Related papers: CMR exploration II -- filament identification with…
Observations suggest that star formation in filamentary molecular clouds occurs in a two-step process, with the formation of filaments preceding that of prestellar cores and stars. Here, we apply the gravo-turbulent fragmentation theory of…
The fragmentation of filaments in molecular clouds has attracted a lot of attention as there seems to be a relation between the evolution of filaments and star formation. The study of the fragmentation process has been motivated by simple…
Analysing the kinematics of filamentary molecular clouds is a crucial step towards understanding their role in the star formation process. Therefore, we study the kinematics of 283 filament candidates in the inner Galaxy, that were…
We present a method for accurately and precisely inferring photometric dust extinction towards stars at mid-to-high Galactic latitudes using probabilistic machine learning to model the colour-magnitude distribution of zero-extinction stars…
We present the results of a machine learning study to measure the dust content of galaxies observed with JWST at z > 6 through the use of trained neural networks based on high-resolution IllustrisTNG simulations. Dust is an important…
We perform ideal MHD high resolution AMR simulations with driven turbulence and self-gravity and find that long filamentary molecular clouds are formed at the converging locations of large-scale turbulence flows and the filaments are…
Polarization of starlight and thermal dust emission caused by aligned dust grains is a valuable tool to characterize magnetic fields (B-fields) and constrain dust properties. However, the physics of grain alignment is not fully understood.…
Dust is a major component of the interstellar medium. Through scattering, absorption and thermal re-emission, it can profoundly alter astrophysical observations. Models for dust composition and distribution are necessary to better…
We aim to understand the onset of cloud formation {and study the formation of} TiO$_2$-CCNs. The formation of (TiO$_2$)$_{\rm N}$ clusters as precursors to extrasolar cloud formation is modelled by two different methods in order to…
Machine learning is used to approximate density functionals. For the model problem of the kinetic energy of non-interacting fermions in 1d, mean absolute errors below 1 kcal/mol on test densities similar to the training set are reached with…
Emission from the interstellar medium can be a significant contaminant of measurements of the intensity and polarization of the cosmic microwave background (CMB). For planning CMB observations, and for optimizing foreground-cleaning…
The complete three-dimensional structure of the magnetic field within molecular clouds has eluded determination despite its high value in determining controlling factors in the star formation process, as it cannot be directly probed…
Diffusion MRI (dMRI) is a critical non-invasive technique to estimate fiber orientation distribution (FOD) for characterizing white matter integrity. Estimating FOD from single-shell low angular resolution dMRI (LAR-FOD) is limited by…
2D-based Industrial Anomaly Detection has been widely discussed, however, multimodal industrial anomaly detection based on 3D point clouds and RGB images still has many untouched fields. Existing multimodal industrial anomaly detection…
We utilize magnetohydrodynamic (MHD) simulations to develop a numerical model for GMC-GMC collisions between nearly magnetically critical clouds. The goal is to determine if, and under what circumstances, cloud collisions can cause…
The orientations of filamentary molecular clouds in the Gould Belt and their local ICM (inter-cloud media) magnetic fields are studied using near-infrared dust extinction maps and optical stellar polarimetry data. These filamentary clouds…
CO observations have been so far the best way to trace molecular gas in external galaxies, but at low metallicity the gas mass deduced could be largely underestimated. At present, the kinematic information of CO data cubes are used to…
Context. Using observations to deduce dust properties, grain size distribution, and physical conditions in molecular clouds is a highly degenerate problem. Aims. The coreshine phenomenon, a scattering process at 3.6 and 4.5 $\mu$m that…
Clouds are a very important factor in the availability of optical remote sensing images. Recently, deep learning-based cloud detection methods have surpassed classical methods based on rules and physical models of clouds. However, most of…
We acquired 450 {\mu}m and 850 {\mu}m dust continuum polarization observations toward the inner region of the Central Molecular Zone (CMZ) as part of the B-Fields In Star-Forming Region Observations (BISTRO) survey using the POL-2…