arXiv subjects

Ji Yang

Publications and source records attributed to Ji Yang.

At least 55 records · Page 3Linked to original sources

arXiv2023

Molecular Clouds in the Galactic Plane from $l$ = [59.75$^\circ$, 74.75$^\circ$] and $b$ = [$-$5.25$^\circ$, +5.25$^\circ$]

In this paper we present the distribution of molecular gas in the Milky Way Galactic plane from $l$ = [59.75, 74.75]$^{\circ}$ and $b$ = [${-}$5.25, +5.25]$^{\circ}$, using the MWISP $^{12}$CO/$^{13}$CO/$\rm {C}^{18}{O}$ emission line data. The molecular gas in this region can be mainly attributed to the Local spur, Local arm, Perseus arm, and Outer arm. Statistics of the physical properties of the molecular gas in each arm, such as excitation temperature, optical depth, and column density, are presented. Using the DBSCAN algorithm, we identified 15 extremely distant molecular clouds with kinematic distances of 14.72$-$17.77 kpc and masses of 363$-$520 M$_{\odot}$, which we find could be part of the Outer Scutum-Centaurus (OSC) arm identified by \cite{2011ApJ...734L..24D} and \cite{2015ApJ...798L..27S}. It is also possible that, 12 of these 15 extremely distant molecular clouds constitute an independent structure between the Outer and the OSC arms or a spur. There exist two Gaussian components in the vertical distribution of the molecular gas in the Perseus spiral arm. These two Gaussian components correspond to two giant filaments parallel to the Galactic plane. We find an upward warping of the molecular gas in the Outer spiral arm with a displacement of around 270 pc with respect to the Galactic mid-plane.

astro-ph.GA↗

arXiv2023

In search for infalling clumps in molecular clouds -- A catalogue of CO blue-profiles

We have started a systematic survey of molecular clumps with infall motions to study the very early phase of star formation. Our first step is to utilize the data products by MWISP to make an unbiased survey for blue asymmetric line profiles of CO isotopical molecules. Within a total area of $\sim$ 2400 square degrees nearby the Galactic plane, we have found 3533 candidates showing blue-profiles, in which 3329 are selected from the $^{12}$CO&$^{13}$CO pair and 204 are from the $^{13}$CO&C$^{18}$O pair. Exploration of the parametric spaces suggests our samples are in the cold phase with relatively high column densities ready for star formation. Analysis of the spatial distribution of our samples suggests that they exist virtually in all major components of the Galaxy. The vertical distribution suggest that the sources are located mainly in the thick disk of $\sim$ 85 parsec, but still a small part are located far beyond Galactic midplane. Our follow-up observation indicates that these candidates are a good sample to start a search for infall motions, and to study the condition of very early phase of star formation.

astro-ph.GA↗

arXiv2023

On the Spatial Distribution of $^{13}$CO Structures within $^{12}$CO Molecular Clouds

We look into the 2851 $^{12}$CO molecular clouds harboring $^{13}$CO structures to reveal the distribution of the projected angular separations and radial velocity separations between their internal $^{13}$CO structures. The projected angular separations are determined using the minimal spanning tree algorithm. We find that $\sim$ 50$\%$ of the angular separations fall in a narrow range of $\sim$ 3 - 7 arcmin with a median of $\sim$ 5 arcmin, and the corresponding radial velocity separations mainly range from $\sim$ 0.3 km s$^{-1}$ to 2.5 km s$^{-1}$. The mean and standard deviation of the angular separations of the internal $^{13}$CO structures within $^{12}$CO clouds appear to be universal, independent of the $^{12}$CO cloud angular areas and the counts of their internal $^{13}$CO structures. We also reveal a scaling relation between the $^{12}$CO cloud angular area and its harbored $^{13}$CO structure count. These results suggest there is a preferred angular separation between $^{13}$CO structures in these $^{12}$CO clouds, considering the distance effects. According to that, we propose an alternative picture for the assembly and destruction of molecular clouds: there is a fundamental separation for the internal structures of molecular clouds, the build-up and destruction of molecular clouds proceeds under this fundamental unit.

astro-ph.GA↗

arXiv2022

The Cassiopeia Filament: A Blown Spur of the Local Arm

We present wide-field and high-sensitivity CO(1-0) molecular line observations toward the Cassiopeia region, using the 13.7m millimeter telescope of the Purple Mountain Observatory (PMO). The CO observations reveal a large-scale highly filamentary molecular cloud within the Galactic region of 132\fdg0\,$\geq$\,$l$\,$\geq$\,122\fdg0 and -1\fdg0\,$\leq$\,$b$\,$\leq$\,3\fdg0 and the velocity range from approximately +1 to +4 km/s. The measured length of the large-scale filament, referred to as the Cassiopeia Filament, is about 390 pc. The observed properties of the Cassiopeia Filament, such as length, column density, and velocity gradient, are consistent with those synthetic large-scale filaments in the inter-arm regions. Based on its observed properties and location on the Galactic plane, we suggest that the Cassiopeia Filament is a spur of the Local arm, which is formed due to the galactic shear. The western end of the Cassiopeia Filament shows a giant arc-like molecular gas shell, which is extending in the velocity range from roughly -1 to +7 km/s. Finger-like structures, with systematic velocity gradients, are detected in the shell. The CO kinematics suggest that the large shell is expanding at a velocity of ~6.5 km/s. Both the shell and finger-like structures outline a giant bubble with a radius of ~16 pc, which is likely produced by stellar wind from the progenitor star of a supernova remnant. The observed spectral linewidths suggest that the whole Cassiopeia Filament was quiescent initially until its west part was blown by stellar wind and became supersonically turbulent.

astro-ph.GA↗

arXiv2022

CO(J = 1-0) Observations toward the Filamentary Cloud in the Galactic Region of $153.60^{\circ} \leqslant l \leqslant 156.50^{\circ}$ and $1.85^{\circ} \leqslant b \leqslant 3.50^{\circ}$

We present observations of $J$=1-0 transition lines of ${ }^{12} \mathrm{CO}$, ${ }^{13} \mathrm{CO}$, and $\mathrm{C}^{18} \mathrm{O}$ towards the Galactic region of $153.60^{\circ} \leqslant l \leqslant 156.50^{\circ}$ and $1.85^{\circ} \leqslant b \leqslant 3.50^{\circ}$, using the Purple Mountain Observatory (PMO) 13.7 m millimeter telescope. Based on the \tht data, one main filament and five sub-filaments are found together as a network structure in the velocity interval of $[-42.5, -30.0] \,\mathrm{km} \mathrm{\,s}^{-1}$. The kinematic distance of this molecular cloud (MC) is estimated to be $\sim4.5 \mathrm{\,kpc}$. The median length, width, excitation temperature, line mass of these filaments are $\sim49 \mathrm{\,pc}$, $\sim2.9 \mathrm{\,pc}$, $\sim8.9 \mathrm{\,K}$, and $\sim39 \,M_{\odot} \mathrm{pc}^{-1}$, respectively. The velocity structures along these filaments exhibit oscillatory patterns, which are likely caused by the fragmentation or accretion process along these filaments. The maximum accretion rate is estimated to be as high as $\sim700 \,M_{\odot} \mathrm{pc}^{-1}$. A total of $\sim162$ \tht clumps and $\sim 103$ young stellar objects (YSOs) are identified in this region. Most of the clumps are in gravitationally bound states. Three \hii regions (G154.359+2.606, SH2-211, SH2-212) are found to be located in the apexes of the filaments. Intense star forming activities are found along the entire filamentary cloud. The observed results may help us to better understand the link between filaments and massive star formation.

astro-ph.GA↗

arXiv2022

Object Wake-up: 3D Object Rigging from a Single Image

Given a single image of a general object such as a chair, could we also restore its articulated 3D shape similar to human modeling, so as to animate its plausible articulations and diverse motions? This is an interesting new question that may have numerous downstream augmented reality and virtual reality applications. Comparing with previous efforts on object manipulation, our work goes beyond 2D manipulation and rigid deformation, and involves articulated manipulation. To achieve this goal, we propose an automated approach to build such 3D generic objects from single images and embed articulated skeletons in them. Specifically, our framework starts by reconstructing the 3D object from an input image. Afterwards, to extract skeletons for generic 3D objects, we develop a novel skeleton prediction method with a multi-head structure for skeleton probability field estimation by utilizing the deep implicit functions. A dataset of generic 3D objects with ground-truth annotated skeletons is collected. Empirically our approach is demonstrated with satisfactory performance on public datasets as well as our in-house dataset; our results surpass those of the state-of-the-arts by a noticeable margin on both 3D reconstruction and skeleton prediction.

cs.CV↗

arXiv2022

Molecular Gas Structures traced by $^{13}$CO Emission in the 18,190 $^{12}$CO Molecular Clouds from the MWISP Survey

After the morphological classification of the 18,190 $^{12}$CO molecular clouds, we further investigate the properties of their internal molecular gas structures traced by the $^{13}$CO($J=$ 1$-$0) line emissions. Using three different methods to extract the $^{13}$CO gas structures within each $^{12}$CO cloud, we find that $\sim$ 15$\%$ of $^{12}$CO clouds (2851) have $^{13}$CO gas structures and these $^{12}$CO clouds contribute about 93$\%$ of the total integrated flux of $^{12}$CO emission. In each of 2851 $^{12}$CO clouds with $^{13}$CO gas structures, the $^{13}$CO emission area generally does not exceed 70$\%$ of the $^{12}$CO emission area, and the $^{13}$CO integrated flux does not exceed 20$\%$ of the $^{12}$CO integrated flux. We reveal a strong correlation between the velocity-integrated intensities of $^{12}$CO lines and those of $^{13}$CO lines in both $^{12}$CO and $^{13}$CO emission regions. This indicates the H$_{2}$ column densities of molecular clouds are crucial for the $^{13}$CO lines emission. After linking the $^{13}$CO structure detection rates of the 18,190 $^{12}$CO molecular clouds to their morphologies, i.e. nonfilaments and filaments, we find that the $^{13}$CO gas structures are primarily detected in the $^{12}$CO clouds with filamentary morphologies. Moreover, these filaments tend to harbor more than one $^{13}$CO structure. That demonstrates filaments not only have larger spatial scales, but also have more molecular gas structures traced by $^{13}$CO lines, i.e. the local gas density enhancements. Our results favor the turbulent compression scenario for filament formation, in which dynamical compression of turbulent flows induces the local density enhancements. The nonfilaments tend to be in the low-pressure and quiescent turbulent environments of the diffuse interstellar medium.

astro-ph.GA↗

arXiv2022

Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms

In this work, we investigate the observational and algorithmic effects on molecular cloud samples identified from position-position-velocity (PPV) space. By smoothing and cutting off the high quality data of the Milky Way Imaging Scroll Painting (MWISP) survey, we extract various molecular cloud samples from those altered data with the DBSCAN (density-based spatial clustering of applications with noise) algorithm. Those molecular cloud samples are subsequently used to gauge the significance of sensitivity, angular/velocity resolution, and DBSCAN parameters. Two additional surveys, the FCRAO Outer Galaxy Survey (OGS) and the CfA-Chile 1.2 m complete CO (CfA-Chile) survey, are used to verify the MWISP results. We found that molecular cloud catalogs are not unique and the boundary and therefore the number shows strong variation with angular resolution and sensitivity. At low angular resolution (large beam sizes), molecular clouds merge together in PPV space, while low sensitivity (high cutoffs) misses small faint molecular clouds and takes bright parts of large molecular clouds as single ones. At high angular resolution and sensitivity, giant molecular clouds (GMCs) are resolved into individual clouds, and their diffuse components are also revealed. Consequently, GMCs are more appropriately interpreted as clusters or aggregates of molecular clouds, i.e., GMCs represent molecular cloud samples themselves.

astro-ph.GA↗

arXiv2022

Gas Column Density Distribution of Molecular Clouds in the Third Quadrant of the Milky Way

We have obtained column density maps for an unbiased sample of 120 molecular clouds in the third quadrant of the Milky Way mid-plane (b$\le |5|^{\circ}$) within the galactic longitude range from 195$^{\circ}$ to 225$^{\circ}$, using the high sensitivity $^{12}$CO and $^{13}$CO ($J=1-0$) data from the Milky Way Imaging Scroll Painting (MWISP) project. The probability density functions of the molecular hydrogen column density of the clouds, N-PDFs, are fitted with both log-normal (LN) function and log-normal plus power-law (LN+PL) function. The molecular clouds are classified into three categories according to their shapes of N-PDFs, i.e., LN, LN+PL, and UN (unclear), respectively. About 72\% of the molecular clouds fall into the LN category, while 18\% and 10\% into the LN+PL and UN categories, respectively. A power-law scaling relation, $σ_s\propto N_{H_2}^{0.44}$, exists between the width of the N-PDF, $σ_s$, and the average column density, $N_{H_2}$, of the molecular clouds. However, $σ_s$ shows no correlation with the mass of the clouds. A correlation is found between the dispersion of normalized column density, $σ_{N/\rm }$, and the sonic Mach number, $\mathcal{M}$, of molecular clouds. Overall, as predicted by numerical simulations, the N-PDFs of the molecular clouds with active star formation activity tend to have N-PDFs with power-law high-density tails.

astro-ph.GA↗

arXiv2022

CO Emission Delineating the Interface between the Milky Way Nuclear Wind Cavity and the Gaseous Disk

Based on the MWISP survey, we study high-z CO emission toward the tangent points, in which the distances of the molecular clouds (MCs) are well determined. In the region of l=12-26 deg and |b|<5.1 deg, a total of 321 MCs with |z|> 110 pc are identified, of which nearly 30 extreme high-z MCs (EHMCs at |z|> 260 pc) are concentrated in a narrow region of R_GC=2.6-3.1 kpc. The EHMC concentrations, together with other high-z MCs at R_GC=2.3-2.6 kpc, constitute molecular crater-wall structures surrounding the edges of the HI voids that are physically associated with the Fermi bubbles. Intriguingly, some large high-z MCs, which lie in the crater walls above and below the Galactic plane, show cometary structures with the head toward the plane, favouring the scenario that the entrained molecular gas moves with the multi-phase flows from the plane to the high-z regions. We suggest that the Milky Way nuclear wind has a significant impact on the Galactic gaseous disk. The powerful nuclear wind at ~3-6 Myr ago is likely responsible for the observational features, (1) the enhanced CO gas lying in the edges of the HI voids, (2) the deficiency of atomic and molecular gas within R_GC<3 kpc, (3) the possible connection between the EHMC concentrations and the 3-kpc arm, and (4) the elongated high-z MCs with the tail pointing away from the Galactic plane.

astro-ph.GA↗

arXiv2021

Preliminary analysis on the noise characteristics of MWISP data

Noise is a significant part within a millimeter-wave molecular line datacube. Analyzing the noise improves our understanding of noise characteristics, and further contributes to scientific discoveries. We measure the noise level of a single datacube from MWISP and perform statistical analyses. We identified major factors which increase the noise level of a single datacube, including bad channels, edge effects, baseline distortion and line contamination. Cleaning algorithms are applied to remove or reduce these noise components. As a result, we obtained the cleaned datacube in which noise follows a positively skewed normal distribution. We further analyzed the noise structure distribution of a 3D mosaicked datacube in the range l = 40°.7 to 43°.3 and b = -2°.3 to 0°.3 and found that noise in the final mosaicked datacube is mainly characterized by noise fluctuation among the cells.

astro-ph.GA↗

arXiv2021

Efficient FPGA-based ECDSA Verification Engine for Permissioned Blockchains

As enterprises embrace blockchain technology, many real-world applications have been developed and deployed using permissioned blockchain platforms (access to network is controlled and given to only nodes with known identities). Such blockchain platforms heavily depend on cryptography to provide a layer of trust within the network, thus verification of cryptographic signatures often becomes the bottleneck. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most commonly used cryptographic scheme in permissioned blockchains. In this paper, we propose an efficient implementation of ECDSA signature verification on an FPGA, in order to improve the performance of permissioned blockchains that aim to use FPGA-based hardware accelerators. We propose several optimizations for modular arithmetic (e.g., custom multipliers and fast modular reduction) and point arithmetic (e.g., reduced number of point double and addition operations, and optimal width NAF representation). Based on these optimized modular and point arithmetic modules, we propose an ECDSA verification engine that can be used by any application for fast verification of ECDSA signatures. We further optimize our ECDSA verification engine for Hyperledger Fabric (one of the most widely used permissioned blockchain platforms) by moving carefully selected operations to a precomputation block, thus simplifying the critical path of ECDSA signature verification. From our implementation on Xilinx Alveo U250 accelerator board with target frequency of 250MHz, our ECDSA verification engine can perform a single verification in $760μs$ resulting in a throughput of 1,315 verifications per second, which is ~2.5x faster than state-of-the-art FPGA-based implementations. Our Hyperledger Fabric-specific ECDSA engine can perform a single verification in $368μs$ with a throughput of 2,717 verifications per second.

cs.CR↗

arXiv2021

3D Pose Estimation and Future Motion Prediction from 2D Images

This paper considers to jointly tackle the highly correlated tasks of estimating 3D human body poses and predicting future 3D motions from RGB image sequences. Based on Lie algebra pose representation, a novel self-projection mechanism is proposed that naturally preserves human motion kinematics. This is further facilitated by a sequence-to-sequence multi-task architecture based on an encoder-decoder topology, which enables us to tap into the common ground shared by both tasks. Finally, a global refinement module is proposed to boost the performance of our framework. The effectiveness of our approach, called PoseMoNet, is demonstrated by ablation tests and empirical evaluations on Human3.6M and HumanEva-I benchmark, where competitive performance is obtained comparing to the state-of-the-arts.

cs.CV↗

arXiv2021

Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry

The empirical results suggest that the learnability of a neural network is directly related to its size. To mathematically prove this, we borrow a tool in topological algebra: Betti numbers to measure the topological geometric complexity of input data and the neural network. By characterizing the expressive capacity of a neural network with its topological complexity, we conduct a thorough analysis and show that the network's expressive capacity is limited by the scale of its layers. Further, we derive the upper bounds of the Betti numbers on each layer within the network. As a result, the problem of architecture selection of a neural network is transformed to determining the scale of the network that can represent the input data complexity. With the presented results, the architecture selection of a fully connected network boils down to choosing a suitable size of the network such that it equips the Betti numbers that are not smaller than the Betti numbers of the input data. We perform the experiments on a real-world dataset MNIST and the results verify our analysis and conclusion. The code is publicly available.

cs.LG↗

arXiv2021

Feedback from $γ$~Cassiopeiae: Large Expanding Cavity, Accelerating Cometary Globules, and Peculiar X-ray Emission

We present wide-field multi-wavelength observations of $γ$ Cassiopeiae (or $γ$~Cas for short) in order to study its feedback toward the interstellar environment. A large expanding cavity is discovered toward $γ$~Cas in the neutral hydrogen (HI) images at a systemic velocity of about -10 km/s. The measured dimension of the cavity is roughly 2.0 deg $\times$ 1.4 deg (or 6.0 pc $\times$ 4.2 pc at a distance of 168 pc), while the expansion velocity is about 5.0$\pm$0.5 km/s. The CO observations reveal systematic velocity gradients in IC63 (about 20 km/s/pc) and IC59 (about 30 km/s/pc), two cometary globules illuminated by $γ$~Cas, proving fast acceleration of the globules under stellar radiation pressure. The gas kinematics indicate that the cavity is opened by strong stellar wind, which has high potential to lead to the peculiar X-ray emission observed in $γ$~Cas. Our result favors a recent new scenario that emphasizes the roles of stellar wind and binarity in the X-ray emission of the $γ$~Cas stars.

astro-ph.SR↗

arXiv2021

Toward Annotator Group Bias in Crowdsourcing

Crowdsourcing has emerged as a popular approach for collecting annotated data to train supervised machine learning models. However, annotator bias can lead to defective annotations. Though there are a few works investigating individual annotator bias, the group effects in annotators are largely overlooked. In this work, we reveal that annotators within the same demographic group tend to show consistent group bias in annotation tasks and thus we conduct an initial study on annotator group bias. We first empirically verify the existence of annotator group bias in various real-world crowdsourcing datasets. Then, we develop a novel probabilistic graphical framework GroupAnno to capture annotator group bias with a new extended Expectation Maximization (EM) training algorithm. We conduct experiments on both synthetic and real-world datasets. Experimental results demonstrate the effectiveness of our model in modeling annotator group bias in label aggregation and model learning over competitive baselines.

cs.HC↗

arXiv2021

Blockchain Machine: A Network-Attached Hardware Accelerator for Hyperledger Fabric

In this paper, we demonstrate how Hyperledger Fabric, one of the most popular permissioned blockchains, can benefit from network-attached acceleration. The scalability and peak performance of Fabric is primarily limited by the bottlenecks present in its block validation/commit phase. We propose Blockchain Machine, a hardware accelerator coupled with a hardware-friendly communication protocol, to act as the validator peer. It can be adapted to applications and their smart contracts, and is targeted for a server with network-attached FPGA acceleration card. The Blockchain Machine retrieves blocks and their transactions in hardware directly from the network interface, which are then validated through a configurable and efficient block-level and transaction-level pipeline. The validation results are then transferred to the host CPU where non-bottleneck operations are executed. From our implementation integrated with Fabric v1.4 LTS, we observed up to 12x speedup in block validation when compared to software-only validator peer, with commit throughput of up to 68,900 tps. Our work provides an acceleration platform that will foster further research on hardware acceleration of permissioned blockchains.

cs.DC↗

arXiv2021

A Morphological Classification of 18190 Molecular Clouds Identified in $^{12}$CO Data from the MWISP Survey

We attempt to visually classify the morphologies of 18190 molecular clouds, which are identified in the $^{12}$CO(1-0) spectral line data over $\sim$ 450 deg$^{2}$ of the second Galactic quadrant from the Milky Way Imaging Scroll Painting project (MWISP). Using the velocity-integrated intensity maps of the $^{12}$CO(1-0) emission, molecular clouds are first divided into unresolved and resolved ones. The resolved clouds are further classified as non-filaments or filaments. Among the 18190 molecular clouds, $\sim$ 25 $\%$ are unresolved, $\sim$ 64$\%$ are non-filaments, and $\sim$ 11$\%$ are filaments. In the terms of the integrated flux of $^{12}$CO(1-0) spectra of the whole 18190 molecular clouds, $\sim$ 90$\%$ are from filaments, $\sim$ 9$\%$ are from non-filaments, and the rest $\sim$ 1$\%$ are from unresolved sources. Although non-filaments are dominant in the number of the discrete molecular clouds, filaments are the main contributor of $^{12}$CO emission flux. We also present the number distributions of physical parameters of the molecular clouds in our catalog, including their angular sizes, velocity spans, peak intensities of $^{12}$CO(1-0) emission, and $^{12}$CO(1-0) total fluxes. We find that there is a systematic difference between the angular sizes of the non-filaments and filaments, with the filaments tending to have larger angular scales. The H$_{2}$ column densities of them are not significantly different. We also discuss the observational effects, such as those induced by the finite spatial resolution, beam dilution and line-of-sight projection, on the morphological classification of molecular clouds in our sample.

astro-ph.GA↗