Related papers: Astroinformatics: Statistically Optimal Approximat…
We present preliminary results from our long-baseline interferometry (LBI) survey to constrain the multiplicity properties of intermediate-mass A-type stars within 80pc. Previous multiplicity studies of nearby stars exhibit orbital…
Asteroseismic observations are crucial to constrain stellar models with precision. Bayesian Estimation of STellar Parameters (BESTP) is a tool that utilizes Bayesian statistics and nested sampling Monte Carlo algorithm to search for the…
We propose an object detection algorithm which is efficient and fast enough to be used in (almost) real time with the limited computer capacities onboard satellites. For stars below the saturation limit of the CCD detectors it is based on a…
We present TA-DA, a new software aimed at greatly simplify and improve the analysis of stellar photometric data in comparison with theoretical models, and allow the derivation of stellar parameters from multi-band photometry. Its…
Stochastic gradient descent type methods are ubiquitous in machine learning, but they are only applicable to the optimization of differentiable functions. Proximal algorithms are more general and applicable to nonsmooth functions. We…
The census of stellar and substellar companions of nearby stars is largely incomplete. It is, however, fundamentally important in the understanding of the stellar and planetary formation and evolution mechanisms. We aim to characterize the…
Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…
Upcoming large-scale spectroscopic surveys such as WEAVE and 4MOST will provide thousands of spectra of massive stars, which need to be analysed in an efficient and homogeneous way. Studies on massive stars are usually based on samples of a…
The next decade of survey astronomy has the potential to transform our knowledge of variable stars. Stellar variability underpins our knowledge of the cosmological distance ladder, and provides direct tests of stellar formation and…
The aim of this paper is to demonstrate the accuracy of our knowledge of close stellar passage distances in the pre-GAIA era.We used the most precise astrometric and kinematic data available at the moment and prepared a list of 40 stars…
In this paper, we study numerical approximations for optimal control of a class of stochastic partial differential equations with partial observations. The system state evolves in a Hilbert space, whereas observations are given in…
Gaia is undertaking a deep synoptic survey of the Galaxy, but photometry from individual epochs has, as of yet, only been released for a minimal number of sources. We show that it is possible to identify variable stars in Gaia Data Release…
This paper contains the fifth part of the Catalog of Variable Stars created from the V-band photometric data collected by 9x9 deg camera of the All Sky Automated Survey. Preliminary list of variable stars found in the fields located between…
Context. The precise determinations of stellar mass at $\sim$1% provide important constraints on stellar evolution models. Accurate parallax measurements can also serve as independent benchmarks for the next Gaia data release. Aims. We aim…
We present the results of an adaptive optics survey for faint companions among Galactic O-type star systems (V < 8) using the Advanced Electro-Optical System (AEOS) 3.6-meter telescope on Haleakala. We surveyed these O star systems in…
This paper considers both the least squares and quasi-maximum likelihood estimation for the recently proposed scalable ARMA model, a parametric infinite-order vector AR model, and their asymptotic normality is also established. It makes…
This paper studies the numerical methods to approximate the solutions for a sort of McKean-Vlasov neutral stochastic differential delay equations (MV-NSDDEs) that the growth of the drift coefficients is super-linear. First, We obtain that…
Aims. This work aims at constraining the masses and separations of potential substellar companions to five accelerating stars (HIP 1481, HIP 88399, HIP 96334, HIP 30314 and HIP 116063) using multiple data sets acquired with different…
Modern large-scale photometric surveys have provided us with multi-band photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (\teff) and metallicities (\feh), absolute…
Variational Inference (VI) is an attractive alternative to Markov Chain Monte Carlo (MCMC) due to its computational efficiency in the case of large datasets and/or complex models with high-dimensional parameters. However, evaluating the…