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We suggest a solution to an important problem of observational helioseismology of the separation of lines of solar acoustic (p) modes of low angular degree in oscillation power spectra by constructing optimal masks for Doppler images of the…
$\texttt{bayes_spec}$ is a Bayesian spectral line modeling framework for astrophysics. Given a user-defined model and a spectral line dataset, $\texttt{bayes_spec}$ enables inference of the model parameters through different numerical…
We develop a general framework for interpreting and analyzing high-precision lightcurves from eccentric stellar binaries. Although our methods are general, we focus on the recently discovered Kepler system KOI-54, a face-on binary of two A…
We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, $\rho$, characterizing the strength of the correlation. We…
Over the past two decades, helioseismology has revolutionized our understanding of the interior structure and dynamics of the Sun. Asteroseismology will soon place this knowledge into a broader context by providing structural data for…
With recent advances in modelling stars using high-precision asteroseismology, the systematic effects associated with our assumptions of stellar helium abundance ($Y$) and the mixing-length theory parameter ($\alpha_\mathrm{MLT}$) are…
Asteroseismology has become an indispensable method for measuring stellar ages and radii, while binary systems remain the most prevalent tool for determining stellar masses. The synergy of the two, namely pulsating stars in binary systems,…
We describe the public release of the Cluster Monte Carlo Code (CMC) a parallel, star-by-star $N$-body code for modeling dense star clusters. CMC treats collisional stellar dynamics using H\'enon's method, where the cumulative effect of…
The study of orbital resonances allows for the constraint of planetary properties of compact systems. We can predict a system's resonances by observing the orbital periods of the planets, as planets in or near mean motion resonance have…
We propose a novel Bayesian methodology for analyzing nonstationary time series that exhibit oscillatory behaviour. We approximate the time series using a piecewise oscillatory model with unknown periodicities, where our goal is to estimate…
The KEYSTONE project aims to enhance our understanding of solar-like oscillators by delivering a catalogue of global asteroseismic parameters (${\Delta\nu}$ and ${\nu_{\rm max}}$) for 173 stars, comprising mainly dwarfs and subgiants,…
Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems.…
After a brief introduction into the asteroseismic modelling of stars, we provide a compilation of the current seismic estimates of the core overshooting parameter and of the rotational frequency of single and binary massive stars. These…
We now know that a large number of stars are born in multiple systems. Additionally, more than 70% of massive stars are found in close binary systems, meaning that they will interact over the course of their lifetime. This has strong…
Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for conducting coherent parameter estimation for interferometric gravitational wave observations of an inspiral of binary compact objects using data from multiple…
Asteroseismology has proven to be a powerful method for probing stellar interiors. Analytical descriptions of the global oscillation modes, in combination with pulsation codes, have provided valuable help in processing and interpreting the…
Bayesian model selection enables comparison and ranking of conceptual subsurface models described by spatial prior models, according to the support provided by available geophysical data. Deep generative neural networks can efficiently…
We present a Markov-chain Monte-Carlo (MCMC) technique to study the source parameters of gravitational-wave signals from the inspirals of stellar-mass compact binaries detected with ground-based gravitational-wave detectors such as LIGO and…
PBjam is an open-source software package for measuring mode frequencies of solar-like oscillators. These frequencies help constrain stellar evolution models to precisely estimate masses, radii, and ages of stars. The overall aim of PBjam is…
Many problems in contemporary astrophysics---from understanding the formation of black holes to untangling the chemical evolution of galaxies---rely on knowledge about binary stars. This, in turn, depends on discovery and characterization…