arXiv subjects

Kai Wang

Publications and source records attributed to Kai Wang.

At least 757 records · Page 42Linked to original sources

arXiv2019

LSANet: Feature Learning on Point Sets by Local Spatial Aware Layer

Directly learning features from the point cloud has become an active research direction in 3D understanding. Existing learning-based methods usually construct local regions from the point cloud and extract the corresponding features. However, most of these processes do not adequately take the spatial distribution of the point cloud into account, limiting the ability to perceive fine-grained patterns. We design a novel Local Spatial Aware (LSA) layer, which can learn to generate Spatial Distribution Weights (SDWs) hierarchically based on the spatial relationship in local region for spatial independent operations, to establish the relationship between these operations and spatial distribution, thus capturing the local geometric structure sensitively.We further propose the LSANet, which is based on LSA layer, aggregating the spatial information with associated features in each layer of the network better in network design.The experiments show that our LSANet can achieve on par or better performance than the state-of-the-art methods when evaluating on the challenging benchmark datasets. For example, our LSANet can achieve 93.2% accuracy on ModelNet40 dataset using only 1024 points, significantly higher than other methods under the same conditions. The source code is available at https://github.com/LinZhuoChen/LSANet.

cs.CV↗

arXiv2019

Quantum Interference Control of Carriers and Currents in Zincblende Semiconductors based on Nonlinear Absorption Processes

Quantum interference between optical absorption processes can excite carriers with a polarized distribution in the Brillouin zone depending on properties of the incident optical fields. The polarized distribution of carriers introduces a current that can be controlled by the phases and polarizations of the incident optical fields. Here we study the quantum interference of 2- and 3-photon absorption processes in AlGaAs. We present theoretical predictions for carrier and current injection rates considering different frequencies, phases, and polarizations of the incident fields. We also discuss the important features that result from only nonlinear optical processes being involved, which leads for instance to a sharper distribution of carriers in the Brillouin zone.

cond-mat.mtrl-sci↗

arXiv2019

Quantum Interference Control of Photocurrents in Semiconductors by Nonlinear Optical Absorption Processes

We report experiments demonstrating Quantum Interference Control (QuIC) based on two nonlinear optical absorption processes in semiconductors. We use two optical beams of frequencies $ω$ and $3ω/2$ incident on AlGaAs and measure the injection current due to the interference between 2- and 3-photon absorption processes. We analyze the dependence of the injection current on the intensities and phases of the incident fields.

cond-mat.mes-hall↗

arXiv2019

BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization

The success of neural summarization models stems from the meticulous encodings of source articles. To overcome the impediments of limited and sometimes noisy training data, one promising direction is to make better use of the available training data by applying filters during summarization. In this paper, we propose a novel Bi-directional Selective Encoding with Template (BiSET) model, which leverages template discovered from training data to softly select key information from each source article to guide its summarization process. Extensive experiments on a standard summarization dataset were conducted and the results show that the template-equipped BiSET model manages to improve the summarization performance significantly with a new state of the art.

cs.CL↗

arXiv2019

Epoxy-inspired Nonlinear Interface Integrating Monolayer Transition-Metal Dichalcogenides with Linear Plasmonic Nanosieves

Although TMDC monolayers offer giant optical nonlinearity within few-angstrom thickness, it is still elusive to modulate and engineer the wavefront of nonlinear emissions. The grain size of high-quality monolayers also restricts possibilities of imparting inhomogeneous or gradient profiles of phases and amplitudes by classical light sources. Plasmonic nanosieves can support huge field enhancement and precise nonlinear phase control with hundred-nanometer pixel-level resolution, however they suffer from intrinsically weak nonlinear susceptibility. In nature, epoxy represents a strong glue whose magic adhesion comes from the bonding of two intrinsic loose and nonsticky resins. Inspired by the nature of epoxy, we report a multifunctional and powerful nonlinear interfaces via integrating transition-metal dichalcogenide (TMDC) monolayers with linear plasmonic nanosieves, which cannot be accessed by either constituents. We experimentally demonstrate orbital angular momentum (OAM) generation, beam steering, versatile polarization control and holograms and of SH emission, with the proposed nonlinear interfaces. In addition, an effective second-harmonic (SH) nonlinearity \c{hi}(2) of ~25 nm/V is obtained for such systems. This designer platform synergizes the complementary advantages of TMDC monolayer, plasmonic nanosieves, geometric phases, and field enhancement, paving a distinct avenue toward designer, multi-functional, and ultra-compact nonlinear optical devices.

physics.optics↗

arXiv2019

Nonreciprocal photon blockade in a two-mode cavity with a second-order nonlinearity

It is shown that the Fizeau drag can be used to cause nonreciprocity. We propose the use of a nanostructured toroid cavity made of $χ^{(2)}$ nonlinear materials to achieve nonreciprocal photon blockade (PB) through the Fizeau drag. Under the weak driving condition, we discuss the origins of the PB based on the doubly resonant modes with good spatial overlap at the fundamental and second-harmonic frequencies. We also find that for the fundamental mode, the PB happens when we drive the system from one side but the photon-induced tunneling happens when we drive the system from the other side. However, there is no such phenomenon in the second-harmonic mode. Remarkably, the PB phenomenon occurs with a reasonably small optical nonlinearity thus bringing the system parameters closer to the reasonably achievable realm by the current technology.

quant-ph↗

arXiv2019

Quark jet versus gluon jet: fully-connected neural networks with high-level features

Jet identification is one of the fields in high energy physics that machine learning has begun to make an impact. More often than not, convolutional neural networks are used to classify jet images with the benefit that essentially no physics input is required. Inspired by a recent work by Datta and Larkoski, we study the classification of quark/gluon-initiated jets based on fully-connected neural networks (FNNs), where expert-designed physical variables are taken as input. FNNs are applied in two ways: trained separately on various narrow jet transverse momentum $p_{TJ}$ bins; trained on a wide region of $p_{TJ} \in [200,~1000]$ GeV. We find their performances are almost the same. The performance is better when the $p_{TJ}$ is larger. Jet discrimination with FNN is studied on both particle and detector level data. The results based on particle level data are comparable with those from deep convolutional neural networks, while the significance improvement characteristic (SIC) from detector level data would at most decrease by $15\%$. We also test the performance of FNNs with full set or subsets of jet observables as input features. The FNN with one subset consisting of fourteen observables shows nearly no degradation of performance. This indicates that these fourteen expert-designed observables could have captured the most necessary information for separating quark and gluon jets.

hep-ph↗

arXiv2019

Supermassive black holes with high accretion rates in active galactic nuclei: X. Optical variability characteristics

We compiled a sample of 73 active galactic nuclei (AGNs) with reverberation mapping (RM) observations from RM campaigns including our ongoing campaign of monitoring super-Eddington accreting massive black holes (SEAMBHs). This sample covers a large range of black hole (BH) mass $(M_{\bullet}=10^{6-9}~M_\odot)$, dimensionless accretion rates $(\dot{\mathscr{M}}=10^{-2.7}-10^{2.7})$ and 5100~Å~luminosity $(L_{5100}=10^{42-46}~\rm erg~s^{-1})$, allowing us to systematically study the AGN variability and their relations with BH mass, accretion rates, and optical luminosity. We employed the damped random walk (DRW) model to delineate the optical variability of continuum at 5100~Å~and obtained damped variability timescale ($τ_{\rm d}$) and amplitude ($σ_{\rm d}$) using a Markov Chain Monte Carlo (MCMC) method. We also estimated the traditional variability amplitudes ($F_{\rm var}$), which provide a model-independent measure and therefore are used to test the DRW results. We found that AGN variability characteristics are generally correlated with $(M_{\bullet},\dot{\mathscr{M}},L_{5100})$. These correlations are smooth from sub-Eddington to super-Eddington accretion AGNs, probably implying that the AGN variability may be caused by the same physical mechanism.

astro-ph.GA↗

arXiv2019

Virtual-Blind-Road Following Based Wearable Navigation Device for Blind People

To help the blind people walk to the destination efficiently and safely in indoor environment, a novel wearable navigation device is presented in this paper. The locating, way-finding, route following and obstacle avoiding modules are the essential components in a navigation system, while it remains a challenging task to consider obstacle avoiding during route following, as the indoor environment is complex, changeable and possibly with dynamic objects. To address this issue, we propose a novel scheme which utilizes a dynamic sub-goal selecting strategy to guide the users to the destination and help them bypass obstacles at the same time. This scheme serves as the key component of a complete navigation system deployed on a pair of wearable optical see-through glasses for the ease of use of blind people's daily walks. The proposed navigation device has been tested on a collection of individuals and proved to be effective on indoor navigation tasks. The sensors embedded are of low cost, small volume and easy integration, making it possible for the glasses to be widely used as a wearable consumer device.

cs.CV↗

arXiv2019

Deep Learning Based Robot for Automatically Picking up Garbage on the Grass

This paper presents a novel garbage pickup robot which operates on the grass. The robot is able to detect the garbage accurately and autonomously by using a deep neural network for garbage recognition. In addition, with the ground segmentation using a deep neural network, a novel navigation strategy is proposed to guide the robot to move around. With the garbage recognition and automatic navigation functions, the robot can clean garbage on the ground in places like parks or schools efficiently and autonomously. Experimental results show that the garbage recognition accuracy can reach as high as 95%, and even without path planning, the navigation strategy can reach almost the same cleaning efficiency with traditional methods. Thus, the proposed robot can serve as a good assistance to relieve dustman's physical labor on garbage cleaning tasks.

cs.CV↗

arXiv2019

Synthetic Data Generation and Adaption for Object Detection in Smart Vending Machines

This paper presents an improved scheme for the generation and adaption of synthetic images for the training of deep Convolutional Neural Networks(CNNs) to perform the object detection task in smart vending machines. While generating synthetic data has proved to be effective for complementing the training data in supervised learning methods, challenges still exist for generating virtual images which are similar to those of the complex real scenes and minimizing redundant training data. To solve these problems, we consider the simulation of cluttered objects placed in a virtual scene and the wide-angle camera with distortions used to capture the whole scene in the data generation process, and post-processed the generated images with a elaborately-designed generative network to make them more similar to the real images. Various experiments have been conducted to prove the efficiency of using the generated virtual images to enhance the detection precision on existing datasets with limited real training data and the generalization ability of applying the trained network to datasets collected in new environment.

cs.CV↗

arXiv2019

A Survey on Face Data Augmentation

The quality and size of training set have great impact on the results of deep learning-based face related tasks. However, collecting and labeling adequate samples with high quality and balanced distributions still remains a laborious and expensive work, and various data augmentation techniques have thus been widely used to enrich the training dataset. In this paper, we systematically review the existing works of face data augmentation from the perspectives of the transformation types and methods, with the state-of-the-art approaches involved. Among all these approaches, we put the emphasis on the deep learning-based works, especially the generative adversarial networks which have been recognized as more powerful and effective tools in recent years. We present their principles, discuss the results and show their applications as well as limitations. Different evaluation metrics for evaluating these approaches are also introduced. We point out the challenges and opportunities in the field of face data augmentation, and provide brief yet insightful discussions.

cs.CV↗

arXiv2019

Reverberation mapping of narrow-line Seyfert 1 galaxy I Zwicky 1: black hole mass

We report results of the first reverberation mapping campaign of I Zwicky 1 during $2014$-$2016$, which showed unambiguous reverberations of the broad H$β$ line emission to the varying optical continuum. From analysis using several methods, we obtain a reverberation lag of $τ_{\rm Hβ}=37.2^{+4.5}_{-4.9}\,$ days. Taking a virial factor of $f_{_{\rm BLR}}=1$, we find a black hole mass of $M_{\bullet}=9.30_{-1.38}^{+1.26}\times 10^6 M_{\odot}$ from the mean spectra. The accretion rate is estimated to be $203.9_{-65.8}^{+61.0}\,L_{\rm Edd}c^{-2}$, suggesting a super-Eddington accretor, where $L_{\rm Edd}$ is the Eddington luminosity and $c$ is the speed of light. By decomposing {\it Hubble Space Telescope} images, we find that the stellar mass of the bulge of its host galaxy is $\log (M_{\rm bulge}/M_{\odot}) = \rm 10.92\pm 0.07$. This leads to a black hole to bulge mass ratio of $\sim 10^{-4}$, which is significantly smaller than that of classical bulges and elliptical galaxies. After subtracting the host contamination from the observed luminosity, we find that I Zw 1 follows the empirical $R_{\rm BLR}\propto L_{5100}^{1/2}$ relation.

astro-ph.GA↗

arXiv2019

A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation

This paper presents a novel framework for simultaneously implementing localization and segmentation, which are two of the most important vision-based tasks for robotics. While the goals and techniques used for them were considered to be different previously, we show that by making use of the intermediate results of the two modules, their performance can be enhanced at the same time. Our framework is able to handle both the instantaneous motion and long-term changes of instances in localization with the help of the segmentation result, which also benefits from the refined 3D pose information. We conduct experiments on various datasets, and prove that our framework works effectively on improving the precision and robustness of the two tasks and outperforms existing localization and segmentation algorithms.

cs.CV↗

arXiv2019

Extreme defect sensitivity from large synthetic dimensionality

The geometric dimensionality of a physical system significantly impacts its fundamental characteristics. While experiments are fundamentally limited to the maximum of three spatial dimensions, there is a growing interest in harnessing additional synthetic dimensions. In our work, we introduce a new paradigm for the experimental realization of excitation dynamics associated with many-dimensional systems. Crucially, it relies solely on static one-dimensional equivalent structures with judiciously tailored parameters to faithfully reproduce the same optical spectrum and density of states of the high-dimensional system to be represented. In order to showcase the capabilities of our approach, we fabricate 1D photonic lattices that exhibit the characteristic non-monotonic excitation decays associated with quantum walks in up to 7D square lattices. Furthermore, we find that a new type of bound state at the edge of the continuum emerges in higher-than-three dimensions and gives rise to a sharp localisation transition at defect sites. In a series of experiments, we implement the mapped equivalent lattices of up to 5D systems and observe an extreme increase of sensitivity with respect to the detuning of the respective anchor sites. Our findings demonstrate the feasibility and applicative potential of harnessing high-dimensional effects in planar photonics for ultra-sensitive switching or sensing. Notably, our general approach is by no means limited to optics, and can readily be adapted to a variety of other physical contexts, including cold atoms and superconducting qubits with exclusively nearest-neighbour interactions, promising to drive significant advances in different fields including quantum simulations and information processing.

physics.optics↗

arXiv2019

Kinematics of the Broad-line Region of 3C 273 from a Ten-year Reverberation Mapping Campaign

Despite many decades of study, the kinematics of the broad-line region of 3C~273 are still poorly understood. We report a new, high signal-to-noise, reverberation mapping campaign carried out from November 2008 to March 2018 that allows the determination of time lags between emission lines and the variable continuum with high precision. The time lag of variations in H$β$ relative to those of the 5100 Angstrom continuum is $146.8_{-12.1}^{+8.3}$ days in the rest frame, which agrees very well with the Paschen-$α$ region measured by the GRAVITY at The Very Large Telescope Interferometer. The time lag of the H$γ$ emission line is found to be nearly the same as for H$β$. The lag of the Fe II emission is $322.0_{-57.9}^{+55.5}$ days, longer by a factor of $\sim$2 than that of the Balmer lines. The velocity-resolved lag measurements of the H$β$ line show a complex structure which can be possibly explained by a rotation-dominated disk with some inflowing radial velocity in the H$β$-emitting region. Taking the virial factor of $f_{\rm BLR} = 1.3$, we derive a BH mass of $M_{\bullet} = 4.1_{-0.4}^{+0.3} \times 10^8 M_{\odot}$ and an accretion rate of $9.3\,L_{\rm Edd}\,c^{-2}$ from the H$β$ line. The decomposition of its $HST$ images yields a host stellar mass of $M_* = 10^{11.3 \pm 0.7} M_\odot$, and a ratio of $M_{\bullet}/M_*\approx 2.0\times 10^{-3}$ in agreement with the Magorrian relation. In the near future, it is expected to compare the geometrically-thick BLR discovered by the GRAVITY in 3C 273 with its spatially-resolved torus in order to understand the potential connection between the BLR and the torus.

astro-ph.GA↗

arXiv2019

Stochastic Nicholson's blowflies delay differential equation with regime switching

In this paper, we investigate the global existence of almost surely positive solution to a stochastic Nicholson's blowflies delay differential equation with regime switching, and give the estimation of the path. The results presented in this paper extend some corresponding results in Wang et al. Stochastic Nicholson's Blowflies Delayed Differential Equations, Appl. Math. Lett. 87 (2019) 20-26.

math.PR↗

arXiv2019

A hadronuclear interpretation of a high-energy neutrino event coincident with a blazar flare

Although many high-energy neutrinos detected by the IceCube telescope are believed to have anextraterrestrial origin, their astrophysical sources remain a mystery. Recently, an unprecedenteddiscovery of a high-energy muon neutrino event coincident with a multiwavelength flare from ablazar, TXS 0506+056, shed some light on the origin of the neutrinos. It is usually believed that ablazar is produced by a relativistic jet launched from an accreting supermassive black hole (SMBH).Here we show that the high-energy neutrino event can be interpreted by the inelastic hadronuclearinteractions between the accelerated cosmic-ray protons in the relativistic jet and the dense gasclouds in the vicinity of the SMBH. Such a scenario only requires a moderate proton power in thejet, which could be much smaller than that required in the conventional hadronic model whichinstead calls upon the photomeson process. Meanwhile, the flux of the multiwavelength flare fromthe optical to gamma-ray band can be well explained by invoking a second radiation zone in thejet at a larger distance to the SMBH. In our model, the neutrino emission lasts a shorter time thanthe multiwavelength flare so the neutrino event is not necessarily correlated with the flare but it is probably accompanied by a spectrum hardening above a few GeV.

astro-ph.HE↗