arXiv subjects

Ke Wang

Publications and source records attributed to Ke Wang.

At least 559 records · Page 31Linked to original sources

arXiv2020

Theory for the negative longitudinal magnetoresistance in the quantum limit of Kramers Weyl semimetals

Negative magnetoresistance is rare in non-magnetic materials. Recently, a negative magnetoresistance has been observed in the quantum limit of $β$-Ag$_2$Se, where only one band of Landau levels is occupied in a strong magnetic field parallel to the applied current. $β$-Ag$_2$Se is a material that host a Kramers Weyl cone with band degeneracy near the Fermi energy. Kramers Weyl cones exist at time-reversal invariant momenta in all symmorphic chiral crystals, and at a subset of these momenta, including the $Γ$ point, in non-symmorphic chiral crystals. Here, we present a theory for the negative magnetoresistance in the quantum limit of Kramers Weyl semimetals. We show that, although there is a band touching similar to those in Weyl semimetals, negative magnetoresistance can exist without a chiral anomaly. We find that it requires screened Coulomb scattering potentials between electrons and impurities, which is naturally the case in $β$-Ag$_2$Se.

cond-mat.mes-hall↗

arXiv2020

A feature-supervised generative adversarial network for environmental monitoring during hazy days

The adverse haze weather condition has brought considerable difficulties in vision-based environmental applications. While, until now, most of the existing environmental monitoring studies are under ordinary conditions, and the studies of complex haze weather conditions have been ignored. Thence, this paper proposes a feature-supervised learning network based on generative adversarial networks (GAN) for environmental monitoring during hazy days. Its main idea is to train the model under the supervision of feature maps from the ground truth. Four key technical contributions are made in the paper. First, pairs of hazy and clean images are used as inputs to supervise the encoding process and obtain high-quality feature maps. Second, the basic GAN formulation is modified by introducing perception loss, style loss, and feature regularization loss to generate better results. Third, multi-scale images are applied as the input to enhance the performance of discriminator. Finally, a hazy remote sensing dataset is created for testing our dehazing method and environmental detection. Extensive experimental results show that the proposed method has achieved better performance than current state-of-the-art methods on both synthetic datasets and real-world remote sensing images.

cs.CV↗

arXiv2020

Fragmentation of star-forming filaments in the X-shape Nebula of the California molecular cloud

Dense molecular filaments are central to the star formation process, but the detailed manner in which they fragment into prestellar cores is not yet well understood. Here, we investigate the fragmentation properties and dynamical state of several star-forming filaments in the X-shape Nebula region of the California MC, in an effort to shed some light on this issue. We used multi-wavelength far-infrared images from Herschel and the getsources and getfilaments extraction methods to identify dense cores and filaments and derive their basic properties. We also used a map of $\rm ^{13}CO (2-1)$ emission from SMT 10m submillimeter telescope to constrain the dynamical state of the filaments. We identified 10 filaments, as well as 57 dense cores. Two star-forming filaments (# 8 and # 10) stand out in that they harbor quasi-periodic chains of dense cores with a typical projected core spacing of $\sim$0.15 pc. These two filaments have thermally supercritical line masses and are not static. Filament~8 exhibits a prominent transverse velocity gradient, suggesting that it is accreting gas from the parent cloud gas reservoir. In both cases, the observed (projected) core spacing is similar to the filament width and significantly shorter than the canonical separation of $\sim \,$4 times the filament width predicted by classical cylinder fragmentation theory. We suggest that continuous accretion of gas onto the two star-forming filaments, as well as geometrical bending of the filaments, may account for the observed core spacing. Our findings suggest that the characteristic fragmentation lengthscale of molecular filaments is quite sensitive to external perturbations from the parent cloud, such as gravitational accretion of ambient material.

astro-ph.SR↗

arXiv2020

The Adaptability and Challenges of Autonomous Vehicles to Pedestrians in Urban China

China is the world's largest automotive market and is ambitious for autonomous vehicles (AVs) development. As one of the key goals of AVs, pedestrian safety is an important issue in China. Despite the rapid development of driverless technologies in recent years, there is a lack of researches on the adaptability of AVs to pedestrians. To fill the gap, this study would discuss the adaptability of current driverless technologies to China urban pedestrians by reviewing the latest researches. The paper firstly analyzed typical Chinese pedestrian behaviors and summarized the safety demands of pedestrians for AVs through articles and open database data, which are worked as the evaluation criteria. Then, corresponding driverless technologies are carefully reviewed. Finally, the adaptability would be given combining the above analyses. Our review found that autonomous vehicles have trouble in the occluded pedestrian environment and Chinese pedestrians do not accept AVs well. And more explorations should be conducted on standard human-machine interaction, interaction information overload avoidance, occluded pedestrians detection and nation-based receptivity research. The conclusions are very useful for motor corporations and driverless car researchers to place more attention on the complexity of the Chinese pedestrian environment, for transportation experts to protect pedestrian safety in the context of AVs, and for governors to think about making new pedestrians policies to welcome the upcoming driverless cars.

cs.HC↗

arXiv2020

Image polaritons in boron nitride for extreme polariton confinement with low losses

Polaritons in two-dimensional materials provide extreme light confinement that is difficult to achieve with metal plasmonics. However, such tight confinement inevitably increases optical losses through various damping channels. Here we demonstrate that hyperbolic phonon polaritons in hexagonal boron nitride can overcome this fundamental trade-off. Among two observed polariton modes, featuring a symmetric and antisymmetric charge distribution, the latter exhibits lower optical losses and tighter polariton confinement. Far-field excitation and detection of this high-momenta mode becomes possible with our resonator design that can boost the coupling efficiency via virtual polariton modes with image charges that we dub image polaritons. Using these image polaritons, we experimentally observe a record-high effective index of up to 132 and quality factors as high as 501. Further, our phenomenological theory suggests an important role of hyperbolic surface scattering in the damping process of hyperbolic phonon polaritons.

physics.optics↗

arXiv2020

Molecular Cloud Cores with High Deuterium Fraction: Nobeyama Single-Pointing Survey

We present the results of a single-pointing survey of 207 dense cores embedded in Planck Galactic Cold Clumps distributed in five different environments ($λ$ Orionis, Orion A, B, Galactic plane, and high latitudes) to identify dense cores on the verge of star formation for the study of the initial conditions of star formation. We observed these cores in eight molecular lines at 76-94 GHz using the Nobeyama 45-m telescope. We find that early-type molecules (e.g., CCS) have low detection rates and that late-type molecules (e.g., N$_2$H$^+$, c-C$_3$H$_2$) and deuterated molecules (e.g., N$_2$D$^+$, DNC) have high detection rates, suggesting that most of the cores are chemically evolved. The deuterium fraction (D/H) is found to decrease with increasing distance, indicating that it suffers from differential beam dilution between the D/H pair of lines for distant cores ($>$1 kpc). For $λ$ Orionis, Orion A, and B located at similar distances, D/H is not significantly different, suggesting that there is no systematic difference in the observed chemical properties among these three regions. We identify at least eight high D/H cores in the Orion region and two at high latitudes, which are most likely to be close to the onset of star formation. There is no clear evidence of the evolutionary change in turbulence during the starless phase, suggesting that the dissipation of turbulence is not a major mechanism for the beginning of star formation as judged from observations with a beam size of 0.04 pc.

astro-ph.GA↗

arXiv2020

Time-aware Graph Embedding: A temporal smoothness and task-oriented approach

Knowledge graph embedding, which aims to learn the low-dimensional representations of entities and relationships, has attracted considerable research efforts recently. However, most knowledge graph embedding methods focus on the structural relationships in fixed triples while ignoring the temporal information. Currently, existing time-aware graph embedding methods only focus on the factual plausibility, while ignoring the temporal smoothness which models the interactions between a fact and its contexts, and thus can capture fine-granularity temporal relationships. This leads to the limited performance of embedding related applications. To solve this problem, this paper presents a Robustly Time-aware Graph Embedding (RTGE) method by incorporating temporal smoothness. Two major innovations of our paper are presented here. At first, RTGE integrates a measure of temporal smoothness in the learning process of the time-aware graph embedding. Via the proposed additional smoothing factor, RTGE can preserve both structural information and evolutionary patterns of a given graph. Secondly, RTGE provides a general task-oriented negative sampling strategy associated with temporally-aware information, which further improves the adaptive ability of the proposed algorithm and plays an essential role in obtaining superior performance in various tasks. Extensive experiments conducted on multiple benchmark tasks show that RTGE can increase performance in entity/relationship/temporal scoping prediction tasks.

cs.LG↗

arXiv2020

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- II. Compact objects in ACA observations and star formation scaling relations

We report studies of the relationships between the total bolometric luminosity ($L_{\rm bol}$ or $L_{\rm TIR}$) and the molecular line luminosities of $J=1-0$ transitions of H$^{13}$CN, H$^{13}$CO$^+$, HCN, and HCO$^+$ with data obtained from ACA observations in the "ATOMS" survey of 146 active Galactic star forming regions. The correlations between $L_{\rm bol}$ and molecular line luminosities $L'_{\rm mol}$ of the four transitions all appear to be approximately linear. Line emission of isotopologues shows as large scatters in $L_{\rm bol}$-$L'_{\rm mol}$ relations as their main line emission. The log($L_{\rm bol}$/$L'_{\rm mol}$) for different molecular line tracers have similar distributions. The $L_{\rm bol}$-to-$L'_{\rm mol}$ ratios do not change with galactocentric distances ($R_{\rm GC}$) and clump masses ($M_{\rm clump}$). The molecular line luminosity ratios (HCN-to-HCO$^+$, H$^{13}$CN-to-H$^{13}$CO$^+$, HCN-to-H$^{13}$CN and HCO$^+$-to-H$^{13}$CO$^+$) all appear constant against $L_{\rm bol}$, dust temperature ($T_{\rm d}$), $M_{\rm clump}$ and $R_{\rm GC}$. Our studies suggest that both the main lines and isotopologue lines are good tracers of the total masses of dense gas in Galactic molecular clumps. The large optical depths of main lines do not affect the interpretation of the slopes in star formation relations. We find that the mean star formation efficiency (SFE) of massive Galactic clumps in the "ATOMS" survey is reasonably consistent with other measures of the SFE for dense gas, even those using very different tracers or examining very different spatial scales.

astro-ph.GA↗

arXiv2020

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- I. Survey description and a first look at G9.62+0.19

The "ATOMS," standing for {\it ALMA Three-millimeter Observations of Massive Star-forming regions}, survey has observed 146 active star forming regions with ALMA Band 3, aiming to systematically investigate the spatial distribution of various dense gas tracers in a large sample of Galactic massive clumps, to study the roles of stellar feedback in star formation, and to characterize filamentary structures inside massive clumps. In this work, the observations, data analysis, and example science of the "ATOMS" survey are presented, using a case study for the G9.62+0.19 complex. Toward this source, some transitions, commonly assumed to trace dense gas, including CS $J = 2-1$, HCO$^+$ $J = 1-0$ and HCN $J = 1-0$, are found to show extended gas emission in low density regions within the clump; less than 25\% of their emission is from dense cores. SO, CH$_3$OH, H$^{13}$CN and HC$_3$N show similar morphologies in their spatial distributions and reveal well the dense cores. Widespread narrow SiO emission is present (over $\sim$1 pc), which may be caused by slow shocks from large--scale colliding flows or H{\sc ii} regions. Stellar feedback from an expanding H{\sc ii} region has greatly reshaped the natal clump, significantly changed the spatial distribution of gas, and may also account for the sequential high-mass star formation in the G9.62+0.19 complex. The ATOMS survey data can be jointly analyzed with other survey data, e.g., "MALT90", "Orion B", "EMPIRE", "ALMA\_IMF", and "ALMAGAL", to deepen our understandings of "dense gas" star formation scaling relations and massive proto-cluster formation.

astro-ph.GA↗

arXiv2020

Singular vector and singular subspace distribution for the matrix denoising model

In this paper, we study the matrix denosing model $Y=S+X$, where $S$ is a low-rank deterministic signal matrix and $X$ is a random noise matrix, and both are $M\times n$. In the scenario that $M$ and $n$ are comparably large and the signals are supercritical, we study the fluctuation of the outlier singular vectors of $Y$. More specifically, we derive the limiting distribution of angles between the principal singular vectors of $Y$ and their deterministic counterparts, the singular vectors of $S$. Further, we also derive the distribution of the distance between the subspace spanned by the principal singular vectors of $Y$ and that spanned by the singular vectors of $S$. It turns out that the limiting distributions depend on the structure of the singular vectors of $S$ and the distribution of $X$, and thus they are non-universal.

math.ST↗

arXiv2020

Asynchronous Real-Time Optimization of Footstep Placement and Timing in Bipedal Walking Robots

Online footstep planning is essential for bipedal walking robots to be able to walk in the presence of disturbances. Until recently this has been achieved by only optimizing the placement of the footstep, keeping the duration of the step constant. In this paper we introduce a footstep planner capable of optimizing footstep placement and timing in real-time by asynchronously combining two optimizers, which we refer to as asynchronous real-time optimization (ARTO). The first optimizer which runs at approximately 25 Hz, utilizes a fourth-order Runge-Kutta (RK4) method to accurately approximate the dynamics of the linear inverted pendulum (LIP) model for bipedal walking, then uses non-linear optimization to find optimal footsteps and duration at a lower frequency. The second optimizer that runs at approximately 250 Hz, uses analytical gradients derived from the full dynamics of the LIP model and constraint penalty terms to perform gradient descent, which finds approximately optimal footstep placement and timing at a higher frequency. By combining the two optimizers asynchronously, ARTO has the benefits of fast reactions to disturbances from the gradient descent optimizer, accurate solutions that avoid local optima from the RK4 optimizer, and increases the probability that a feasible solution will be found from the two optimizers. Experimentally, we show that ARTO is able to recover from considerably larger pushes and produces feasible solutions to larger reference velocity changes than a standard footstep location optimizer, and outperforms using just the RK4 optimizer alone.

cs.RO↗

arXiv2020

Studying $Λ^*$ resonances in the $p \bar p \rightarrow Λ\barΛη$ reaction

In this work, we make a theoretical study on the $p \bar p \rightarrow Λ\barΛη$ reaction for antiproton beam energy from threshold to 4GeV within an effective Lagrangian approach and isobar model. By assuming this reaction is dominated by the excitation of $Λ$ and $\bar Λ$ resonances in intermediate states, we calculate the total cross sections and give the predictions of the angular distribution and invariant mass spectrum of final particles. In particular, we discuss the possibility to verify the existence of a narrow $Λ$ resonance found in the process of $K^- p\to ηΛ$ in the present reaction. It shows that the $p \bar p \rightarrow \bar ΛΛη$ reaction can provide us with valuable information about the $Λ$ resonances having significant couplings to $\bar K N$ and $Λη$ channels. Thus the experimental data of this reaction will be a good supplement to the $\bar K N\toηΛ$ scattering data for studying $Λ$ resonances.

hep-ph↗

arXiv2020

Relative Pose Estimation for Stereo Rolling Shutter Cameras

In this paper, we present a novel linear algorithm to estimate the 6 DoF relative pose from consecutive frames of stereo rolling shutter (RS) cameras. Our method is derived based on the assumption that stereo cameras undergo motion with constant velocity around the center of the baseline, which needs 9 pairs of correspondences on both left and right consecutive frames. The stereo RS images enable the recovery of depth maps from the semi-global matching (SGM) algorithm. With the estimated camera motion and depth map, we can correct the RS images to get the undistorted images without any scene structure assumption. Experiments on both simulated points and synthetic RS images demonstrate the effectiveness of our algorithm in relative pose estimation.

cs.CV↗

arXiv2020

Implications for cosmology from Ground-based Cosmic Microwave Background observations

Cosmic Microwave Background (CMB) anisotropy encodes a lot of information about our Universe. In this paper we take the ground-based CMB observations (GCMB), including the South Pole Telescope (SPT), SPTpol and the Atacama Cosmology Telescope Polarimeter (ACTPol), as a new probe to the CMB anisotropy independent of two satellite observations, i.e. Wilkinson Microwave Anisotropy Probe (WMAP) and Planck. The combination of current GCMB data is consistent with WMAP and Planck. In the spatially flat $Λ$CDM model, the Hubble constant is $H_0=69.72\pm 1.63$ km/s/Mpc at $68\%$ confidence level (CL). Combining with baryon acoustic oscillation (BAO) and the Pantheon sample of Type Ia supernovae (SN), we find that $H_0=68.40\pm 0.58$ km/s/Mpc ($68\%$ CL) in the spatially flat $Λ$CDM cosmology which has a tension with local measurement given by Riess et al. in 2019 at $3.7σ$ level, and $Ω_k=-0.0013\pm 0.0039$ and $N_{\rm{eff}}=2.90\pm 0.41$ ($68\%$ CL) in the extended cosmological models.

astro-ph.CO↗

arXiv2020

Signatures of primordial gravitational waves in matter power spectrum

We simulate the evolution of a dust universe from $z=1089$ to $z=0$ by numerically integrating the Einstein's equation for a spatially flat Friedmann-Lemaire-Robertson-Walker (FLRW) background spacetime with scalar perturbations which are derived from the matter power spectrum produced with the Code for Anisotropies in the Microwave Background (CAMB). To investigate the effects of primordial gravitational waves (GWs) on the inhomogeneity of the universe, we add an additional decaying, divergenceless and traceless primordial tensor perturbation with its initial amplitude being $3\times 10^{-4}$ to the above metric. We find that this primordial tensor perturbation suppresses the matter power spectrum by about $0.01\%$ at $z=0$ for modes with wave number similar to its. This suppression may be a possible probe of a GWs background in the future.

astro-ph.CO↗

arXiv2020

Constraints on Newton's Constant from Cosmological Observations

Newton's constant has observational effects on both the CMB power spectra and the light curves of SNIa. We use Planck data, BAO data and the SNIa measurement to constrain the varying Newton's constant $G$ during the CMB epoch and the redshift ranges of PANTHEON samples, and find no evidence indicating that $G$ is varying with redshift. By extending the $Λ$CDM model with one free parameter $G$, we get $G =(6.65635_{-0.18560}^{+0.18766} ) \times 10^{-11} \rm m^3kg^{-1}s^{-2}$ and $H_0=67.62^{+1.24}_{-1.25} $ km s$^{-1}$ Mpc$^{-1}$ at 68$\%$ C.L. from Planck$+$BAO$+$uncalibrated PANTHEON. The results show the value of $G$ is consistent with CODATA 2018, but the $H_0$ tension can't be solved in this way.

astro-ph.CO↗

arXiv2020

Learning Semantic Program Embeddings with Graph Interval Neural Network

Learning distributed representations of source code has been a challenging task for machine learning models. Earlier works treated programs as text so that natural language methods can be readily applied. Unfortunately, such approaches do not capitalize on the rich structural information possessed by source code. Of late, Graph Neural Network (GNN) was proposed to learn embeddings of programs from their graph representations. Due to the homogeneous and expensive message-passing procedure, GNN can suffer from precision issues, especially when dealing with programs rendered into large graphs. In this paper, we present a new graph neural architecture, called Graph Interval Neural Network (GINN), to tackle the weaknesses of the existing GNN. Unlike the standard GNN, GINN generalizes from a curated graph representation obtained through an abstraction method designed to aid models to learn. In particular, GINN focuses exclusively on intervals for mining the feature representation of a program, furthermore, GINN operates on a hierarchy of intervals for scaling the learning to large graphs. We evaluate GINN for two popular downstream applications: variable misuse prediction and method name prediction. Results show in both cases GINN outperforms the state-of-the-art models by a comfortable margin. We have also created a neural bug detector based on GINN to catch null pointer deference bugs in Java code. While learning from the same 9,000 methods extracted from 64 projects, GINN-based bug detector significantly outperforms GNN-based bug detector on 13 unseen test projects. Next, we deploy our trained GINN-based bug detector and Facebook Infer to scan the codebase of 20 highly starred projects on GitHub. Through our manual inspection, we confirm 38 bugs out of 102 warnings raised by GINN-based bug detector compared to 34 bugs out of 129 warnings for Facebook Infer.

cs.SE↗

arXiv2020

Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks

The current deep learning based visual tracking approaches have been very successful by learning the target classification and/or estimation model from a large amount of supervised training data in offline mode. However, most of them can still fail in tracking objects due to some more challenging issues such as dense distractor objects, confusing background, motion blurs, and so on. Inspired by the human "visual tracking" capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual tracking, which successfully exploits both appearance and motion features for model update. Our TS-RCN can be integrated with existing deep learning based visual trackers. To further improve the tracking performance, we adopt a "wider" residual network ResNeXt as its feature extraction backbone. To the best of our knowledge, TS-RCN is the first end-to-end trainable two-stream visual tracking system, which makes full use of both appearance and motion features of the target. We have extensively evaluated the TS-RCN on most widely used benchmark datasets including VOT2018, VOT2019, and GOT-10K. The experiment results have successfully demonstrated that our two-stream model can greatly outperform the appearance based tracker, and it also achieves state-of-the-art performance. The tracking system can run at up to 38.1 FPS.

cs.CV↗