Related papers: Testing pre-main sequence models: the power of a B…
The apparent age and mass of a stellar cluster can be strongly affected by stochastic sampling of the stellar initial mass function, when inferred from the integrated color of low mass clusters (less than ~10^4 solar masses). We use…
The ages of young star clusters are fundamental clocks to constrain the formation and evolution of pre-main-sequence stars and their protoplanetary disks and exoplanets. However, dating methods for very young clusters often disagree,…
We have developed and successfully tested a new self-consistent method to reliably identify pre-main sequence (PMS) objects actively undergoing mass accretion in a resolved stellar population, regardless of their age. The method does not…
Divergence is not only an important mathematical concept in information theory, but also applied to machine learning problems such as low-dimensional embedding, manifold learning, clustering, classification, and anomaly detection. We…
We present a Bayesian parameter-estimation pipeline to measure the properties of inspiralling stellar-mass black hole binaries with LISA. Our strategy (i) is based on the coherent analysis of the three noise-orthogonal LISA data streams,…
Asteroseismology is a powerful tool to probe the structure of stars. Space-borne instruments like CoRoT, Kepler and TESS have observed the oscillations of numerous stars, among which {\delta} Scutis are particularly interesting owing to…
Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…
I introduce a general, Bayesian method for modelling univariate time series data assumed to be drawn from a continuous, stochastic process. The method accommodates arbitrary temporal sampling, and takes into account measurement…
We present a Bayesian inference methodology for the estimation of orbital parameters on single-line spectroscopic binaries with astrometric data, based on the No-U-Turn sampler Markov chain Monte Carlo algorithm. Our approach is designed to…
Context: Internal chemical mixing in intermediate- and high-mass stars represents an immense uncertainty in stellar evolution models.In addition to extending the main-sequence lifetime, chemical mixing also appreciably increases the mass of…
This paper describes our study of the astrophysics of individual components in close pre-main-sequence binaries. We observed both stars in 17 systems, located in 4 nearby star forming regions, using low-resolution (R=760), infrared…
We study the accretion properties of pre-main sequence low-mass stars in the LH 91 association within the Large Magellanic Clouds. Using optical multiband photometry obtained with the Hubble Space Telescope, we identify 75 candidates…
We present a novel statistical algorithm, Stellar Ages, which currently infers the age, metallicity, and extinction posterior distributions of stellar populations from their magnitudes. While this paper focuses on these parameters, the…
Uncertainty in the prediction of future weather is commonly assessed through the use of forecast ensembles that employ a numerical weather prediction model in distinct variants. Statistical postprocessing can correct for biases in the…
An efficient Bayesian technique for estimation problems in fundamental stellar astronomy is tested on simulated data for a binary observed both astrometrically and spectroscopically. Posterior distributions are computed for the components'…
We conduct a statistical analysis of a combined sample of direct imaging data, totalling nearly 250 stars. The stars cover a wide range of ages and spectral types, and include five detections ($\kappa$ And b, two $\sim$60 M$_{\rm J}$ brown…
To quantify how well theoretical predictions of structural ensembles agree with experimental measurements, we depend on the accuracy of forward models. These models are computational frameworks that generate observable quantities from…
Fine particulate matter and aerosol optical thickness are of interest to atmospheric scientists for understanding air quality and its various health/environmental impacts. The available data are extremely large, making uncertainty…
Establishing ages for young clusters is key for properly tracking the star formation history of a region. In this paper we investigate a new approach to estimating ages for young populations, based on the well-founded assumption that the…
BASE-9 is a Bayesian software suite that recovers star cluster and stellar parameters from photometry. BASE-9 is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems.…