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Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…
Existing point cloud representation learning methods primarily rely on data-driven strategies to extract geometric information from large amounts of scattered data. However, most methods focus solely on the spatial distribution features of…
We study the physical properties and 3D distribution of molecular clouds (MCs) toward the Cygnus region using the MWISP CO survey and Gaia DR3 data. Based on Gaussian decomposition and clustering for $\rm ^{13}CO$ lines, over 70% of the…
Hierarchical clustering is a common algorithm in data analysis. It is unique among many clustering algorithms in that it draws dendrograms based on the distance of data under a certain metric, and group them. It is widely used in all areas…
We provide a numerical platform for the analysis of particle shape and topology effect on the macroscopic behavior of granular media. We work within a Discrete Element Method (DEM) framework and apply a peridynamic model for deformable…
Modern observations of the interstellar medium (ISM) in galaxies detect a variety of atomic and molecular species. The goal is to connect these observations to the astrochemical properties of the ISM. 3D hydro-chemical simulations attempt…
We present the results of ALMA-ACA 7 m-array observations in $^{12}$CO($J=2-1$), $^{13}$CO($J=2-1$), and C$^{18}$O($J=2-1$) line emission toward the molecular-gas disk in the Local Group spiral galaxy M33 at an angular resolution of 7".31…
Superresolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer scale. The ability to monitor microgels response to temperature…
We use the COMPLETE Survey's observations of the Perseus star-forming region to assess and intercompare three methods for measuring column density in molecular clouds: extinction mapping (NIR); thermal emission mapping (FIR); and mapping…
Understanding the molecular content of galaxies is a critical problem in star formation and galactic evolution. Here we present a new method, based on a Stromgren-type analysis, to calculate the amount of HI that surrounds a molecular cloud…
We describe a morphological imprint of magnetization found when considering the relative orientation of the magnetic field direction with respect to the density structures in simulated turbulent molecular clouds. This imprint was found…
We discuss the systematic effects arising from the cosmological redshift-space (geometric) distortion on the statistical analysis of isodensity contour using high-redshift catalogs. Especially, we present a simple theoretical model for…
We use the distance probability density function (DPDF) formalism of Ellsworth-Bowers et al. (2013, 2015) to derive physical properties for the collection of 1,710 Bolocam Galactic Plane Survey (BGPS) version 2 sources with well-constrained…
We report the results of a new large scale survey of the Orion-Monoceros complex of molecular clouds made in the J = 1->0 line of CO with the Harvard-Smithsonian 1.2m millimetre-wave telescope. The survey consists of 52,288 uniformly spaced…
HOLODEC, an airborne cloud particle imager, captures holographic images of a fixed volume of cloud to characterize the types and sizes of cloud particles, such as water droplets and ice crystals. Cloud particle properties include position,…
The structure of molecular clouds (MCs) holds important clues on the physical processes that lead to their formation and subsequent evolution. While it is well established that turbulence imprints a self-similar structure to the clouds,…
We report on high-angular resolution observations of a dense core in the cirrus cloud MCLD123.5+24.9 obtained with the PdB and the OVRO interferometers. Our maps show substructures down to the scale of the beam (~ 1000 AU). The chosen…
In this paper, we review some of the properties of dense molecular cloud cores. The results presented here rely on three-dimensional numerical simulations of isothermal, magnetized, turbulent, and self-gravitating molecular clouds (MCs) in…
Describing the deviation of a real structure from a hypothetical higher-symmetry ideal can be a powerful tool to understand and interpret phase transitions. Here we introduce a simple yet effective metric that quantifies the degree of unit…
Within scientific and real life problems, classification is a typical case of extremely complex tasks in data-driven scenarios, especially if approached with traditional techniques. Machine Learning supervised and unsupervised paradigms,…