Related papers: VarStar Detect, a Python library dedicated to the …
One of the few ways that we can understand the environment around dusty stars and how much material they contribute back to the Universe, is by fitting their brightness at different wavelengths with models that account for how the energy…
The large side aperture of the NuSTAR telescope for unfocused photons (so-called stray light) is a known source of rich astrophysical information. To support many studies based on the NuSTAR stray light data, we present a fully automatic…
Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from…
Additional pulsation modes have been discovered in many Cepheids, RR Lyrae, and other variable stars. Fourier transforms are used to find, fit and subtract the main pulsation period and its harmonics to reveal additional modes. Commonly,…
In the analysis of variable stars, the problem of sampling is central. This article focusses on the determination of the Nyquist frequency. It is well defined in the case of regular sampling. However, the time series of variable stars…
We explore methods for the identification of stellar flare events in irregularly sampled data of ground-based time domain surveys. In particular, we describe a new technique for identifying flaring stars, which we have implemented in a…
Stellar atmosphere modelling predicts the luminosity and temperature of a star, together with parameters such as the effective gravity and the metallicity, by reproducing the observed spectral energy distribution. Most observational data…
Asteroseismology is an exceptional tool for studying stars by using the properties of observed modes of oscillation. So far the process of performing an asteroseismic analysis of a star has remained somewhat esoteric and inaccessible to…
We introduce PyChEst, a Python package which provides tools for the simultaneous estimation of multiple changepoints in the distribution of piece-wise stationary time series. The nonparametric algorithms implemented are provably consistent…
We review in brief the development and implementation of the Star integral, a tool yielding measurements of correlations much superior to conventional methods. A version for use in pion interferometry is explained. We also show how effects…
We present the pulsar_spectra software repository, an open-source pulsar flux density catalogue and automated spectral fitting software that finds the best spectral model and produces publication-quality plots. The Python-based software…
Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a…
We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in {\tt Python} to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to…
BayesPy is an open-source Python software package for performing variational Bayesian inference. It is based on the variational message passing framework and supports conjugate exponential family models. By removing the tedious task of…
The Variable Star One-shot Project (VSOP) is aimed at (1) providing the variability type and spectral type of all unstudied variable stars, (2) process, publish, and make the data available as automatically as possible, and (3) generate…
A complete single-point statistical description of a narrow-band partially polarized optical field is developed in terms of the 2-D Period-Averaged Probability Density Function (PA-PDF) of the electrical field vector. This statistic can be…
A method is developed for fitting theoretically predicted astronomical spectra to an observed spectrum. Using a hierarchical Bayesian principle, the method takes both systematic and statistical measurement errors into account, which has not…
We accurately identify and classify the variability of A-F stars in the southern continuous viewing zone of the TESS satellite. The brightness limit was set to 10 mag to ensure the utmost reliability of our results and allow for…
We present TurbuStat (v1.0): a Python package for computing turbulence statistics in spectral-line data cubes. TurbuStat includes implementations of fourteen methods for recovering turbulent properties from observational data. Additional…
This paper explores optimal methods for obtaining one-dimensional (1D) powder pattern intensities from two-dimensional (2D) planar detectors with good estimates of their standard deviations. We describe methods to estimate uncertainties…