相关论文: Comparing the morphology of molecular clouds witho…
Recent studies of the nearest star-forming clouds of the Galaxy at submillimeter wavelengths with the Herschel Space Observatory have provided us with unprecedented images of the initial and boundary conditions of the star formation…
The physical properties of molecular clouds are often measured using spectral-line observations, which provide the only probes of the clouds' velocity structure. It is hard, though, to assess whether and to what extent intensity features in…
High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce.…
Morse complexes are gradient-based topological descriptors with close connections to Morse theory. They are widely applicable in scientific visualization as they serve as important abstractions for gaining insights into the topology of…
Deformable object manipulation (DOM) with point clouds has great potential as non-rigid 3D shapes can be measured without detecting and tracking image features. However, robotic shape control of deformable objects with point clouds is…
We have extensively mapped a sample of dense molecular clouds (L1512, TMC-1C, L1262, Per 7, L1389, L1251E) in lines of HC3N, CH3OH, SO and C^{18}O. We demonstrate that a high degree of chemical differentiation is present in all of the…
We compare the predictions of three independently developed semi-analytic galaxy formation models that are being used to aid in the interpretation of results from the CANDELS survey. These models are each applied to the same set of halo…
Weak gravitational lensing is a powerful probe of cosmology, with second-order shear statistics commonly used to constrain parameters such as the matter density $\Omega_\mathrm{m}$ and the clustering amplitude $S_8$. However, parameter…
In this paper, we introduce a novel method for comparing 3D point clouds, a critical task in various machine learning applications. By interpreting point clouds as samples from underlying probability density functions, the statistical…
We study the properties of giant molecular clouds (GMCs) from a smoothed particle hydrodynamics simulation of a portion of a spiral galaxy, modelled at high resolution, with robust representations of the physics of the interstellar medium.…
In this paper a LES model with Lagrangian representation of microphysics is used to simulate stratucumulus clouds in idealized 2D set-up based on the VOCALS observations. The general features of the cloud simulated by the model, such as…
We used CO (2-1) and CO (1-0) data cubes to identify molecular clouds and study their kinematics and dynamics in three nearby galaxies and the inner Milky Way. When observed at similar spatial and velocity resolutions, molecular clouds in…
We investigate the sensitivity of topological and traditional summary statistics to primordial non-Gaussianity (PNG) using two suites of simulations. First, we introduce a new simulation suite for PNG, PNG-pmwd, comprising more than…
We study the probabilistic behavior of persistence-based statistics and propose a novel nonparametric framework for detecting structural changes in high-dimensional random point clouds. We establish moment bounds and tightness results for…
A structural graph summary is a small graph representation that preserves structural information necessary for a given task. The summary is used instead of the original graph to complete the task faster. We introduce multi-view structural…
The sample of 566 molecular clouds identified in the CO(2--1) IRAM survey covering the disk of M~33 is explored in detail.The clouds were found using CPROPS and were subsequently catalogued in terms of their star-forming properties as…
We explore whether observed molecular clouds could include a substantial population of unbound clouds. Using simulations which include only turbulence and gravity, we are able to match observed relations and naturally reproduce the observed…
We examine the idea that diffuse and giant molecular clouds and their substructure form as density fluctuations induced by large scale interstellar turbulence. We do this by investigating the topology of various fields in realistic…
We present Point2SSM, a novel unsupervised learning approach for constructing correspondence-based statistical shape models (SSMs) directly from raw point clouds. SSM is crucial in clinical research, enabling population-level analysis of…
While branching network structures abound in nature, their objective analysis is more difficult than expected because existing quantitative methods often rely on the subjective judgment of branch structures. This problem is particularly…