arXiv subjects

Wei Li

Publications and source records attributed to Wei Li.

At least 1,171 records · Page 65Linked to original sources

arXiv2019

Insight-HXMT observations of Swift J0243.6+6124 during its 2017-2018 outburst

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\it the Hard X-ray Modulation Telescope} ({\it Insight-\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to $\rm 150~keV$. In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with $B\rm \sim 10^{13}~G$, $D\rm \sim 6~kpc$ and peak luminosity of $\rm >10^{39}~erg~s^{-1}$ which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.

astro-ph.HE↗

arXiv2019

Two-Gap Superconductivity in CaFe_{0.88}Co_{0.12}AsF Revealed by Temperature Dependence of the Lower Critical Field H_{c1}^c(T)

Gap symmetry and structure are crucial issues in understanding the superconducting mechanism of unconventional superconductors. Here we report an in-depth investigation on the out-of-plane lower critical field $H_{c1}^{c}$ of fluorine-based 1111 system superconductor CaFe$_{0.88}$Co$_{0.12}$AsF with $T_c$ = 21 K. A pronounced two-gap feature is revealed by the kink in the temperature dependent $H_{c1}^c(T)$ curve. The magnitudes of the two gaps are determined to be $Δ_1$ = 0.86 meV and $Δ_2$ = 4.48 meV, which account for 74% and 26% of the total superfluid density respectively. Our results suggest that the local antiferromagnetic exchange pairing picture is favored compared to the Fermi surface nesting scenario.

cond-mat.supr-con↗

arXiv2019

Multiple gaps revealed by low temperature specific heat in the 1111-type CaFe_{0.88}Co_{0.12}AsF single crystals

Low-temperature specific heat (SH) is measured on the 1111-type CaFe_{0.88}Co_{0.12}AsF single crystals under different magnetic fields. A clear SH jump with the height ΔC/T|_Tc = 10.4 mJ/mol K^2 was observed at the superconducting transition temperature T_c. The electronic SH coefficient Δγ(B) increases linearly with the field below 5 T and a kink is observed around 5 T, indicating a multi-gap feature in the present system. Such a sign is also reflected in the Tc-B data. A detailed analysis shows that this behavior can be interpreted in terms of a two-gap scenario with the ratio Δ_L=Δ_S = 2:8-4:5.

cond-mat.supr-con↗

arXiv2019

Deformable Tube Network for Action Detection in Videos

We address the problem of spatio-temporal action detection in videos. Existing methods commonly either ignore temporal context in action recognition and localization, or lack the modelling of flexible shapes of action tubes. In this paper, we propose a two-stage action detector called Deformable Tube Network (DTN), which is composed of a Deformation Tube Proposal Network (DTPN) and a Deformable Tube Recognition Network (DTRN) similar to the Faster R-CNN architecture. In DTPN, a fast proposal linking algorithm (FTL) is introduced to connect region proposals across frames to generate multiple deformable action tube proposals. To perform action detection, we design a 3D convolution network with skip connections for tube classification and regression. Modelling action proposals as deformable tubes explicitly considers the shape of action tubes compared to 3D cuboids. Moreover, 3D convolution based recognition network can learn temporal dynamics sufficiently for action detection. Our experimental results show that we significantly outperform the methods with 3D cuboids and obtain the state-of-the-art results on both UCF-Sports and AVA datasets.

cs.CV↗

arXiv2019

The Prototype of Decentralized Multilateral Co-Governing Post-IP Internet Architecture and Its Testing on Operator Networks

The Internet has become the most important infrastructure of modern society, while the existing IP network is unable to provide high-quality service. The unilateralism IP network is unable to satisfy the Co-managing and Co-governing demands to Cyberspace for most Nations in the world as well. Facing this challenge, we propose a novel Decentralized Multilateral Co-Governing Post-IP Internet architecture. To verify its effectiveness, we develop the prototype on the operator's networks including China Mainland, Hong Kong, and Macao. The experiments and testing results show that this architecture is feasible for co-existing of Content-Centric Networking and IP network, and it might become a Chinese Solution to the world.

cs.NI↗

arXiv2019

FPGA-based real-time autocorrelator and its application in dynamic light scattering

Digital correlators play a significant role in dynamic light scattering (DLS) technology, which characterizes particle size distribution. We present a field programmable gate array (FPGA)-based digital correlator that can be applied to process DLS data. To satisfy the DLS requirements in the FPGA logic with limited resources, a multiple lag time period (multi-τ ) method is employed that does not require storing the full data set in memory. Moreover, the device directly accepts the transistor-transistor logic (TTL) signal from the photon counting detector by measuring the time intervals between photon events and calculates the autocorrelation functions in real time. Furthermore, we derive estimates for the error arising from the use of the multi-τ correlator. We implement all the necessary operations in a single Xilinx FPGA chip with a lag time from 10 ns to 45 min, including a highly optimized photon counter.

eess.SP↗

arXiv2019

Monotonic Infinite Lookback Attention for Simultaneous Machine Translation

Simultaneous machine translation begins to translate each source sentence before the source speaker is finished speaking, with applications to live and streaming scenarios. Simultaneous systems must carefully schedule their reading of the source sentence to balance quality against latency. We present the first simultaneous translation system to learn an adaptive schedule jointly with a neural machine translation (NMT) model that attends over all source tokens read thus far. We do so by introducing Monotonic Infinite Lookback (MILk) attention, which maintains both a hard, monotonic attention head to schedule the reading of the source sentence, and a soft attention head that extends from the monotonic head back to the beginning of the source. We show that MILk's adaptive schedule allows it to arrive at latency-quality trade-offs that are favorable to those of a recently proposed wait-k strategy for many latency values.

cs.CL↗

arXiv2019

Protein contact map prediction using bi-directional recurrent neural network

Given native 2D contact map, protein 3D structure could be reconstructed with accuracy of 2A or better, and such reconstruction is a feasible computational approach for protein folding problem. The prediction accuracy from traditional methods is generally too poor to useful, but the recent deep learning model has significantly improved the accuracy. In this study, we proposed a neural network model comprising a bi-directional recurrent neural network and artificial neural network. Over the non-redundant database of all available protein 3D structures in Protein Data Bank, this deep learning model achieved an accuracy of 0.80, much higher than those of previous models. This study represents a major breakthrough in protein 2D contact map prediction and likely a major step forward for the protein folding problem.

q-bio.BM↗

arXiv2019

A Sustainable Multi-modal Multi-layer Emotion-aware Service at the Edge

Limited by the computational capabilities and battery energy of terminal devices and network bandwidth, emotion recognition tasks fail to achieve good interactive experience for users. The intolerable latency for users also seriously restricts the popularization of emotion recognition applications in the edge environments such as fatigue detection in auto-driving. The development of edge computing provides a more sustainable solution for this problem. Based on edge computing, this article proposes a multi-modal multi-layer emotion-aware service (MULTI-EASE) architecture that considers user's facial expression and voice as a multi-modal data source of emotion recognition, and employs the intelligent terminal, edge server and cloud as multi-layer execution environment. By analyzing the average delay of each task and the average energy consumption at the mobile device, we formulate a delay-constrained energy minimization problem and perform a task scheduling policy between multiple layers to reduce the end-to-end delay and energy consumption by using an edge-based approach, further to improve the users' emotion interactive experience and achieve energy saving in edge computing. Finally, a prototype system is also implemented to validate the architecture of MULTI-EASE, the experimental results show that MULTI-EASE is a sustainable and efficient platform for emotion analysis applications, and also provide a valuable reference for dynamic task scheduling under MULTI-EASE architecture.

cs.NI↗

arXiv2019

Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model

Automatic article commenting is helpful in encouraging user engagement and interaction on online news platforms. However, the news documents are usually too long for traditional encoder-decoder based models, which often results in general and irrelevant comments. In this paper, we propose to generate comments with a graph-to-sequence model that models the input news as a topic interaction graph. By organizing the article into graph structure, our model can better understand the internal structure of the article and the connection between topics, which makes it better able to understand the story. We collect and release a large scale news-comment corpus from a popular Chinese online news platform Tencent Kuaibao. Extensive experiment results show that our model can generate much more coherent and informative comments compared with several strong baseline models.

cs.CL↗

arXiv2019

Giant magnetic quantum oscillations in the thermal conductivity of TaAs: Indications of chiral zero sound

Charge transport of topological semimetals has been in the focus of intensive investigations because of their non-trivial band topology. Heat transport of these materials, on the other hand, is largely unexplored and remains elusive. Here we report on an observation of unprecedented, giant magnetic quantum oscillations of thermal conductivity in the prototypical Weyl semimetal TaAs. The oscillations are antiphase with the quantum oscillating electronic density of states of a Weyl pocket, and their amplitudes amount to two orders of magnitude of the estimation based on the Wiedemann-Franz law. Our analyses show that all the conventional heat-transport mechanisms through diffusions of propagating electrons, phonons and electron-hole bipolar excitations, are far inadequate to account for these phenomena. Taking further experimental facts that the parallel field configuration favors much higher magneto-thermal conductivity, we propose that the newly proposed chiral zero sound provides a reasonable explanation to these exotic phenomena. More work focusing on other topological semimetals along the same line is badly called for.

cond-mat.mtrl-sci↗

arXiv2019

Multiple Policy Value Monte Carlo Tree Search

Many of the strongest game playing programs use a combination of Monte Carlo tree search (MCTS) and deep neural networks (DNN), where the DNNs are used as policy or value evaluators. Given a limited budget, such as online playing or during the self-play phase of AlphaZero (AZ) training, a balance needs to be reached between accurate state estimation and more MCTS simulations, both of which are critical for a strong game playing agent. Typically, larger DNNs are better at generalization and accurate evaluation, while smaller DNNs are less costly, and therefore can lead to more MCTS simulations and bigger search trees with the same budget. This paper introduces a new method called the multiple policy value MCTS (MPV-MCTS), which combines multiple policy value neural networks (PV-NNs) of various sizes to retain advantages of each network, where two PV-NNs f_S and f_L are used in this paper. We show through experiments on the game NoGo that a combined f_S and f_L MPV-MCTS outperforms single PV-NN with policy value MCTS, called PV-MCTS. Additionally, MPV-MCTS also outperforms PV-MCTS for AZ training.

cs.AI↗

arXiv2019

Thermal Tensor Network Simulations of the Heisenberg Model on the Bethe Lattice

We have extended the canonical tree tensor network (TTN) method, which was initially introduced to simulate the zero-temperature properties of quantum lattice models on the Bethe lattice, to finite temperature simulations. By representing the thermal density matrix with a canonicalized tree tensor product operator, we optimize the TTN and accurately evaluate the thermodynamic quantities, including the internal energy, specific heat, and the spontaneous magnetization, etc, at various temperatures. By varying the anisotropic coupling constant $Δ$, we obtain the phase diagram of the spin-1/2 Heisenberg XXZ model on the Bethe lattice, where three kinds of magnetic ordered phases, namely the ferromagnetic, XY and antiferromagnetic ordered phases, are found in low temperatures and separated from the high-$T$ paramagnetic phase by a continuous thermal phase transition at $T_c$. The XY phase is separated from the other two phases by two first-order phase transition lines at the symmetric coupling points $ Δ=\pm 1$. We have also carried out a linear spin wave calculation on the Bethe lattice, showing that the low-energy magnetic excitations are always gapped, and find the obtained magnon gaps in very good agreement with those estimated from the TTN simulations. Despite the gapped excitation spectrum, Goldstone-like transverse fluctuation modes, as a manifestation of spontaneous continuous symmetry breaking, are observed in the ordered magnetic phases with $|Δ|\le 1$. One remarkable feature there is that the prominent transverse correlation length reaches $ξ_c=1/\ln{(z-1)}$ for $T\leq T_c$, the maximal value allowed on a $z$-coordinated Bethe lattice.

cond-mat.str-el↗

arXiv2019

Photonic refrigeration from time-modulated thermal emission

Active photonic cooling is of significant importance to realize robust, compact, vibration-free, all-solid-state refrigeration. Currently proposed photonic cooling approaches are based on luminescence and impose stringent requirements on luminescence efficiency. We propose a new photonic cooling mechanism arising from temporal modulation of thermal emission. We show that this mechanism has a high thermodynamic performance that can approach the Carnot limit and yet does not rely on luminescence. Further, our work opens exciting new avenues in active, time-modulated control of thermal emission for cooling and energy harvesting applications.

physics.optics↗

arXiv2019

Multiple Pulses Phase-matching Quantum Key Distribution

We propose a multiple pulses phase-matching quantum key distribution protocol (MPPM-QKD) to exceed the linear key rate bound and to achieve higher error tolerance. In our protocol, Alice and Bob generate at first their own train pulses (each train should contain L pulses) as well as random bit sequences, and also encode each pulse of their trains with a randomized phase and a modulation phase. As the next step, both encoded trains are simultaneously sent to Charlie, who performs an interference detection and may be also an eavesdropper. After a successful detection is announced by Charlie, Alice and Bob open the randomized phase of each pulse and keep only communications when the summation of the difference randomized phases at two success detection's time-stamps for Alice and Bob are equal to 0 or pi. Thereafter, Alice and Bob compute the sifted key with the time-stamps. The above procedure is repeated until both Alice and Bob achieve sufficiently long sifted keys. We can also show that the secret key rate of the proposed QKD protocol can beat the rate-loss limit of so far known QKD protocols when the transmission distance is greater than 250 km. Moreover, the proposed protocol has a higher error tolerance, approximately 24%, when the transmission distance is 50 km and L = 128. The secret key rate and the transmission distance of our protocol are superior to that of the round-robin differential-phase-shift quantum key distribution protocol [6], and also of the measurement-device-independent quantum key distribution protocol [4], and the secret key rate performance is better in both cases than that of phase-matching quantum key distribution when bit train length is greater than 32.

quant-ph↗

arXiv2019

The electrochemical storage mechanism in oxy-hydroxyfluorinated anatase for sodium-ion batteries

Replacing lithium ions with sodium ions as the charge carriers in rechargeable batteries can induce noticeable differences in the electrochemical storage mechanisms of electrode materials. Many material parameters, such as particle size, morphology, and the presence of defects, are known to further affect the storage mechanism. Here, we report an investigation of how the introduction of titanium vacancies into anatase TiO2 affects the sodium storage mechanism. From pair distribution function analysis, we observe that sodium ions are inserted into titanium vacancies at the early stage of the discharge process. This is supported by density functional theory calculations, which predict that sodium insertion is more favourable at vacancies than at interstitial sites. Our calculations also show that the intercalation voltage is sensitive to the anion coordination environment of the vacancy. Sodiation to higher concentrations induces a phase transition toward a disordered rhombohedral structure, similar to that observed in defect-free TiO2. Finally, we find that the X-ray diffraction pattern of the rhombohedral phase drastically changes depending on the composition and degree of disorder, providing further comprehension on the sodium storage mechanism of anatase.

physics.chem-ph↗

arXiv2019

p-adic CFT is a holographic tensor network

The p-adic AdS/CFT correspondence relates a CFT living on the p-adic numbers to a system living on the Bruhat-Tits tree. Modifying our earlier proposal for a tensor network realization of p-adic AdS/CFT, we prove that the path integral of a p-adic CFT is equivalent to a tensor network on the Bruhat-Tits tree, in the sense that the tensor network reproduces all correlation functions of the p-adic CFT. Our rules give an explicit tensor network for any p-adic CFT (as axiomatized by Melzer), and can be applied not only to the p-adic plane, but also to compute any correlation functions on higher genus p-adic curves. Finally, we apply them to define and study RG flows in p-adic CFTs, establishing in particular that any IR fixed point is itself a p-adic CFT.

hep-th↗

arXiv2019

Wilson line networks in $p$-adic AdS/CFT

The $p$-adic AdS/CFT is a holographic duality based on the $p$-adic number field $\mathbb{Q}_p$. For a $p$-adic CFT living on $\mathbb{Q}_p$ and with complex-valued fields, the bulk theory is defined on the Bruhat-Tits tree, which can be viewed as the bulk dual of $\mathbb{Q}_p$. We propose that bulk theory can be formulated as a lattice gauge theory of PGL$(2,\mathbb{Q}_p)$ on the Bruhat-Tits tree, and show that the Wilson line networks in this lattice gauge theory can reproduce all the correlation functions of the boundary $p$-adic CFT.

hep-th↗