Related papers: The ILIUM forward modelling algorithm for multivar…
Large-scale precision matrix estimation is of fundamental importance yet challenging in many contemporary applications for recovering Gaussian graphical models. In this paper, we suggest a new approach of innovated scalable efficient…
Context. As increasingly more spectroscopic data are being delivered by medium- and high-resolving power multi-object spectrographs, more automatic stellar parameter determination softwares are being developed. The quality of the spectra…
Context. While Gaia enables to probe in great detail the extended local neighbourhood, the thin disk structure at larger distances remains sparsely explored. Aims. We aim here to build a non-parametric 3D model of the thin disc structures…
Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to…
We propose a methodological framework to perform forward asteroseismic modeling of stars with a convective core, based on gravity-mode oscillations. These probe the near-core region in the deep stellar interior. The modeling relies on a set…
High-precision astrometry well beyond the capacities of Gaia will provide a unique way to achieve astrophysical breakthroughs, in particular on the nature of dark matter, and a complete survey of nearby habitable exoplanets. In this…
The orbital solutions for astrometric (unresolved) binary stars provided in the Gaia mission Data Release 3 reveal an obvious deficit of face-on orbits with line-of-sight inclinations close to 0 or $\pi$. This is shown to be an intrinsic…
Rapidly growing datasets from stellar spectroscopic surveys are providing unprecedented opportunities to analyse the chemical evolution history of our Galaxy. However, spectral analysis requires accurate modelling of synthetic stellar…
Aims. We present simulations of the perfomances of the future SPHERE IFS instrument designed for imaging extrasolar planets in the near infrared (Y, J, and H bands). Methods. We used the IDL package code for adaptive optics simulation…
Galaxy intrinsic alignments (IA) are a critical uncertainty for current and future weak lensing measurements. We describe a perturbative expansion of IA, analogous to the treatment of galaxy biasing. From an astrophysical perspective, this…
Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for…
Due to the importance of accurate Fourier parameters, we devise a method that is more appropriate for deriving these parameters on low-quality data than the traditional Fourier fitting. Based on the accurate light curves of 248 fundamental…
We consider a class of systems with time-varying parameters, which are written as linear regressions with bounded disturbances. The task is to estimate such parameters under the condition that the regressor is finitely exciting (FE).…
A number of open problems hinder our present ability to extract scientific information from data that will be gathered by the near-future gravitational-wave mission LISA. Many of these relate to the modeling, detection and characterization…
Generalized additive index models (GAIMs) offer a flexible semiparametric framework for capturing complex data relationships, balancing the interpretability of parametric models with the flexibility of nonparametric approaches. However,…
We present a method for the determination of [alpha/Fe] ratios from low-resolution (R = 2000) SDSS/SEGUE stellar spectra. By means of a star-by-star comparison with degraded spectra from the ELODIE spectral library and with a set of…
White dwarfs represent the end stage for 97% of stars, making precise parameter measurement crucial for understanding stellar evolution. Traditional estimation methods involve fitting spectra or photometry, which require high-quality data.…
The intrinsic alignments (IA) of galaxies, a key contaminant in weak lensing analyses, arise from correlations in galaxy shapes driven by tidal interactions and galaxy formation processes. Accurate IA modeling is essential for robust…
Context.The Gaia Early Data Release 3 contained the positions, parallaxes and proper motions of 1.5 billion sources, among which some did not fit well the "single star" model. Binarity is one of the causes of this. Aims. Four million of…
Machine Learning is an efficient method for analyzing and interpreting the increasing amount of astronomical data that is available. In this study, we show, a pedagogical approach that should benefit anyone willing to experiment with Deep…