arXiv subjects

Chen Wang

Publications and source records attributed to Chen Wang.

At least 739 records · Page 41Linked to original sources

arXiv2019

Transmission Lines Positive Sequence Parameters Estimation and Instrument Transformers Calibration Based on PMU Measurement Error Model

Phasor Measurement Unit measurement data have been widely used in nowadays power system applications both in steady state and dynamic analysis. The performance of these applications running in utilities' energy management system depends heavily on an accurate positive sequence power system model. However, it is impractical to find this accurate model with transmission line parameters calculated directly with the PMU measurements due to ratio errors brought by instrument transformers and communication errors brought by PMUs. Therefore, a methodology is proposed in this paper to estimate the actual transmission lines parameters throughout the whole system and, at the same time, calibrate the corresponding instrument transformers. A PMU positive sequence measurement error model is proposed targeting at the aforementioned errors, which is applicable to both transposed and un-transposed transmission lines. A single line parameters estimation method is designed based on Least Squares Estimation and this error model. This method requires only one set of reference measurements and the accuracy can be propagated throughout the whole network along with the topology acquired by the introduced Edge-based Breadth-first Search algorithm. The IEEE 118-bus system and the Texas 2000-bus system are used to demonstrate the effectiveness and efficiency of the proposed method. The potential for deployment in reality is also discussed.

eess.SY↗

arXiv2019

Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model

Car following models have been widely applied and made remarkable achievements in traffic engineering. However, the traffic micro-simulation accuracy of car following models in a platoon level, especially during traffic oscillations, still needs to be enhanced. Rather than using traditional individual car following models, we proposed a new trajectory generation approach to generate platoon level trajectories given the first leading vehicle's trajectory. In this paper, we discussed the temporal and spatial error propagation issue for the traditional approach by a car following block diagram representation. Based on the analysis, we pointed out that error comes from the training method and the model structure. In order to fix that, we adopt two improvements on the basis of the traditional LSTM based car following model. We utilized a scheduled sampling technique during the training process to solve the error propagation in the temporal dimension. Furthermore, we developed a unidirectional interconnected LSTM model structure to extract trajectories features from the perspective of the platoon. As indicated by the systematic empirical experiments, the proposed novel structure could efficiently reduce the temporal and spatial error propagation. Compared with the traditional LSTM based car following model, the proposed model has almost 40% less error. The findings will benefit the design and analysis of micro-simulation for platoon level car following models.

cs.LG↗

arXiv2019

A polaron theory of quantum thermal transistor in nonequilibrium three-level systems

We investigate the quantum thermal transistor effect in nonequilibrium three-level systems by applying the polaron transformed Redfield equation combined with full counting statistics. The steady state heat currents are obtained via this unified approach over a wide region of system-bath coupling, and can be analytically reduced to the Redfield and nonequilibrium noninteracting blip approximation results in the weak and strong coupling limits, respectively. A giant heat amplification phenomenon emerges in the strong system-bath coupling limit, where transitions mediated by the middle thermal bath is found to be crucial to unravel the underlying mechanism. Moreover, the heat amplification is also exhibited with moderate coupling strength, which can be properly explained within the polaron framework.

quant-ph↗

arXiv2019

6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints

We present 6-PACK, a deep learning approach to category-level 6D object pose tracking on RGB-D data. Our method tracks in real-time novel object instances of known object categories such as bowls, laptops, and mugs. 6-PACK learns to compactly represent an object by a handful of 3D keypoints, based on which the interframe motion of an object instance can be estimated through keypoint matching. These keypoints are learned end-to-end without manual supervision in order to be most effective for tracking. Our experiments show that our method substantially outperforms existing methods on the NOCS category-level 6D pose estimation benchmark and supports a physical robot to perform simple vision-based closed-loop manipulation tasks. Our code and video are available at https://sites.google.com/view/6packtracking.

cs.CV↗

arXiv2019

Autonomous Quantum State Transfer by Dissipation Engineering

Quantum state transfer from an information-carrying qubit to a receiving qubit is ubiquitous for quantum information technology. In a closed quantum system, this task requires precisely-timed control of coherent qubit-qubit interactions that are intrinsically reciprocal. Here, breaking reciprocity by tailoring dissipation in an open system, we show that it is possible to autonomously transfer a quantum state between stationary qubits without time-dependent control. We present the general requirements for this directional transfer process, and show that the minimum system dimension for transferring one qubit of information is 3 $\times$ 2 (between one physical qutrit and one physical qubit), plus one auxiliary reservoir. We propose realistic implementations in present-day superconducting circuit QED experiments, and further propose schemes compatible with long-distance state transfer using impedance-matched dissipation engineering.

quant-ph↗

arXiv2019

$p$-adic analogues of hypergeometric identities and their applications

In this paper, we confirm several conjectures posed by Sun recently; for example, we prove that for any odd prime $p$ we have $$ \sum_{k=0}^{p-1}A_k\equiv\begin{cases}4x^2-2p\pmod{p^2}\quad&\text{if $p=x^2+2y^2\ (x,y\in\mathbb{Z})$},\\ 0\pmod{p^2}\quad&\text{if $p\equiv5,7\pmod{8}$},\end{cases} $$ where $A_n:=\sum_{k=0}^n\binom{n+k}{k}^2\binom{n}{k}^2$ are the Apéry numbers.

math.NT↗

arXiv2019

Photoninduced Weyl half-metal phase and spin filter effect from topological Dirac semimetals

Recently discovered Dirac semimetals (DSMs) with two Dirac nodes, such as Na$_{3}$Bi and Cd$_{2}$As$_{3}$, are regarded to carry the $\mathbb{Z}_{2}$ topological charge in addition to the chiral charge. Here, we study the Floquet phase transition of $\mathbb{Z}_{2}$ topological DSMs subjected to a beam of circularly polarized light. Due to the resulting interplay of the chiral and $\mathbb{Z}_{2}$ charges, the Weyl nodes are not only chirality-dependent but also spin-dependent, which constrains the behaviors in creation and annihilation of the Weyl nodes in pair. Interestingly, we find a novel phase: One spinband is in Weyl semimetal phase while the other spinband is in insulator phase, and we dub it Weyl half-metal (WHM) phase. We further study the spin-dependent transport in a Dirac-Weyl semimetal junction and find a spin filter effect as a fingerprint of existence of the WHM phase. The proposed spin filter effect, based on the WHM bulk band, is highly tunable in a broad parameter regime and robust against magnetic disorder, which is expected to overcome the shortcomings of the previously proposed spin filter based on the topological edge/surface states. Our results offer a unique opportunity to explore the potential applications of topological DSMs in spintronics.

cond-mat.mes-hall↗

arXiv2019

WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection

Wind power, as an alternative to burning fossil fuels, is abundant and inexhaustible. To fully utilize wind power, wind farms are usually located in areas of high altitude and facing serious ice conditions, which can lead to serious consequences. Quick detection of blade ice accretion is crucial for the maintenance of wind farms. Unlike traditional methods of installing expensive physical detectors on wind blades, data-driven approaches are increasingly popular for inspecting the wind turbine failures. In this work, we propose a wavelet enhanced autoencoder model (WaveletAE) to identify wind turbine dysfunction by analyzing the multivariate time series monitored by the SCADA system. WaveletAE is enhanced with wavelet detail coefficients to enforce the autoencoder to capture information from multiple scales, and the CNN-LSTM architecture is applied to learn channel-wise and temporal-wise relations. The empirical study shows that the proposed model outperforms other state-of-the-art time series anomaly detection methods for real-world blade icing detection.

cs.LG↗

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↗

arXiv2019

Nonlinear dynamics of forced baroclinic critical layers

In this paper, we study the forcing of baroclinic critical levels, which arise in stratified fluids with horizontal shear flow along the surfaces where the phase speed of a wave relative to the mean flow matches a natural internal wavespeed. Linear theory predicts the baroclinic critical layer dynamics is similar to that of a classical critical layer, characterized by the secular growth of flow perturbations over a region of decreasing width. By using matched asymptotic expansions, we construct a nonlinear baroclinic critical layer theory to study how the flow perturbation evolves once they enter the nonlinear regime. A key feature of the theory is that, because the location of the baroclinic critical layer is determined by the streamwise wavenumber, the nonlinear dynamics filters out harmonics and the modification to the mean flow controls the evolution. At late times, we show that the vorticity begins to focus into yet smaller regions whose width decreases exponentially with time, and that the addition of dissipative effects can arrest this focussing to create a drifting coherent structure. Jet-like defects in the mean horizontal velocity are the main outcome of the critical-layer dynamics.

physics.flu-dyn↗

arXiv2019

RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments

Semantic segmentation of surgical instruments plays a crucial role in robot-assisted surgery. However, accurate segmentation of cataract surgical instruments is still a challenge due to specular reflection and class imbalance issues. In this paper, an attention-guided network is proposed to segment the cataract surgical instrument. A new attention module is designed to learn discriminative features and address the specular reflection issue. It captures global context and encodes semantic dependencies to emphasize key semantic features, boosting the feature representation. This attention module has very few parameters, which helps to save memory. Thus, it can be flexibly plugged into other networks. Besides, a hybrid loss is introduced to train our network for addressing the class imbalance issue, which merges cross entropy and logarithms of Dice loss. A new dataset named Cata7 is constructed to evaluate our network. To the best of our knowledge, this is the first cataract surgical instrument dataset for semantic segmentation. Based on this dataset, RAUNet achieves state-of-the-art performance 97.71% mean Dice and 95.62% mean IOU.

cs.CV↗

arXiv2019

A Radio Signal Modulation Recognition Algorithm Based on Residual Networks and Attention Mechanisms

To solve the problem of inaccurate recognition of types of communication signal modulation, a RNN neural network recognition algorithm combining residual block network with attention mechanism is proposed. In this method, 10 kinds of communication signals with Gaussian white noise are generated from standard data sets, such as MASK, MPSK, MFSK, OFDM, 16QAM, AM and FM. Based on the original RNN neural network, residual block network is added to solve the problem of gradient disappearance caused by deep network layers. Attention mechanism is added to the network to accelerate the gradient descent. In the experiment, 16QAM, 2FSK and 4FSK are used as actual samples, IQ data frames of signals are used as input, and the RNN neural network combined with residual block network and attention mechanism is trained. The final recognition results show that the average recognition rate of real-time signals is over 93%. The network has high robustness and good use value.

eess.SP↗

arXiv2019

Two congruences concerning Apéry numbers

Let $n$ be a nonnegative integer. The $n$-th Apéry number is defined by $$ A_n:=\sum_{k=0}^n\binom{n+k}{k}^2\binom{n}{k}^2. $$ Z.-W. Sun ever investigated the congruence properties of Apéry numbers and posed some conjectures. For example, Sun conjectured that for any prime $p\geq7$ $$ \sum_{k=0}^{p-1}(2k+1)A_k\equiv p-\frac{7}{2}p^2H_{p-1}\pmod{p^6} $$ and for any prime $p\geq5$ $$ \sum_{k=0}^{p-1}(2k+1)^3A_k\equiv p^3+4p^4H_{p-1}+\frac{6}{5}p^8B_{p-5}\pmod{p^9}, $$ where $H_n=\sum_{k=1}^n1/k$ denotes the $n$-th harmonic number and $B_0,B_1,\ldots$ are the well-known Bernoulli numbers. In this paper we shall confirm these two conjectures.

math.NT↗

arXiv2019

Two-photon statistics of nonclassical radiation in the dissipative finite-size Dicke model

The nonclassical feature of photons in the open finite-size Dicke model is investigated via the two-photon correlation function. The quantum dressed master equation combined with the extended coherent photonic states is applied to analyze the dissipative dynamics of both the photons and qubits. The anti-bunching to bunching transition of photons is clearly observed by tuning the qubit-photon coupling strength. The optimal qubits number is unraveled to enhance the two-photon correlation function. Moreover, the temperature bias of thermal baths induces significant two-photon bunching signature with deep strong qubit-photon interaction.

quant-ph↗

arXiv2019

FfDL : A Flexible Multi-tenant Deep Learning Platform

Deep learning (DL) is becoming increasingly popular in several application domains and has made several new application features involving computer vision, speech recognition and synthesis, self-driving automobiles, drug design, etc. feasible and accurate. As a result, large scale on-premise and cloud-hosted deep learning platforms have become essential infrastructure in many organizations. These systems accept, schedule, manage and execute DL training jobs at scale. This paper describes the design, implementation and our experiences with FfDL, a DL platform used at IBM. We describe how our design balances dependability with scalability, elasticity, flexibility and efficiency. We examine FfDL qualitatively through a retrospective look at the lessons learned from building, operating, and supporting FfDL; and quantitatively through a detailed empirical evaluation of FfDL, including the overheads introduced by the platform for various deep learning models, the load and performance observed in a real case study using FfDL within our organization, the frequency of various faults observed including unanticipated faults, and experiments demonstrating the benefits of various scheduling policies. FfDL has been open-sourced.

cs.DC↗

arXiv2019

Formation control for multiple agents with local measurements: continuous-time and sampled-data-based cases

We study the formation control problem for a group of mobile agents in a plane, in which each agent is modeled as a kinematic point and can only use the local measurements in its local frame. The agents are required to maintain a geometric pattern while keeping a desired distance to a static/moving target. The prescribed formation is a general one which can be any geometric pattern, and the neighboring relationship of the N-agent system only has the requirement of containing a directed spanning tree. To solve the formation control problem, a distributed controller is proposed based on the idea of decoupled design. One merit of the controller is that it only uses each agent's local measurements in its local frame, so that a practical issue that the lack of a global coordinate frame or a common reference direction for real multi-robot systems is successfully solved. Considering another practical issue of real robotic applications that sampled data is desirable instead of continuous-time signals, the sampled-data based controller is developed. Theoretical analysis of the convergence to the desired formation is provided for the multi-agent system under both the continuous-time controller with a static/moving target and the sampled-data based one with a static target. Numerical simulations are given to show the effectiveness and performance of the controllers.

math.OC↗

arXiv2019

A Sparkler in the Fireworks Galaxy: Discovery of an Ultraluminous X-ray Transient with a Strong Oxygen Line in NGC 6946

We discovered and studied an ultraluminous X-ray source (CXOU J203451.1+601043) that appeared in the spiral galaxy NGC 6946 at some point between 2008 February and 2012 May, and has remained at luminosities $\approx$2-4 $\times 10^{39}$ erg s$^{-1}$ in all observations since then. Our spectral modelling shows that the source is generally soft, but with spectral variability from epoch to epoch. Using standard empirical categories of the ultraluminous regimes, we find that CXOU J203451.1+601043 was consistent with a broadened disk state in 2012, but was in a transitional state approaching the super-soft regime in 2016, with substantial down-scattering of the hard photons (similar, for example, to the ultraluminous X-ray source in NGC 55). It has since hardened again in 2018-2019 without any significant luminosity change. The most outstanding property of CXOU J203451.1+601043 is a strong emission line at an energy of of $(0.66 \pm 0.01)$ keV, with equivalent width of $\approx$100 eV, and de-absorbed line luminosity of $\approx$2 $\times 10^{38}$ erg s$^{-1}$, seen when the continuum spectrum was softest. We identify the line as OVIII Ly$α$ (rest frame energy of 0.654 keV); we interpret it as a strong indicator of a massive outflow. Our finding supports the connection between two independent observational signatures of the wind in super-Eddington sources: a lower temperature of the Comptonized component, and the presence of emission lines in the soft X-ray band. We speculate that the donor star is oxygen-rich: a CO or O-Ne-Mg white dwarf in an ultracompact binary. If that is the case, the transient behaviour of CXOU J203451.1+601043 raises intriguing theoretical questions.

astro-ph.HE↗

arXiv2019

Repeated out of Sample Fusion in the Estimation of Small Tail Probabilities

Often, it is required to estimate the probability that a quantity such as toxicity level, plutonium, temperature, rainfall, damage, wind speed, wave size, earthquake magnitude, risk, etc., exceeds an unsafe high threshold. The probability in question is then very small. To estimate such a probability, information is needed about large values of the quantity of interest. However, in many cases, the data only contain values below or even far below the designated threshold, let alone exceedingly large values. It is shown that by repeated fusion of the data with externally generated random data, more information about small tail probabilities is obtained with the aid of certain new statistical functions. This provides relatively short, yet reliable interval estimates based on moderately large samples. A comparison of the approach with a method from extreme values theory (Peaks over Threshold, or POT), using both artificial and real data, points to the merit of repeated out of sample fusion.

stat.ME↗