相关论文: Fitting galaxy spectra with STECKMAP: a user guide

Adaptive dynamic programming is a collective term for a variety of approaches to infinite-horizon optimal control. Common to all approaches is approximation of the infinite-horizon cost function based on dynamic programming philosophy.…

We present a stellar parameter catalog built to accompany the MaStar Stellar Library, which is a comprehensive collection of empirical, medium-resolution stellar spectra. We constructed this parameter catalog by using a multicomponent…

Context. Limb darkening is an important tool for understanding stellar atmospheres, but most observations measuring limb darkening assume various parameterizations that yield no significant information about the structure of stellar…

Spectangular is a GUI based software package written in C++ designed for spectral disentangling on the wavelength scale. The code disentangles spectra of SB1 and SB2 systems and can now also be used also for spectra showing variability. In…

Spectral lines from interstellar molecules provide crucial insights into the physical and chemical conditions of the interstellar medium. Traditional spectral line analysis relies heavily on manual intervention, which becomes impractical…

We introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex's vertices…

High resolution spectral models for simple stellar populations (SSP) developed in the past few years have become a standard ingredient in studies of stellar population of galaxies. As more such models become available, it becomes…

Statistics of the weak lensing of galaxies can be used to constrain cosmology if the galaxy shear can be estimated accurately. In general this requires accurate modelling of unlensed galaxy shapes and the point spread function (PSF). I…

Spectral clustering is a powerful method for finding structure in a dataset through the eigenvectors of a similarity matrix. It often outperforms traditional clustering algorithms such as $k$-means when the structure of the individual…

Inferring stellar parameters and chemical abundances by forward modeling stellar spectra usually requires a spectral synthesis code, or an emulator constructed from a curated training set. In these situations continuum normalization is…

The stellar line-of-sight velocity distribution (LOSVD) can be strongly asymmetric in regions where the light contributions of both disc and bulge in spiral and lenticular galaxies are comparable. Existing techniques for the stellar…

The development of evolutionary stellar population models is central to interpreting observations of galaxies in terms of astrophysical quantities. Stellar population models must therefore be both accurate and compatible with inversion…

With the advent of dedicated photometric space missions, the ability to rapidly process huge catalogues of stars has become paramount. Bellinger and Angelou et al. (2016) recently introduced a new method based on machine learning for…

With current space-based missions it is now possible to obtain age-sensitive asteroseismic information for tens of thousands of red giants. This provides a promising opportunity to study the Galactic structure and evolution. We use…

One of the great challenges in understanding stars is measuring their masses. The best methods for measuring stellar masses include binary interaction, asteroseismology and stellar evolution models, but these methods are not ideal for red…

ASTRA is a Python package that provides a modular, instrument-independent interface for working with high-resolution stellar spectra. Designed to support data from multiple spectrographs, including ESPRESSO (Pepe et al., 2021), HARPS (Mayor…

We present a comprehensive method for determining stellar mass functions, and apply it to samples in the local Universe. We combine the classical 1/Vmax approach with STY, a parametric maximum likelihood method and SWML, a non-parametric…

Asteroseismology is a powerful tool to precisely determine the evolutionary status and fundamental properties of stars. With the unprecedented precision and nearly continuous photometric data acquired by the NASA Kepler mission, parameters…

Photometric Redshift is critical for analyzing astronomical objects, but existing ML methods often overlook the aleatoric uncertainties inherent in observed data. We introduce Starkindler, a novel training objective that explicitly…

The stellar populations of galaxies contain a wealth of detailed information. From the youngest, most massive stars, to almost invisible remnants, the history of star formation is encoded in the stars that make up a galaxy. Extracting some,…