The Perils of Clumpfind: The Mass Spectrum of Sub-structures in Molecular Clouds

We study the mass spectrum of sub-structures in the Perseus Molecular Cloud Complex traced by 13CO (1-0), finding that $dN/dM\propto M^{-2.4}$ for the standard Clumpfind parameters. This result does not agree with the classical $dN/dM\propto M^{-1.6}$. To understand this discrepancy we study the robustness of the mass spectrum derived using the Clumpfind algorithm. Both 2D and 3D Clumpfind versions are tested, using 850 $\mu$m dust emission and 13CO spectral-line observations of Perseus, respectively. The effect of varying threshold is not important, but varying stepsize produces a different effect for 2D and 3D cases. In the 2D case, where emission is relatively isolated (associated with only the densest peaks in the cloud), the mass spectrum variability is negligible compared to the mass function fit uncertainties. In the 3D case, however, where the 13CO emission traces the bulk of the molecular cloud, the number of clumps and the derived mass spectrum are highly correlated with the stepsize used. The distinction between "2D" and "3D" here is more importantly also a distinction between "sparse" and "crowded" emission. In any "crowded" case, Clumpfind should not be used blindly to derive mass functions. Clumpfind's output in the "crowded" case can still offer a statistical description of emission useful in inter-comparisons, but the clump-list should not be treated as a robust region decomposition suitable to generate a physically-meaningful mass function. We conclude that the 13CO mass spectrum depends on the observations resolution, due to the hierarchical structure of MC.Comment: 5 pages, 3 figures. Accepted for publication in ApJ Letter

The Dynamics of Dense Cores in the Perseus Molecular Cloud II: The Relationship Between Dense Cores and the Cloud

We utilize the extensive datasets available for the Perseus molecular cloud to analyze the relationship between the kinematics of small-scale dense cores and the larger structures in which they are embedded. The kinematic measures presented here can be used in conjunction with those discussed in our previous work as strong observational constraints that numerical simulations (or analytic models) of star formation should match. We find that dense cores have small motions with respect to the 13CO gas, about one third of the 13CO velocity dispersion along the same line of sight. Within each extinction region, the core-to-core velocity dispersion is about half of the total (13CO) velocity dispersion seen in the region. Large-scale velocity gradients account for roughly half of the total velocity dispersion in each region, similar to what is predicted from large-scale turbulent modes following a power spectrum of P(k) ~ k^{-4}.Comment: Accepted for publication in ApJ. 47 pages (preprint format), 20 figures, 5 table

A^2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes

Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies. Methods have evolved from manual construction by structural biologists to perform 6D translation-rotation searching, which is extremely compute-intensive. In this paper, we propose a learning-based method and formulate this problem as a vision-inspired 3D detection and pose estimation task. We develop a deep learning framework for amino acid determination in a 3D Cryo-EM density volume. We also design a sequence-guided Monte Carlo Tree Search (MCTS) to thread over the candidate amino acids to form the molecular structure. This framework achieves 91% coverage on our newly proposed dataset and takes only a few minutes for a typical structure with a thousand amino acids. Our method is hundreds of times faster and several times more accurate than existing automated solutions without any human intervention.Comment: 8 pages, 5 figures, 4 table

The GALFA-HI Compact Cloud Catalog

We present a catalog of 1964 isolated, compact neutral hydrogen clouds from the Galactic Arecibo L-Band Feed Array Survey Data Release One (GALFA-HI DR1). The clouds were identified by a custom machine-vision algorithm utilizing Difference of Gaussian kernels to search for clouds smaller than 20'. The clouds have velocities typically between |VLSR| = 20-400 km/s, linewidths of 2.5-35 km/s, and column densities ranging from 1 - 35 x 10^18 cm^-2. The distances to the clouds in this catalog may cover several orders of magnitude, so the masses may range from less than a Solar mass for clouds within the Galactic disc, to greater than 10^4 Solar Masses for HVCs at the tip of the Magellanic Stream. To search for trends, we separate the catalog into five populations based on position, velocity, and linewidth: high velocity clouds (HVCs); galaxy candidates; cold low velocity clouds (LVCs); warm, low positive-velocity clouds in the third Galactic Quadrant; and the remaining warm LVCs. The observed HVCs are found to be associated with previously-identified HVC complexes. We do not observe a large population of isolated clouds at high velocities as some models predict. We see evidence for distinct histories at low velocities in detecting populations of clouds corotating with the Galactic disc and a set of clouds that is not corotating.Comment: 34 Pages, 9 Figures, published in ApJ (2012, ApJ, 758, 44), this version has the corrected fluxes and corresponding flux histogram and masse

Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean

This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features

From Multiview Image Curves to 3D Drawings

Reconstructing 3D scenes from multiple views has made impressive strides in recent years, chiefly by correlating isolated feature points, intensity patterns, or curvilinear structures. In the general setting - without controlled acquisition, abundant texture, curves and surfaces following specific models or limiting scene complexity - most methods produce unorganized point clouds, meshes, or voxel representations, with some exceptions producing unorganized clouds of 3D curve fragments. Ideally, many applications require structured representations of curves, surfaces and their spatial relationships. This paper presents a step in this direction by formulating an approach that combines 2D image curves into a collection of 3D curves, with topological connectivity between them represented as a 3D graph. This results in a 3D drawing, which is complementary to surface representations in the same sense as a 3D scaffold complements a tent taut over it. We evaluate our results against truth on synthetic and real datasets.Comment: Expanded ECCV 2016 version with tweaked figures and including an overview of the supplementary material available at multiview-3d-drawing.sourceforge.ne