arXiv subjects

Wei Li

Publications and source records attributed to Wei Li.

At least 1,135 records · Page 63Linked to original sources

arXiv2020

Disentangle contributions to small-system collectivity via scans of light nucleus-nucleus collisions

The observation of multi-particle azimuthal correlations in high-energy small-system collisions has led to intense debate on its origin and the possible coexistence from two competing theoretical scenarios: one based on initial-state intrinsic momentum anisotropy (ISM), and the other based on final-state collective response to the collision geometry (FSM). To complement the previous scan of asymmetric collision systems ($p$+Au, $d$+Au and He+Au), we propose a scan of small symmetric collision systems at RHIC, such as C+C, O+O, Al+Al and Ar+Ar $\sqrt{s_{\mathrm{NN}}}=0.2$ TeV, to provide further insights in disentangling contributions from these two scenarios. These symmetric small systems have the advantage of providing a better controlled initial geometry dominated by the average shape of the overlap region, as opposed to fluctuation-driven geometries in asymmetric systems. A transport model is employed to investigate the expected geometry response in the FSM scenario. Different trends of elliptic flow with increasing charge particle multiplicity are observed between symmetric and asymmetric systems, while triangular flow appears to show a similar behavior. Furthermore, a comparison of O+O collisions at $\sqrt{s_{\mathrm{NN}}}=0.2$ TeV and at $\sqrt{s_{\mathrm{NN}}}=2.76-7$ TeV, as proposed at the LHC, provides a unique opportunity to disentangle the collision geometry effects at nucleon level from those arising from subnucleon fluctuations.

nucl-ex↗

arXiv2020

Dissociated dislocation-mediated carbon transport and diffusion in austenitic iron

Dislocation-solute interaction plays fundamental roles in mechanical properties of alloys. Here, we disclose the essential features of dislocation-carbon interaction in austenitic Fe at the atomistic scale. We show that passage of a Shockley partial dislocation in face-centered cubic iron is able to move carbon atoms on the slip plane forward by one Burgers vector, revealing a novel dissociated dislocation-mediated transport mechanism. This mechanism is induced by shear, which is distinct from the normal thermally activated diffusion process. Furthermore, we show that there exists a fast diffusion channel with significantly reduced diffusion energy barrier in the partial dislocation core, which is highly localized and directional. These inherent geometrical features are crucial for understanding the dependence of the diffusivity of dislocation pipe diffusion on the character of dislocations; most importantly, they can result in unbalanced pinning effect on the leading and trailing partials in a mixed dislocation, consequently facilitating stacking fault formation and deformation twinning. This explains the controversial effects of carbon on deformation twinning observed in various alloys. Our findings pave the road to tune mechanical properties of materials by manipulating dislocation-interstitial interaction.

cond-mat.mtrl-sci↗

arXiv2020

Full field-of-view multi-targets imaging through scattering beyond 3D optical memory effect

A robust method and strategy for efficient full field-ofview and depth separation optical imaging through scattering media regardless of the three-dimensional (3D) optical memory effect are proposed. In this method, the problem of imaging de-aliasing, decomposition, and separation of speckle patterns are solved taking advantages of the spatial decorrelation characteristics of speckles by employing randomly modulated illumination strategy and independent component analysis methods. Full field-of-view imaging of multi-targets locate at diverse spatial positions behind a scattering layer are realized and observed experimentally, for the first time, to the best of our knowledge. The method and strategy provide a potentially useful means for incoherent imaging through scattering in a wide class of fields such as optical microscopy, biomedical imaging, and astronomical imaging.

physics.optics↗

arXiv2020

Causal Mediation Analysis with Multiple Treatments and Latent Confounders

Causal mediation analysis is used to evaluate direct and indirect causal effects of a treatment on an outcome of interest through an intermediate variable or a mediator.It is difficult to identify the direct and indirect causal effects because the mediator cannot be randomly assigned in many real applications. In this article, we consider a causal model including latent confounders between the mediator and the outcome. We present sufficient conditions for identifying the direct and indirect effects and propose an approach for estimating them. The performance of the proposed approach is evaluated by simulation studies. Finally, we apply the approach to a data set of the customer loyalty survey by a telecom company.

stat.AP↗

arXiv2020

Electronic states and magnetic response of MnBi2Te4 by scanning tunneling microscopy and spectroscopy

Exotic quantum phenomena have been demonstrated in recently discovered intrinsic magnetic topological insulator MnBi2Te4. At its two-dimensional limit, quantum anomalous Hall (QAH) effect and axion insulator state are observed in odd and even layers of MnBi2Te4, respectively. The measured band structures exhibit intriguing and complex properties. Here we employ low-temperature scanning tunneling microscopy to study its surface states and magnetic response. The quasiparticle interference patterns indicate that the electronic structures on the topmost layer of MnBi2Te4 is different from that of the expected out-of-plane A-type antiferromagnetic phase. The topological surface states may be embedded in deeper layers beneath the topmost surface. Such novel electronic structure presumably related to the modification of crystalline structure during sample cleaving and re-orientation of magnetic moment of Mn atoms near the surface. Mn dopants substituted at the Bi site on the second atomic layer are observed. The ratio of Mn/Bi substitutions is 5%. The electronic structures are fluctuating at atomic scale on the surface, which can affect the magnetism of MnBi2Te4. Our findings shed new lights on the magnetic property of MnBi2Te4 and thus the design of magnetic topological insulators.

cond-mat.mtrl-sci↗

arXiv2019

The Strength of Ramsey's Theorem For Pairs over trees: I. Weak König's Lemma

Let $\mathsf{TT}^2_k$ denote the combinatorial principle stating that every $k$-coloring of pairs of compatible nodes in the full binary tree has a homogeneous solution, i.e. an isomorphic subtree in which all pairs of compatible nodes have the same color. Let $\mathsf{WKL}_0$ be the subsystem of second order arithmetic consisting of the base system $\mathsf{RCA}_0$ together with the principle (called Weak König's Lemma) stating that every infinite subtree of the full binary tree has an infinite path. We show that over $\mathsf{RCA}_0$, $\mathsf{TT}^2_k$ doe not imply $\mathsf{WKL}_0$. This solves the open problem on the relative strength between the two major subsystems of second order arithmetic.

math.LO↗

arXiv2019

The geometry of optimal functionals

In this paper, we give a geometric interpretation of optimal functionals in the context of intersection of symmetry planes and cyclic polytopes. For 1D CFTs, we demonstrate that at given derivative order, the functional is given by a degenerate simplex of the cyclic polytope. More precisely the derivative functionals at $2N{+}1$-th order, is given by an unique $N$-dimensional simplex enclosing the origin. Taking the continuous limit, in the large $Δ$ approximation this qualitatively agrees with that derived by Mazac et al. Remarkably similar construction applies to 2D CFT in the diagonal limit as well as the spin-less modular bootstrap. Finally we show that such geometric interpretation can be extended to functionals associated with bounds beyond the leading operator.

hep-th↗

arXiv2019

Visual-UWB Navigation System for Unknown Environments

Navigation applications relying on the Global Navigation Satellite System (GNSS) are limited in indoor environments and GNSS-denied outdoor terrains such as dense urban or forests. In this paper, we present a novel accurate, robust and low-cost GNSS-independent navigation system, which is composed of a monocular camera and Ultra-wideband (UWB) transceivers. Visual techniques have gained excellent results when computing the incremental motion of the sensor, and UWB methods have proved to provide promising localization accuracy due to the high time resolution of the UWB ranging signals. However, the monocular visual techniques with scale ambiguity are not suitable for applications requiring metric results, and UWB methods assume that the positions of the UWB transceiver anchor are pre-calibrated and known, thus precluding their application in unknown and challenging environments. To this end, we advocate leveraging the monocular camera and UWB to create a map of visual features and UWB anchors. We propose a visual-UWB Simultaneous Localization and Mapping (SLAM) algorithm which tightly combines visual and UWB measurements to form a joint non-linear optimization problem on Lie-Manifold. The 6 Degrees of Freedom (DoF) state of the vehicles and the map are estimated by minimizing the UWB ranging errors and landmark reprojection errors. Our navigation system starts with an exploratory task which performs the real-time visual-UWB SLAM to obtain the global map, then the navigation task by reusing this global map. The tasks can be performed by different vehicles in terms of equipped sensors and payload capability in a heterogeneous team. We validate our system on the public datasets, achieving typical centimeter accuracy and 0.1% scale error.

cs.RO↗

arXiv2019

AutoRemover: Automatic Object Removal for Autonomous Driving Videos

Motivated by the need for photo-realistic simulation in autonomous driving, in this paper we present a video inpainting algorithm \emph{AutoRemover}, designed specifically for generating street-view videos without any moving objects. In our setup we have two challenges: the first is the shadow, shadows are usually unlabeled but tightly coupled with the moving objects. The second is the large ego-motion in the videos. To deal with shadows, we build up an autonomous driving shadow dataset and design a deep neural network to detect shadows automatically. To deal with large ego-motion, we take advantage of the multi-source data, in particular the 3D data, in autonomous driving. More specifically, the geometric relationship between frames is incorporated into an inpainting deep neural network to produce high-quality structurally consistent video output. Experiments show that our method outperforms other state-of-the-art (SOTA) object removal algorithms, reducing the RMSE by over $19\%$.

cs.CV↗

arXiv2019

Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View

Graph Neural Networks (GNNs) have achieved promising performance on a wide range of graph-based tasks. Despite their success, one severe limitation of GNNs is the over-smoothing issue (indistinguishable representations of nodes in different classes). In this work, we present a systematic and quantitative study on the over-smoothing issue of GNNs. First, we introduce two quantitative metrics, MAD and MADGap, to measure the smoothness and over-smoothness of the graph nodes representations, respectively. Then, we verify that smoothing is the nature of GNNs and the critical factor leading to over-smoothness is the low information-to-noise ratio of the message received by the nodes, which is partially determined by the graph topology. Finally, we propose two methods to alleviate the over-smoothing issue from the topological view: (1) MADReg which adds a MADGap-based regularizer to the training objective;(2) AdaGraph which optimizes the graph topology based on the model predictions. Extensive experiments on 7 widely-used graph datasets with 10 typical GNN models show that the two proposed methods are effective for relieving the over-smoothing issue, thus improving the performance of various GNN models.

cs.LG↗

arXiv2019

A two-dimensional propensity score matching method for longitudinal quasi-experimental studies: A focus on travel behavior and the built environment

The lack of longitudinal studies of the relationship between the built environment and travel behavior has been widely discussed in the literature. This paper discusses how standard propensity score matching estimators can be extended to enable such studies by pairing observations across two dimensions: longitudinal and cross-sectional. Researchers mimic randomized controlled trials (RCTs) and match observations in both dimensions, to find synthetic control groups that are similar to the treatment group and to match subjects synthetically across before-treatment and after-treatment time periods. We call this a two-dimensional propensity score matching (2DPSM). This method demonstrates superior performance for estimating treatment effects based on Monte Carlo evidence. A near-term opportunity for such matching is identifying the impact of transportation infrastructure on travel behavior.

econ.EM↗

arXiv2019

Statistical Properties of Links of Network: A Survey on the Shipping Lines of Worldwide Marine Transport Network

Node properties and node importance identification of networks have been vastly studied in the last decades. While in this work, we analyse the links' properties of networks by taking the Worldwide Marine Transport Network (WMTN) as an example, i.e., statistical properties of the shipping lines of WMTN have been investigated in various aspects: Firstly, we study the feature of loops in the shipping lines by defining the line saturability. It is found that the line saturability decays exponentially with the increase of line length. Secondly, to detect the geographical community structure of shipping lines, the Label Propagation Algorithm with compression of Flow (LPAF) and Multi-Dimensional Scaling (MDS) method are employed, which show rather consistent communities. Lastly, to analyse the redundancy property of shipping lines of different marine companies, the multilayer networks were constructed by aggregating the shipping lines of different marine companies. It is observed that the topological quantities, such as average degree, average clustering coefficient, etc., increase smoothly when marine companies are randomly merged (randomly choose two marine companies, then merge the shipping lines of them together), while the relative entropy decreases when the merging sequence is determined by the Jensen-Shannon distance (choose two marine companies when the J-S distance between them is the lowest). This indicates the low redundancy of shipping lines among different marine companies.

physics.soc-ph↗

arXiv2019

A Three-dimensional Convolutional-Recurrent Network for Convective Storm Nowcasting

Very short-term convective storm forecasting, termed nowcasting, has long been an important issue and has attracted substantial interest. Existing nowcasting methods rely principally on radar images and are limited in terms of nowcasting storm initiation and growth. Real-time re-analysis of meteorological data supplied by numerical models provides valuable information about three-dimensional (3D), atmospheric, boundary layer thermal dynamics, such as temperature and wind. To mine such data, we here develop a convolution-recurrent, hybrid deep-learning method with the following characteristics: (1) the use of cell-based oversampling to increase the number of training samples; this mitigates the class imbalance issue; (2) the use of both raw 3D radar data and 3D meteorological data re-analyzed via multi-source 3D convolution without any need for handcraft feature engineering; and (3) the stacking of convolutional neural networks on a long short-term memory encoder/decoder that learns the spatiotemporal patterns of convective processes. Experimental results demonstrated that our method performs better than other extrapolation methods. Qualitative analysis yielded encouraging nowcasting results.

cs.CV↗

arXiv2019

High-speed measurement-device-independent quantum key distribution with integrated silicon photonics

Measurement-device-independent quantum key distribution (MDI-QKD) removes all detector side channels and enables secure QKD with an untrusted relay. It is suitable for building a star-type quantum access network, where the complicated and expensive measurement devices are placed in the central untrusted relay and each user requires only a low-cost transmitter, such as an integrated photonic chip. Here, we experimentally demonstrate a 1.25 GHz silicon photonic chip-based MDI-QKD system using polarization encoding. The photonic chip transmitters integrate the necessary encoding components for a standard QKD source. We implement random modulations of polarization states and decoy intensities, and demonstrate a finite-key secret rate of 31 bps over 36 dB channel loss (or 180 km standard fiber). This key rate is higher than state-of-the-art MDI-QKD experiments. The results show that silicon photonic chip-based MDI-QKD, benefiting from miniaturization, low-cost manufacture and compatibility with CMOS microelectronics, is a promising solution for future quantum secure networks.

quant-ph↗

arXiv2019

Dynamic Upsampling of Smoke through Dictionary-based Learning

Simulating turbulent smoke flows is computationally intensive due to their intrinsic multiscale behavior, thus requiring relatively high resolution grids to fully capture their complexity. For iterative editing or simply faster generation of smoke flows, dynamic upsampling of an input low-resolution numerical simulation is an attractive, yet currently unattainable goal. In this paper, we propose a novel dictionary-based learning approach to the dynamic upsampling of smoke flows. For each frame of an input coarse animation, we seek a sparse representation of small, local velocity patches of the flow based on an over-complete dictionary, and use the resulting sparse coefficients to generate a high-resolution smoke animation sequence. We propose a novel dictionary-based neural network which learns both a fast evaluation of sparse patch encoding and a dictionary of corresponding coarse and fine patches from a sequence of example simulations computed with any numerical solver. Our upsampling network then injects into coarse input sequences physics-driven fine details, unlike most previous approaches that only employed fast procedural models to add high frequency to the input. We present a variety of upsampling results for smoke flows and offer comparisons to their corresponding high-resolution simulations to demonstrate the effectiveness of our approach.

cs.GR↗

arXiv2019

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.

astro-ph.IM↗

arXiv2019

The Low Energy X-ray telescope (LE) onboard the Insight-HXMT astronomy satellite

The low energy (LE) X-ray telescope is one of the three main instruments of the Insight-Hard X-ray Modulation Telescope (Insight-HXMT). It is equipped with Swept Charge Device (SCD) sensor arrays with a total geometrical area of 384 cm2 and an energy band from 0.7 keV to 13 keV. In order to evaluate the particle induced X-ray background and the cosmic X-ray background simultaneously, LE adopts collimators to define four types of Field Of Views (FOVs). LE is constituted of three detector boxes (LEDs) and an electric control box (LEB) and achieves a good energy resolution of 140 eV at 5.9 keV, an excellent time resolution of 0.98 ms, as well as an extremely low pileup (<1% at 18000 cts/s). Detailed performance tests and calibration on the ground have been performed, including energy-channel relation, energy response, detection efficiency and time response.

astro-ph.IM↗

arXiv2019

Studies on the time response distribution of Insigh}-HXMT/LE

The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite. The Low Energy X-ray Telescope (LE) is one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 with L-shaped transfer electrodes. Charges in detection area are read out continuously along specific paths, which leads to a time response distribution of photons readout time. We designed a long exposure readout mode to measure the time response distribution. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. Through analysis of the photons readout time in this mode, we obtained the probability distribution of photons readout time.

astro-ph.IM↗