Related papers: Testing pre-main sequence models: the power of a B…
Context: Quantitative spectroscopy of luminous blue stars relies on detailed non-LTE model atmospheres whose increasing physical realism makes direct, iterative analyses computationally demanding. Aims: We introduce MAUI (Machine-learning…
We present a Bayesian implementation of isochrone fitting in deriving stellar ages and masses, incorporating absolute K magnitude ($\rm M_K$) derived from 2MASS photometry and Gaia DR1 parallax and differentiation between initial bulk…
[abridged] Inversion techniques are the most powerful methods to obtain information about the thermodynamical and magnetic properties of solar and stellar atmospheres. In the last years, we have witnessed the development of highly…
Accurate stellar properties are essential for precise stellar astrophysics and exoplanetary science. In the M-dwarf regime, much effort has gone into defining empirical relations that can use readily accessible observables to assess…
We report on the properties of the low-mass stars that recently formed in the central ~ 2.7'x2.7' of 30 Dor including the R136 cluster. Using the photometric catalogue of De Marchi et al. (2011c), based on observations with the Hubble Space…
Pulsational properties of 1.8 M$_{\odot}$ stellar models covering the latest stages of contraction toward the main sequence up to early hydrogen burning phases are investigated by means of linear nonadiabatic analyses. Results confirm that…
The ages of stars have historically relied on isochrone fitting of standardised grids of models. While these stellar models have provided key constraints on observational samples of massive stars, they inherit many systematic uncertainties,…
With the routine collection of massive-dimensional predictors in many application areas, screening methods that rapidly identify a small subset of promising predictors have become commonplace. We propose a new MOdular Bayes Screening (MOBS)…
We report on a very large set of simulations of collisions between two main sequence (MS) stars. These computations were done with the ``Smoothed Particle Hydrodynamics'' method. Realistic stellar structure models for evolved MS stars were…
The study of young stellar populations has revealed that most stars are in binary or higher order multiple systems. In this study the influence on the stellar initial mass function (IMF) of large quantities of unresolved multiple massive…
Predictive dynamical models for marine ecosystems are used for a variety of needs. Due to sparse measurements and limited understanding of the myriad of ocean processes, there is however significant uncertainty. There is model uncertainty…
Pre-main sequence (PMS) binaries and multiples enable critical tests of stellar models if masses, metallicities, and luminosities of the component stars are known. We have analyzed high-resolution, high signal-to-noise echelle spectra of…
Constraining parameters such as the initial mass function high-mass slope and the frequency of type Ia supernovae is of critical importance in the ongoing quest to understand galactic physics and create realistic hydrodynamical simulations.…
Rotation periods and projected equatorial velocities of pre-main-sequence (PMS) stars in star forming regions can be combined to give projected stellar radii. Assuming random axial orientation, a Monte-Carlo model is used to illustrate that…
(Abridged) Highly unequal-mass ratio binaries are rare among field brown dwarfs, with the known census described by q^(4.9+/-0.7). However, such systems can test the joint accuracy of evolutionary and atmospheric models, under the…
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a…
The frequency and properties of multiple star systems offer powerful tests of star formation models. Multiplicity surveys over the past decade have shown that binary properties vary strongly with mass, but the functional forms and the…
Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian…
In high-dimensional Bayesian statistics, various methods have been developed, including prior distributions that induce parameter sparsity to handle many parameters. Yet, these approaches often overlook the rich spectral structure of the…
A common problem in natural sciences is the comparison of competing models in the light of observed data. Bayesian model comparison provides a statistically sound framework for this comparison based on the evidence each model provides for…