV-to-radio SED of four nearby starbursting dwarf galaxies. The main originality of this model is that…
Weight averaging has become a standard technique for enhancing model performance. However, methods such as Stochastic Weight Averaging (SWA) and Latest Weight Averaging (LAWA) often require manually designed procedures to sample from the…
Deep learning has significantly advanced image edge detection (ED), primarily through improved feature extraction. However, most existing ED models apply uniform feature fusion across all pixels, ignoring critical differences between…
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…
Pathology images are considered the ``gold standard" for cancer diagnosis and treatment, with gigapixel images providing extensive tissue and cellular information. Existing methods fail to simultaneously extract global structural and local…