相关论文: AIMS - A new tool for stellar parameter determinat…
Context: Detailed oscillation spectra comprising individual frequencies for numerous solar-type stars and red giants are or will become available. These data can lead to a precise characterisation of stars. Aims: Our goal is to test and…
In the era of advanced electromagnetic and gravitational wave detectors, it has become increasingly important to effectively combine and study the impact of stellar evolution on binaries and dynamical systems of stars. Systematic studies…
Identifying anomalies in multi-dimensional datasets is an important task in many real-world applications. A special case arises when anomalies are occluded in a small set of attributes, typically referred to as a subspace, and not…
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.…
Detecting complex interactions among risk factors in case-control studies is a fundamental task in clinical and population research. However, though hypothesis testing using logistic regression (LR) is a convenient solution, the LR…
Astronomical data are typically irregular in time, e.g. the space (HIPPARCOS/TYCHO, KEPLER, GAIA, WISE etc.) and ground-based CCD (NSVS, ASAS, CRTS, SuperWASP etc.) and photographic (Harvard, Sonneberg, Odessa etc.) photometrical surveys.…
The study of fundamental properties (such as temperatures, radii, masses, and ages) and interior processes (such as convection and angular momentum transport) of stars has implications on various topics in astrophysics, ranging from the…
Adaptive Multilevel Splitting (AMS for short) is a generic Monte Carlo method for Markov processes that simulates rare events and estimates associated probabilities. Despite its practical efficiency, there are almost no theoretical results…
With current space-based missions it is now possible to obtain age-sensitive asteroseismic information for tens of thousands of red giants. This provides a promising opportunity to study the Galactic structure and evolution. We use…
Accelerator mass spectrometry (AMS) is a widely-used technique with multiple applications, including geology, molecular biology and archeology. In order to achieve a high dynamic range, AMS requires tandem accelerators and large magnets,…
The stellar inclination angle-the angle between the rotation axis of a star and our line of sight-provides valuable information in many different areas, from the characterisation of the geometry of exoplanetary and eclipsing binary systems,…
The large amount of spectra obtained during the epoch of extensive spectroscopic surveys of Galactic stars needs the development of automatic procedures to derive their atmospheric parameters and individual element abundances. Starting from…
Coupling stellar feedback to the evolution of individual stars, as opposed to averaging over the initial mass function (IMF), substantially improves the fidelity of galaxy formation simulations by capturing stochastic population effects.…
Asteroseismic methods offer a means to investigate stellar activity and activity cycles as well as to identify those properties of stars which are crucial for the operation of stellar dynamos. With data from CoRoT and \textit{Kepler},…
High precision asteroseismic data provide a unique opportunity to test input microphysics such as stellar opacities, chemical composition or equation of state. These tests are possible because pulsational frequencies as well as amplitudes…
Precise asteroseismic parameters allow one to quickly estimate radius and mass distributions for large samples of stars. A number of automated methods are available to calculate the frequency of maximum acoustic power ($\nu_{\mathrm{max}}$)…
Asteroseismology is a powerful tool that can precisely characterize the mass, radius, and other properties of field stars. However, our inability to properly model the near-surface layers of stars creates a frequency-dependent frequency…
As the next generation of large galaxy surveys come online, it is becoming increasingly important to develop and understand the machine learning tools that analyze big astronomical data. Neural networks are powerful and capable of probing…
This work investigates the problem of instance-level image retrieval re-ranking with the constraint of memory efficiency, ultimately aiming to limit memory usage to 1KB per image. Departing from the prevalent focus on performance…
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…