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Bayesian model selection provides the cosmologist with an exacting tool to distinguish between competing models based purely on the data, via the Bayesian evidence. Previous methods to calculate this quantity either lacked general…
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.…
Diamonds with nitrogen-vacancy (NV) center ensembles are one of the most promising solid-state quantum platforms for various sensing applications. The combination of a long spin dephasing time ($T_2^*$) and a high NV center concentration is…
Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space…
Ensembles of nitrogen-vacancy (NV) centers in diamond are versatile quantum sensors with broad applications in the physical and life sciences. The concentration of neutral substitutional nitrogen ([N$_\text{s}^0$]) strongly influences…
For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare…
Massive stars are important building blocks of the Universe, and their stellar structure and evolution models are fundamental cornerstones of various fields in modern astrophysics. The precision of these models is limited by our lack of…
We present MINESweeper, a tool to measure stellar parameters by jointly fitting observed spectra and broadband photometry to model isochrones and spectral libraries. This approach enables the measurement of spectrophotometric distances, in…
Cavity-optomechanical systems realized in single-crystal diamond are poised to benefit from its extraordinary material properties, including low mechanical dissipation and a wide optical transparency window. Diamond is also rich in…
The unrivalled astrometric and photometric capabilities of the Gaia mission have given new impetus to the study of young stars: both from an environmental perspective, as members of comoving star-forming regions, and from an individual…
Binary stars are fundamental to astrophysics, providing critical insights into stellar evolution, galactic dynamics, and fundamental physics. However, the high dimensionality of orbital parameters and observational constraints present…
Asteroseismology with the Kepler space telescope is providing not only an improved characterization of exoplanets and their host stars, but also a new window on stellar structure and evolution for the large sample of solar-type stars in the…
The long-lived electronic spin of the nitrogen-vacancy (NV) center in diamond is a promising quantum sensor for detecting nanoscopic magnetic and electric fields in a variety of experimental conditions. Nevertheless, an outstanding…
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,…
Light curves of oscillating stars provide valuable insights into the stellar interiors. When oscillations from a pair of stars are captured within a single photometric aperture, they can be considered as potential asteroseismic binaries…
Clear power excess in a frequency range typical for solar-type oscillations in red giants has been detected in more than 1000 stars, which have been observed during the first 138 days of the science operation of the NASA Kepler satellite.…
Asteroseismology is a powerful tool to measure the fundamental properties of stars and probe their interiors. This is particularly efficient for red giants because their modes are well detectable and give information on their deep layers.…
The unparalleled photometric data obtained by NASA's Kepler Space Telescope has led to an improved understanding of stellar structure and evolution - in particular for solar-like oscillators in this context. Binary stars are fascinating…
In the era of Big Data, scalable and accurate clustering algorithms for high-dimensional data are essential. We present new Bayesian Distance Clustering (BDC) models and inference algorithms with improved scalability while maintaining the…
In this work, we propose a novel method to classify close binary stars, derived from the dynamical structure inherent in their light curves. We apply the technique to light curves of binaries from the revised Kepler Eclipsing binary…