Related papers: Assessing the Performance of a Machine Learning Al…
One of the major challenges we face is how to quickly and accurately create the three-dimensional (3D) density distributions of interstellar dust in the Milky Way using extinction and distance measurements of large samples of stars. In this…
We present a self-consistent three-dimensional Monte-Carlo radiative transfer model of the stellar and dust emission in the Milky-Way, and have computed synthetic observations of the 3.6 to 100 microns emission in the Galactic mid-plane. In…
Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each…
When dense granular gases are continuously excited under microgravity conditions, spatial inhomogeneities of the particle number density can emerge. A significant share of particles may collect in strongly overpopulated regions, called…
Machine learning (ML) has become a key tool in astronomy, driving advancements in the analysis and interpretation of complex datasets from observations. This article reviews the application of ML techniques in the identification and…
We present a new analysis of the properties of star-forming cores in the Perseus molecular cloud, identified in SCUBA 850 micron data. Our goal is to determine which core properties can be robustly identified and which depend on the…
Binding energies (BEs) of adsorbates on interstellar dust grains critically control adsorption, desorption, diffusion, and surface reactivity, and therefore strongly influence astrochemical models of star- and planet-forming regions. While…
Substellar objects have extremely long life-spans. The cosmological consequence for older objects are low abundances of heavy elements, which results in a wide distribution of objects over metallicity, hence over age. Within their cool…
Context: Bouncing collisions of dust aggregates within the protoplanetary may have a significant impact on the growth process of planetesimals. Yet, the conditions that result in bouncing are not very well understood. Existing simulations…
Since the discovery of brown dwarfs in 1994, and the discovery of dust cloud formation in the latest Very Low Mass Stars (VLMs) and Brown Dwarfs (BDs) in 1996, the most important challenge in modeling their atmospheres as become the…
Stars form within dense cores composed of both gas and dust within molecular clouds. However, despite the crucial role that dust plays in the star formation process, its dynamics is frequently overlooked, with the common assumption being a…
We seek to understand the evolution of Wolf-Rayet central stars by comparing the diffuse X-ray emission from their wind-blown bubbles with that from their hydrogen-rich counterparts with predictions from hydrodynamical models. We simulate…
Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the…
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…
Stars, and collections of stars, encode rich signatures of stellar physics and galaxy evolution. With properties influenced by both their environment and intrinsic nature, stars retain information about astrophysical phenomena that are not…
In a companion paper, we develop a theory for the evolution of stellar wind driven bubbles in dense, turbulent clouds. This theory proposes that turbulent mixing at a fractal bubble-shell interface leads to highly efficient cooling, in…
Dust offers a unique probe of the interstellar medium (ISM) across multiple size, density, and temperature scales. Dust is detected in outflows of evolved stars, star-forming molecular clouds, planet-forming disks, and even in galaxies at…
Dust formation in brown dwarf atmospheres is studied by utilising a model for driven turbulence in the mesoscopic scale regime. We apply a pseudo-spectral method where waves are created and superimposed within a limited wavenumber interval.…
In this paper, we study the effect of MHD turbulence on the dynamics of dust particles in protoplanetary disks. We vary the size of the particles and relate the dust evolution to the turbulent velocity fluctuations. We performed numerical…
We present a new catalogue of 5,106 infrared bubbles created through visual classification via the online citizen science website 'The Milky Way Project'. Bubbles in the new catalogue have been independently measured by at least 5…