Related papers: High-precision interpolation of stellar atmosphere…
Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help…
Models of stellar spectra are necessary for interpreting light from individual stars, planets, integrated stellar populations, nebulae, and the interstellar medium. We provide a comprehensive and homogeneous collection of synthetic spectra…
The use of machine learning is becoming ubiquitous in astronomy, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a multi-parameter space is swept through in real time to find…
Resolving the phase structure of neutral hydrogen (HI) is crucial for understanding the life cycle of the interstellar medium (ISM). However, accurate measurements of HI temperature and density are limited by the availability of background…
The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution…
Atmospheric correction is a fundamental task in remote sensing because observations are taken either of the atmosphere or looking through the atmosphere. Atmospheric correction errors can significantly alter the spectral signature of the…
The interpretation of observations of atomic and molecular tracers in the galactic and extragalactic interstellar medium (ISM) requires comparisons with state-of-the-art astrophysical models to infer some physical conditions. Usually, ISM…
We analyze synthetic neutral hydrogen (HI) absorption and emission spectral lines from a high- resolution, three-dimensional hydrodynamical simulation to quantify how well observational methods recover the physical properties of…
We present a database of 45,000 atmospheric models (which will become 80,000 models by the end of the project) with stellar masses between 9 and 120 M$_{\odot}$, covering the region of the OB main sequence and W-R stars in the H-R diagram.…
Context. The emergence of mixed modes during the subgiant phase, whose frequencies are characterized by a fast evolution with age, can potentially enable a precise determination of stellar properties, a key goal for future missions like…
Point cloud upsampling aims to generate dense and uniformly distributed point sets from sparse point clouds. Existing point cloud upsampling methods typically approach the task as an interpolation problem. They achieve upsampling by…
The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because…
Many astrophysical applications require efficient yet reliable forecasts of stellar evolution tracks. One example is population synthesis, which generates forward predictions of models for comparison with observations. The majority of…
Lagrangian trajectory or particle dispersion models as well as semi-Lagrangian advection schemes require meteorological data such as wind, temperature and geopotential at the exact spatio-temporal locations of the particles that move…
We present a new method to retrieve molecular abundances and temperature profiles from exoplanet atmosphere photometry and spectroscopy. We run millions of 1D atmosphere models in order to cover the large range of allowed parameter space,…
We present the Stagger-grid, a comprehensive grid of time-dependent, 3D hydrodynamic model atmospheres for late-type stars with realistic treatment of radiative transfer, covering a wide range in stellar parameters. This grid of 3D models…
Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given…
Context: Traditional one-dimensional (1D) hydrostatic model atmospheres introduce systematic modelling errors into spectroscopic analyses of FGK-type stars. Aims: We present an updated version of the STAGGER-grid of 3D model atmospheres,…
Ensemble weather predictions typically show systematic errors that have to be corrected via post-processing. Even state-of-the-art post-processing methods based on neural networks often solely rely on location-specific predictors that…
We applied machine learning to the entire data history of ESO's High Accuracy Radial Velocity Planet Searcher (HARPS) instrument. Our primary goal was to recover the physical properties of the observed objects, with a secondary emphasis on…