相关论文: Data-Driven Stellar Models

It has long been understood that the light curve of a transiting planet constrains the density of its host star. That fact is routinely used to improve measurements of the stellar surface gravity and has been argued to be an independent…

The scarcity of high-fidelity extinction measurements remains a bottleneck in deriving accurate stellar properties from Gaia parallaxes. In this work, we aim to derive precision extinction estimates for APOGEE DR19 stars, establishing a new…

It takes years of effort employing the best telescopes and instruments to obtain high-quality stellar photometry, astrometry, and spectroscopy. Stellar evolution models contain the experience of lifetimes of theoretical calculations and…

We perform a comparison of different approaches to star-galaxy classification using the broad-band photometric data from Year 1 of the Dark Energy Survey. This is done by performing a wide range of tests with and without external `truth'…

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…

Aims. We aim at deriving stellar atmospheric parameters based on the photometric data from the Javalambre Photometric Local Universe Survey (J-PLUS) in addition to near-infrared photometry from the Two Micron All-Sky Survey (2MASS).…

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…

Data-driven approaches play a crucial role in space computing, and our paper focuses on analyzing data to learn more about celestial objects. Photometric redshift, a measure of the shift of light towards the red part of the spectrum, helps…

Observational astronomy has undergone a significant transformation driven by large-scale surveys, such as the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) Survey, the Sloan Digital Sky Survey (SDSS), and the Gaia…

We present a new method for inferring photometric redshifts in deep galaxy and quasar surveys, based on a data driven model of latent spectral energy distributions (SEDs) and a physical model of photometric fluxes as a function of redshift.…

We present MWFitting, a method to fit the stellar components of the Galaxy by comparing Hess Diagrams (HDs) from TRILEGAL models to real data. We apply MWFitting to photometric data from the first three years of the Dark Energy Survey…

We describe a technique for deriving effective temperatures, surface gravities, rotation velocities, and radial velocities from high resolution near-IR spectra. The technique matches the observed near-IR spectra to spectra synthesized from…

Context. The surface structures and dynamics of cool stars are characterized by the presence of convective motions and turbulent flows which shape the emergent spectrum. Aims. We used realistic three-dimensional radiative hydrodynamical…

The Next Generation Space Telescope (NGST) will gather unprecedented spectro-photometric data on galaxies out to the highest redshifts. It is therefore crucial to identify the spectro-photometric diagnostics within reach of NGST, which will…

We test how well available stellar population models can reproduce observed u,g,r,i,z-band photometry of the local galaxy population (0.02<=z<=0.03) as probed by the SDSS. Our study is conducted from the perspective of a user of the models,…

We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the…

Over the last years a new generation of model atmosphere codes, which include the effects of metal line-blanketing of millions of spectral lines in NLTE, has been used to re-determine the properties of massive stars through quantitative…

In the last decades, stellar atmosphere models have become a key tool in understanding massive stars. Applied for spectroscopic analysis, these models provide quantitative information on stellar wind properties as well as fundamental…

The ability to generate physically plausible ensembles of variable sources is critical to the optimization of time-domain survey cadences and the training of classification models on datasets with few to no labels. Traditional data…

We present MINESweeper, a tool to measure stellar parameters by jointly fitting observed spectra and broadband photometry to model isochrones and spectral libraries. This approach enables the measurement of spectrophotometric distances, in…