Related papers: Structural Analysis of Molecular Clouds: Dendrogra…
How can we tell complex point clouds with different small scale characteristics apart, while disregarding global features? Can we find a suitable transformation of such data in a way that allows to discriminate between differences in this…
We present a census of molecular outflows across four active regions of star formation in the Perseus molecular cloud (NGC 1333, IC348/HH211, L1448 and L1455), totalling an area of over 1000 sq arcmin. This is one of the largest surveys of…
We leverage the 1 pc spatial resolution of the Leike et al. 2020 3D dust map to characterize the three-dimensional structure of nearby molecular clouds ($d \lesssim 400$ pc). We start by "skeletonizing" the clouds in 3D volume density space…
We present a self-consistent hydrodynamical simulation of a Milky Way-like galaxy, at the resolution of 0.05 pc. The model includes star formation and a new implementation of stellar feedback through photo-ionization, radiative pressure and…
'Big' high-dimensional data are commonly analyzed in low-dimensions, after performing a dimensionality-reduction step that inherently distorts the data structure. For the same purpose, clustering methods are also often used. These methods…
We present Data Release 6 of ThrUMMS, consisting of complete data cubes and various moments of line emission ($^{12}$CO, $^{13}$CO, C$^{18}$O) from molecular clouds, across 60$^{\circ}$$\times$2$^{\circ}$ of the Fourth Quadrant (4Q) of the…
Using the PHANGS-ALMA CO (2-1) survey, we characterize molecular gas properties on ${\sim}$100 pc scales across 102,778 independent sightlines in 70 nearby galaxies. This yields the best synthetic view of molecular gas properties on cloud…
(Abridged) Massive stars can determine the evolution of molecular clouds with their strong ultraviolet (UV) radiation fields. Moreover, UV radiation is relevant in setting the thermal gas pressure in star-forming clouds, whose influence can…
Unsupervised 3D keypoints estimation from Point Cloud Data (PCD) is a complex task, even more challenging when an object shape is deforming. As keypoints should be semantically and geometrically consistent across all the 3D frames - each…
In this article, we study curvature-like feature value of data sets in Euclidean spaces. First, we formulate such curvature functions with desirable properties under the manifold hypothesis. Then we make a test property for the validity of…
We study the relation between molecular gas and star formation in a volume-limited sample of 222 galaxies from the COLD GASS survey, with measurements of the CO(1-0) line from the IRAM 30m telescope. The galaxies are at redshifts…
"mdendro" is an R package that provides a comprehensive collection of linkage methods for agglomerative hierarchical clustering on a matrix of proximity data (distances or similarities), returning a multifurcated dendrogram or…
The universality of interstellar turbulence is examined from observed structure functions of 27 giant molecular clouds and Monte Carlo modeling. We show that the structure functions, dv=v0 l^gamma, derived from wide field imaging of CO…
In this paper we examine the factors that shape the distribution of molecular gas surface densities on the 150 pc scale across 67 morphologically diverse star-forming galaxies in the PHANGS-ALMA CO (2-1) survey. Dividing each galaxy into…
Pillars and globules are present in many high-mass star-forming regions, such as the Eagle nebula (M16) and the Rosette molecular cloud, and understanding their origin will help characterize triggered star formation. The formation…
Hierarchical clustering is one of the standard methods taught for identifying and exploring the underlying structures that may be present within a data set. Students are shown examples in which the dendrogram, a visual representation of the…
We consider the problem of analyzing the structure of spectroscopic cubes using unsupervised machine learning techniques. We propose representing the target's signal as a homogeneous set of volumes through an iterative algorithm that…
Stars form within molecular clouds, so characterizing the physical states of molecular clouds is key in understanding the process of star formation. Cloud structure and stability is frequently assessed using metrics including the virial…
Open cellular solids usually possess random microstructures that may contain a characteristic length scale, such as the cell size. This gives rise to size dependent mechanical properties where large systems behave differently from small…
The surface curvature of membranes, interfaces, and substrates plays a crucial role in shaping the self-assembly of particles adsorbed on these surfaces. However, little is known about the interplay between particle anisotropy and surface…