Related papers: SMART - a computer program for modelling stellar a…
Probabilistic programming makes it easy to represent a probabilistic model as a program. Building an individual model, however, is only one step of probabilistic modeling. The broader challenge of probabilistic modeling is in understanding…
We present a verification of a computational model, developed at the Los Alamos National Laboratory (LANL) for simulating radiation transfer in X-ray bursting neutron star atmospheres. We tested a baseline case and demonstrated strong…
Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes, and randomly sampled spatial processes. Joint analysis of such collections of observations is clearly…
The plethora of spectra of OB-type stars in observatory archives and the much larger numbers to come from the WEAVE and 4MOST spectroscopic facilities require efficient, but also accurate and precise methods for (semi)automatic quantitative…
We construct partially ionized hydrogen atmosphere models for magnetized neutron stars in radiative equilibrium with fixed surface fields between B=10^12 and 2x10^13 G and effective temperatures logT_eff=5.5-6.8, as well as with surface B…
We present a new model of the microwave sky in polarization that can be used to simulate data from CMB polarization experiments. We exploit the most recent results from the Planck satellite to provide an accurate description of the diffuse…
Smart matter consists of many sensors, computers and actuators embedded within materials. These microelectromechanical systems allow properties of the materials to be adjusted under program control. In this context, we study the behavior of…
We present a code for generating synthetic SEDs and intensity maps from Smoothed Particle Hydrodynamics simulation snapshots. The code is based on the Lucy (1999) Monte Carlo Radiative Transfer method, i.e. it follows discrete luminosity…
We present a distributed system for storage, processing, three-dimensional visualisation and basic analysis of data from Earth-observing satellites. The database and the server have been designed for high performance and scalability,…
A promising approach to improve climate-model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data-driven. However, neural networks (NNs) often lead…
Raman spectroscopy is an important characterization tool with diverse applications in many areas of research. We propose a machine learning method for predicting polarizabilities with the goal of providing Raman spectra from molecular…
Simple spherical, non-rotating stellar models are inadequate when describing real stars in the limit of very fast rotation: Both the observable spectrum and the geometrical shape of the star deviate strongly from simple models. We attempt…
Simulations of dense stellar systems currently face two major hurdles, one astrophysical and one computational. The astrophysical problem lies in the fact that several major stages in binary evolution, such as common envelope evolution, are…
Context. Spectroscopy of exoplanet atmospheres at high resolving powers is rapidly gaining popularity to measure the presence of atomic and molecular species. While this technique is robust against contaminant absorption in the Earth's…
Environmental monitoring is crucial to our understanding of climate change, biodiversity loss and pollution. The availability of large-scale spatio-temporal data from sources such as sensors and satellites allows us to develop sophisticated…
We present Scalable Multi-Agent Realistic Testbed (SMART), a realistic and efficient software tool for evaluating Multi-Agent Path Finding (MAPF) algorithms. MAPF focuses on planning collision-free paths for a group of robots. While…
The correct interpretation of the large amount of complex data from next-generation (in particular, space-based) observational facilities requires a very strong theoretical underpinning. One can thus predict that in the near future the use…
Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, i.e., solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set…
Since about 25 years ago work has been dedicated to the development of hydrodynamical model atmospheres for cool stars (of A to T spectral type). Despite their obviously sounder physical foundation in comparison with standard hydrostatic…
We compute model atmospheres and emergent spectra for low field (B<10^10 G) neutron stars, using new opacity and equation of state data from the OPAL project. These computations, incorporating improved treatments of flux transport and…