arXiv subjects

Jie Zhang

Publications and source records attributed to Jie Zhang.

At least 1,027 records · Page 57Linked to original sources

arXiv2018

Locating earthquakes with a network of seismic stations via a deep learning method

The accurate and automated determination of earthquake locations is still a challenging endeavor. However, such information is critical for monitoring seismic activity and assessing potential hazards in real time. Recently, a convolutional neural network was applied to detect earthquakes from single-station waveforms and approximately map events across several large surface areas. In this study, we locate 194 earthquakes induced during oil and gas operations in Oklahoma, USA, within an error range of approximately 4.9 km on average to the epicenter and 1.0 km to the depth in catalogs with data from 30 network stations by applying the fully convolutional network. The network is trained by 1,013 historic events, and the output is a 3D volume of the event location probability in the Earth. The trained system requires approximately one hundredth of a second to locate an event without the need for any velocity model or human interference.

physics.geo-ph↗

arXiv2018

Semileptonic decays of $B_c$ meson to $P$-wave charmonium states

Inspired by a series of unexpected measurements of semileptonic decays mediated via $b\rightarrow c $ charged current interactions, we explore semileptonic $B_c$ decays to the four lightest $P$-wave charmonium states, $χ_{c0}, χ_{c1}, χ_{c2}, h_c$, by the recently developed improved perturbative QCD formalism, in which the charm quark mass effect is included both in the Sudakov factor and the hard kernels. We first directly evaluate the concerned transition form factors with vector and axial-vector currents in the region of small momentum transfer squared, and then recast them to the full kinematical region by adopting the exponential parametrization. The obtained form factors are used to evaluate the semileptonic decay branching ratios, which can reach the order of $10^{-3}$, letting the corresponding measurement appear feasible. For a better analysis, a comparison of our results with the predictions of other models is provided. We also present the ratios between the tau and light lepton branching ratios and the polarization contributions in the relevant processes, which still need experimental tests in the ongoing and forthcoming experiments. Any significant deviations from the Standard Model results may provide some hints of new physics effects.

hep-ph↗

arXiv2018

Energy Efficient and Fair Resource Allocation for LTE-Unlicensed Uplink Networks: A Two-sided Matching Approach with Partial Information

LTE-Unlicensed (LTE-U) has recently attracted worldwide interest to meet the explosion in cellular traffic data. By using carrier aggregation (CA), licensed and unlicensed bands are integrated to enhance transmission capacity while maintaining reliable and predictable performance. As there may exist other conventional unlicensed band users, such as Wi-Fi users, LTE-U users have to share the same unlicensed bands with them. Thus, an optimized resource allocation scheme to ensure the fairness between LTE-U users and conventional unlicensed band users is critical for the deployment of LTE-U networks. In this paper, we investigate an energy efficient resource allocation problem in LTE-U coexisting with other wireless networks, which aims at guaranteeing fairness among the users of different radio access networks (RANs). We formulate the problem as a multi-objective optimization problem and propose a semi-distributed matching framework with a partial information-based algorithm to solve it. We demonstrate our contributions with simulations in which various network densities and traffic load levels are considered.

cs.IT↗

arXiv2018

Hardness Results for Consensus-Halving

We study the consensus-halving problem of dividing an object into two portions, such that each of $n$ agents has equal valuation for the two portions. The $ε$-approximate consensus-halving problem allows each agent to have an $ε$ discrepancy on the values of the portions. We prove that computing $ε$-approximate consensus-halving solution using $n$ cuts is in PPA, and is PPAD-hard, where $ε$ is some positive constant; the problem remains PPAD-hard when we allow a constant number of additional cuts. It is NP-hard to decide whether a solution with $n-1$ cuts exists for the problem. As a corollary of our results, we obtain that the approximate computational version of the Continuous Necklace Splitting Problem is PPAD-hard when the number of portions $t$ is two.

cs.GT↗

arXiv2018

A Study of a Compound Solar Eruption with Two Consecutive Erupting Magnetic Structures

We report a study of a compound solar eruption that was associated with two consecutively erupting magnetic structures and correspondingly two distinct peaks, during impulsive phase, of an M-class flare (M8.5). Simultaneous multi-viewpoint observations from $\textit{SDO}$, $\textit{GOES}$ and $\textit{STEREO-A}$ show that this compound eruption originated from two pre-existing sigmoidal magnetic structures lying along the same polarity inversion line. Observations of the associated pre-existing filaments further show that these magnetic structures are lying one on top of the other, separated by 12 Mm in height, in a so-called "double-decker" configuration. The high-lying magnetic structure became unstable and erupted first, appearing as an expanding hot channel seen at extreme ultraviolet wavelengths. About 12 minutes later, the low-lying structure also started to erupt and moved at an even faster speed compared to the high-lying one. As a result, the two erupting structures interacted and merged with each other, appearing as a single coronal mass ejection in the outer corona. We find that the double-decker configuration is likely caused by the persistent shearing motion and flux cancellation along the source active region's strong-gradient polarity inversion line. The successive destabilization of these two separate but closely spaced magnetic structures, possibly in the form of magnetic flux ropes, led to a compound solar eruption. The study of the compound eruption provides a unique opportunity to reveal the formation process, initiation, and evolution of complex eruptive structures in solar active regions.

astro-ph.SR↗

arXiv2018

Few-femtosecond Electron Beam with THz-frequency Wakefield-driven Compression

We propose and demonstrate a novel method to produce few-femtosecond electron beam with relatively low timing jitter. In this method a relativistic electron beam is compressed from about 150 fs (rms) to about 7 fs (rms, upper limit) with the wakefield at THz frequency produced by a leading drive beam in a dielectric tube. By imprinting the energy chirp in a passive way, we demonstrate through laser-driven THz streaking technique that no additional timing jitter with respect to an external laser is introduced in this bunch compression process, a prominent advantage over the conventional method using radio-frequency bunchers. We expect that this passive bunching technique may enable new opportunities in many ultrashort-beam based advanced applications such as ultrafast electron diffraction and plasma wakefield acceleration.

physics.acc-ph↗

arXiv2018

Structural and Topological Nature of Plasticity in Sheared Granular Materials

Upon mechanical loading, granular materials yield and undergo plastic deformation. The nature of plastic deformation is essential for the development of the macroscopic constitutive models and the understanding of shear band formation. However, we still do not fully understand the microscopic nature of plastic deformation in disordered granular materials. Here we used synchrotron X-ray tomography technique to track the structural evolutions of three-dimensional granular materials under shear. We establish that highly distorted coplanar tetrahedra are the structural defects responsible for microscopic plasticity in disordered granular packings. The elementary plastic events occur through flip events which correspond to a neighbor switching process among these coplanar tetrahedra (or equivalently as the rotation motion of 4-ring disclinations). These events are discrete in space and possess specific orientations with the principal stress direction.

cond-mat.soft↗

arXiv2018

The MicroTCA fast control board for generic control and data acquisition applications in HEP experiments

To provide the generic clock, trigger and control function and fulfill the data transmission performance requirement in high energy physics (HEP) experiments, a MicroTCA Fast Control board (uFC) was developed based on the Advanced Mezzanine Card (AMC) specification. Built around the Xilinx Kintex-7 FPGA, the uFC provides users with a platform with data memory, reference clock, trigger and SFP+ (Small Form-factor Pluggable) connections that are required in general experiment. In addition, it has access to two on-board FPGA Mezzanine Card (FMC) sockets with a large array of configurable I/O and high-speed links up to 10 Gbps. This paper presents test results from the first set of pre-production prototypes and reports on the application in High Energy Photon Source in China.

physics.ins-det↗

arXiv2018

A readout method based on 10 Gigabit Ethernet for Sipixel detector

With the rapid development of network protocol, TCP/IP has been widely applied in various OS systems because of its advantages of high-speed network transmission and standardization. Furthermore, TCP/IP has the functions of retransmission and flow control, so it can ensure data's security and stability. In recent years, as a transmission Field-bus, it is also widely used in high-energy physics detectors. This article describes a readout method using 10 gigabit network processor applied in silicon pixel detector which is a pixel detector designed for the High Energy Photon Source (HEPS) in China. The PHY layer and the MAC layer of this hardware are both instantiated in FPGA. The logic of hardware can process and read out the data of the detectors. Meanwhile, it wraps up data and send them to TOE (TCP Offload Engine). A kind of bus control protocol interface is also provided, which can facilitate the host computer to read and write the specific register directly through the UDP protocol. Only a piece of FPGA can complete the processing of the TCP and UDP packets. It is important for the miniaturization of the detectors.

cs.NI↗

arXiv2018

Spectral Network Embedding: A Fast and Scalable Method via Sparsity

Network embedding aims to learn low-dimensional representations of nodes in a network, while the network structure and inherent properties are preserved. It has attracted tremendous attention recently due to significant progress in downstream network learning tasks, such as node classification, link prediction, and visualization. However, most existing network embedding methods suffer from the expensive computations due to the large volume of networks. In this paper, we propose a $10\times \sim 100\times$ faster network embedding method, called Progle, by elegantly utilizing the sparsity property of online networks and spectral analysis. In Progle, we first construct a \textit{sparse} proximity matrix and train the network embedding efficiently via sparse matrix decomposition. Then we introduce a network propagation pattern via spectral analysis to incorporate local and global structure information into the embedding. Besides, this model can be generalized to integrate network information into other insufficiently trained embeddings at speed. Benefiting from sparse spectral network embedding, our experiment on four different datasets shows that Progle outperforms or is comparable to state-of-the-art unsupervised comparison approaches---DeepWalk, LINE, node2vec, GraRep, and HOPE, regarding accuracy, while is $10\times$ faster than the fastest word2vec-based method. Finally, we validate the scalability of Progle both in real large-scale networks and multiple scales of synthetic networks.

cs.SI↗

arXiv2018

Microwave Photocurrent from the Helical Edge state of InAs/GaInSb Bilayers

We measure microwave photocurrent in devices made from InAs/GaInSb bilayers where both insulating bulk state and conducting edge state were observed in the inverted-band regime, consistent with the theoretical prediction for a quantum spin Hall (QSH) insulator. It has been theoretically proposed that microwave photocurrent could be a unique probe in studying the properties of QSH edge states. To distinguish possible photoresponse between bulk state and helical edge state, we prepare Hall bar and Corbino disk from the same wafer. Results show that the Corbino disk samples have a negligible photocurrent in the bulk gap while clear photocurrent signals from the Hall bar samples are observed. This finding suggests that the photocurrent may carry information concerning the electronic properties of the edge states.

cond-mat.mes-hall↗

arXiv2018

Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices

Recurrent neural networks (RNNs) achieve cutting-edge performance on a variety of problems. However, due to their high computational and memory demands, deploying RNNs on resource constrained mobile devices is a challenging task. To guarantee minimum accuracy loss with higher compression rate and driven by the mobile resource requirement, we introduce a novel model compression approach DirNet based on an optimized fast dictionary learning algorithm, which 1) dynamically mines the dictionary atoms of the projection dictionary matrix within layer to adjust the compression rate 2) adaptively changes the sparsity of sparse codes cross the hierarchical layers. Experimental results on language model and an ASR model trained with a 1000h speech dataset demonstrate that our method significantly outperforms prior approaches. Evaluated on off-the-shelf mobile devices, we are able to reduce the size of original model by eight times with real-time model inference and negligible accuracy loss.

cs.LG↗

arXiv2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing

Incentive mechanisms for crowdsourcing are designed to incentivize financially self-interested workers to generate and report high-quality labels. Existing mechanisms are often developed as one-shot static solutions, assuming a certain level of knowledge about worker models (expertise levels, costs of exerting efforts, etc.). In this paper, we propose a novel inference aided reinforcement mechanism that learns to incentivize high-quality data sequentially and requires no such prior assumptions. Specifically, we first design a Gibbs sampling augmented Bayesian inference algorithm to estimate workers' labeling strategies from the collected labels at each step. Then we propose a reinforcement incentive learning (RIL) method, building on top of the above estimates, to uncover how workers respond to different payments. RIL dynamically determines the payment without accessing any ground-truth labels. We theoretically prove that RIL is able to incentivize rational workers to provide high-quality labels. Empirical results show that our mechanism performs consistently well under both rational and non-fully rational (adaptive learning) worker models. Besides, the payments offered by RIL are more robust and have lower variances compared to the existing one-shot mechanisms.

cs.GT↗

arXiv2018

CIAO: Cache Interference-Aware Throughput-Oriented Architecture and Scheduling for GPUs

A modern GPU aims to simultaneously execute more warps for higher Thread-Level Parallelism (TLP) and performance. When generating many memory requests, however, warps contend for limited cache space and thrash cache, which in turn severely degrades performance. To reduce such cache thrashing, we may adopt cache locality-aware warp scheduling which gives higher execution priority to warps with higher potential of data locality. However, we observe that warps with high potential of data locality often incurs far more cache thrashing or interference than warps with low potential of data locality. Consequently, cache locality-aware warp scheduling may undesirably increase cache interference and/or unnecessarily decrease TLP. In this paper, we propose Cache Interference-Aware throughput-Oriented (CIAO) on-chip memory architecture and warp scheduling which exploit unused shared memory space and take insight opposite to cache locality-aware warp scheduling. Specifically, CIAO on-chip memory architecture can adaptively redirect memory requests of severely interfering warps to unused shared memory space to isolate memory requests of these interfering warps from those of interfered warps. If these interfering warps still incur severe cache interference, CIAO warp scheduling then begins to selectively throttle execution of these interfering warps. Our experiment shows that CIAO can offer 54% higher performance than prior cache locality-aware scheduling at a small chip cost.

cs.AR↗

arXiv2018

THz pulses over 50 millijoules generated from relativistic picosecond laser-plasma interactions

Ultrahigh-power terahertz (THz) radiation sources are essential for many applications, such as nonlinear THz physics, THz-wave based compact accelerators, etc. However, until now none of THz sources reported, whether based upon large-scale accelerators or high power lasers, have produced THz pulses with energies above the millijoule (mJ) barrier. Here we report on the efficient generation of low-frequency (<3 THz) THz pulses with unprecedentedly high energies over 50 mJ. The THz radiation is produced by coherent transition radiation of a picosecond laser-accelerated ultra-bright bunch of relativistic electrons from a solid target. Such high energy THz pulses can not only trigger various nonlinear dynamics in matter, but also open up a new research field of relativistic THz optics.

physics.plasm-ph↗

arXiv2018

An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending

Solar forecasting accuracy is affected by weather conditions, and weather awareness forecasting models are expected to improve the performance. However, it may not be available and reliable to classify different forecasting tasks by using only meteorological weather categorization. In this paper, an unsupervised clustering-based (UC-based) solar forecasting methodology is developed for short-term (1-hour-ahead) global horizontal irradiance (GHI) forecasting. This methodology consists of three parts: GHI time series unsupervised clustering, pattern recognition, and UC-based forecasting. The daily GHI time series is first clustered by an Optimized Cross-validated ClUsteRing (OCCUR) method, which determines the optimal number of clusters and best clustering results. Then, support vector machine pattern recognition (SVM-PR) is adopted to recognize the category of a certain day using the first few hours' data in the forecasting stage. GHI forecasts are generated by the most suitable models in different clusters, which are built by a two-layer Machine learning based Multi-Model (M3) forecasting framework. The developed UC-based methodology is validated by using 1-year of data with six solar features. Numerical results show that (i) UC-based models outperform non-UC (all-in-one) models with the same M3 architecture by approximately 20%; (ii) M3-based models also outperform the single-algorithm machine learning (SAML) models by approximately 20%.

cs.LG↗

arXiv2018

Terahertz streaking of few-femtosecond relativistic electron beams

Streaking of photoelectrons with optical lasers has been widely used for temporal characterization of attosecond extreme ultraviolet pulses. Recently, this technique has been adapted to characterize femtosecond x-ray pulses in free-electron lasers with the streaking imprinted by farinfrared and Terahertz (THz) pulses. Here, we report successful implementation of THz streaking for time-stamping of an ultrashort relativistic electron beam of which the energy is several orders of magnitude higher than photoelectrons. Such ability is especially important for MeV ultrafast electron diffraction (UED) applications where electron beams with a few femtosecond pulse width may be obtained with longitudinal compression while the arrival time may fluctuate at a much larger time scale. Using this laser-driven THz streaking technique, the arrival time of an ultrashort electron beam with 6 fs (rms) pulse width has been determined with 1.5 fs (rms) accuracy. Furthermore, we have proposed and demonstrated a non-invasive method for correction of the timing jitter with femtosecond accuracy through measurement of the compressed beam energy, which may allow one to advance UED towards sub-10 fs frontier far beyond the ~100 fs (rms) jitter.

physics.acc-ph↗

arXiv2018

Modeling and Analysis of MPTCP Proxy-based LTE-WLAN Path Aggregation

Long Term Evolution (LTE)-Wireless Local Area Network (WLAN) Path Aggregation (LWPA) based on Multi-path Transmission Control Protocol (MPTCP) has been under standardization procedure as a promising and cost-efficient solution to boost Downlink (DL) data rate and handle the rapidly increasing data traffic. This paper aims at providing tractable analysis for the DL performance evaluation of large-scale LWPA networks with the help of tools from stochastic geometry. We consider a simple yet practical model to determine under which conditions a native WLAN Access Point (AP) will work under LWPA mode to help increasing the received data rate. Using stochastic spatial models for the distribution of WLAN APs and LTE Base Stations (BSs), we analyze the density of active LWPA-mode WiFi APs in the considered network model, which further leads to closed-form expressions on the DL data rate and area spectral efficiency (ASE) improvement. Our numerical results illustrate the impact of different network parameters on the performance of LWPA networks, which can be useful for further performance optimization.

cs.NI↗