W. Lu - Tsinghua University

W. Lu
Are you W. Lu?

Claim your profile, edit publications, add additional information:

Contact Details

W. Lu
Tsinghua University

Pubs By Year

External Links

Pub Categories

Physics - Mesoscopic Systems and Quantum Hall Effect (7)
High Energy Astrophysical Phenomena (6)
Physics - Materials Science (5)
Mathematics - Differential Geometry (3)
Physics - Optics (3)
Computer Science - Information Retrieval (3)
Physics - Plasma Physics (3)
Computer Science - Learning (2)
Mathematics - Information Theory (2)
Computer Science - Information Theory (2)
Physics - Computational Physics (2)
Physics - Superconductivity (2)
Computer Science - Computer Vision and Pattern Recognition (2)
Physics - Classical Physics (2)
Astrophysics of Galaxies (1)
Statistics - Methodology (1)
Statistics - Theory (1)
Physics - Medical Physics (1)
Mathematics - Statistics (1)
Mathematics - Optimization and Control (1)
Statistics - Machine Learning (1)
High Energy Physics - Phenomenology (1)
Computer Science - Architecture (1)
Solar and Stellar Astrophysics (1)
Computer Science - Computation and Language (1)
Instrumentation and Methods for Astrophysics (1)
Computer Science - Neural and Evolutionary Computing (1)
Computer Science - Databases (1)
Physics - Accelerator Physics (1)
Mathematics - Numerical Analysis (1)
Nuclear Experiment (1)
Nonlinear Sciences - Adaptation and Self-Organizing Systems (1)

Publications Authored By W. Lu

A pair of type-II Dirac cones in PdTe$_2$ was recently predicted by theories and confirmed in experiments, making PdTe$_2$ the first material that processes both superconductivity and type-II Dirac fermions. In this work, we study the evolution of Dirac cones in PdTe$_2$ under hydrostatic pressure by the first-principles calculations. Our results show that the pair of type-II Dirac points disappears at 6. Read More

In a recent SIGMOD paper titled "Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study", Arora et al. [1] undertake a performance benchmarking study of several well-known algorithms for influence maximization. In the process, they contradict several published results, and claim to have unearthed and debunked several "myths" that existed around the research of influence maximization. Read More

A wide bandwidth, dual polarized, modified four-square antenna is presented as a feed antenna for radio astronomical measurements. A linear array of these antennas is used as a line-feed for cylindrical reflectors for Tianlai, a radio interferometer designed for 21~cm intensity mapping. Simulations of the feed antenna beam patterns and scattering parameters are compared to experimental results at multiple frequencies across the 650 - 1420 MHz range. Read More

Recently, the soft attention mechanism, which was originally proposed in language processing, has been applied in computer vision tasks like image captioning. This paper presents improvements to the soft attention model by combining a convolutional LSTM with a hierarchical system architecture to recognize action categories in videos. We call this model the Convolutional Hierarchical Attention Model (CHAM). Read More

The mid-infrared (MIR) spectral range, pertaining to important applications such as molecular 'fingerprint' imaging, remote sensing, free space telecommunication and optical radar, is of particular scientific interest and technological importance. However, state-of-the-art materials for MIR detection are limited by intrinsic noise and inconvenient fabrication processes, resulting in high cost photodetectors requiring cryogenic operation. We report black arsenic-phosphorus-based long wavelength infrared photodetectors with room temperature operation up to 8. Read More

The electronic and magnetic properties of ZrS2 nanoribbons (NRs) are investigated based on the first-principles calculations. It is found that the ZrS2 NRs with armchair edges are all indirect-band-gap semiconductors without magnetism and the band-gap exhibits odd-even oscillation behavior with the increase of the ribbon width. For the NRs with zigzag edges, those with both edges S-terminated are nonmagnetic direct-band-gap semiconductors and the gap decreases monotonically as a function of the ribbon width. Read More

TextRank is a variant of PageRank typically used in graphs that represent documents, and where vertices denote terms and edges denote relations between terms. Quite often the relation between terms is simple term co-occurrence within a fixed window of k terms. The output of TextRank when applied iteratively is a score for each vertex, i. Read More

Typically, every part in most coherent text has some plausible reason for its presence, some function that it performs to the overall semantics of the text. Rhetorical relations, e.g. Read More

We study the Berezin-Toeplitz quantization using as quantum space the space of eigenstates of the renormalized Bochner Laplacian corresponding to eigenvalues localized near the origin on a symplectic manifold. We show that this quantization has the correct semiclassical behavior and construct the corresponding star-product. Read More

We use the observed properties of fast radio bursts (FRBs) and a number of general physical considerations to provide a broad-brush model for the physical properties of FRB sources and the radiation mechanism. We show that the magnetic field in the source region should be at least 10^{14} Gauss. This strong field is required to ensure that the electrons have sufficiently high ground state Landau energy so that particle collisions, instabilities, and strong electric and magnetic fields associated with the FRB radiation do not perturb electrons' motion in the direction transverse to the magnetic field and destroy their coherent motion; coherence is required by the high observed brightness temperature of FRB radiation. Read More

We prove an estimate for Donaldson's $Q$-operator on a prequantized compact symplectic manifold. This estimate is an ingredient in the recent result of Keller and Lejmi about a symplectic generalization of Donaldson's lower bound for the $L^2$-norm of the Hermitian scalar curvature. Read More

Existing object proposal algorithms usually search for possible object regions over multiple locations and scales separately, which ignore the interdependency among different objects and deviate from the human perception procedure. To incorporate global interdependency between objects into object localization, we propose an effective Tree-structured Reinforcement Learning (Tree-RL) approach to sequentially search for objects by fully exploiting both the current observation and historical search paths. The Tree-RL approach learns multiple searching policies through maximizing the long-term reward that reflects localization accuracies over all the objects. Read More

We propose the design of an impedance matching acoustic bend in this article. The bending structure is composed of sub-wavelength unit cells with perforated plates and side pipes, whose mass density and bulk modulus can be tuned simultaneously. So the refraction index and the impedance of the acoustic bend can be modulated simultaneously to guarantee both the bending effect and the high transmission. Read More

Many black hole (BH) candidates have been discovered in X-ray binaries and in the nuclei of galaxies. The prediction of Einstein's general relativity is that BHs have an event horizon --- a one-way membrane through which particles fall into the BH but cannot exit. However, except for the very few nearby supermassive BH candidates, our telescopes are unable to resolve and provide a direct proof of the event horizon. Read More

It is known that a compact symplectic manifold endowed with a prequantum line bundle can be embedded in the projective space generated by the eigensections of low energy of the Bochner Laplacian acting on high $p$-tensor powers of the prequantum line bundle. We show that the Fubini-Study metrics induced by these embeddings converge at speed rate $1/p^{2}$ to the symplectic form. Read More

In this paper, we design, fabricate and experimentally characterize a broadband acoustic right-angle bend device in air. Perforated panels with various hole-sizes are used to construct the bend structure. Both the simulated and the experimental results verify that acoustic beam can be rotated effectively through the acoustic bend in a wide frequency range. Read More

We present hydrodynamic simulations of the hot cocoon produced when a relativistic jet passes through the gamma-ray burst (GRB) progenitor star and its environment, and we compute the lightcurve and spectrum of the radiation emitted by the cocoon. The radiation from the cocoon has a nearly thermal spectrum with a peak in the X-ray band, and it lasts for a few minutes in the observer frame; the cocoon radiation starts at roughly the same time as when $\gamma$-rays from a burst trigger detectors aboard GRB satellites. The isotropic cocoon luminosity ($\sim 10^{47}$ erg s$^{-1}$) is of the same order of magnitude as the X-ray luminosity of a typical long-GRB afterglow during the plateau phase. Read More

Superconductivity of transition metal dichalcogenide $1T$-TiTe$_2$ under high pressure was investigated by the first-principles calculations. Our results show that the superconductivity of $1T$-TiTe$_2$ exhibits very different behavior under the hydrostatic and uniaxial pressure. The hydrostatic pressure is harmful to the superconductivity, while the uniaxial pressure is beneficial to the superconductivity. Read More

For decades, advances in electronics were directly related to the scaling of CMOS transistors according to Moore's law. However, both the CMOS scaling and the classical computer architecture are approaching fundamental and practical limits, and new computing architectures based on emerging devices, such as non-volatile memories e.g. Read More

Incentivized social advertising, an emerging marketing model, provides monetization opportunities not only to the owners of the social networking platforms but also to their influential users by offering a "cut" on the advertising revenue. We consider a social network (the host) that sells ad-engagements to advertisers by inserting their ads, in the form of promoted posts, into the feeds of carefully selected "initial endorsers" or seed users: these users receive monetary incentives in exchange for their endorsements. The endorsements help propagate the ads to the feeds of their followers. Read More

Phosphorus atomic chains, the utmost-narrow nanostructures of black phosphorus (BP), are highly relevant to the in-depth development of BP into one-dimensional (1D) regime. In this contribution, we report a top-down route to prepare atomic chains of BP via electron beam sculpting inside a transmission electron microscope (TEM). The growth and dynamics (i. Read More

We study the spectra of photospheric emission from highly relativistic gamma-ray burst outflows using a Monte Carlo (MC) code. We consider the Comptonization of photons with a fast cooled synchrotron spectrum in a relativistic jet with photon to electron number ratio $N_{\gamma}/N_e = 10^5$. For all our simulations, we use mono-energetic protons which interact with thermalised electrons through the Coulomb interaction. Read More

The neutral component of an inert scalar multiplet with hypercharge can provide a stable dark matter particle when its real and imaginary parts have a splitting mass spectrum. Otherwise, a tree-level dark matter-nucleon scattering mediated by the $Z$ boson will be much above the experimental limit. In this paper we focus on a mixed inert scalar triplet dark matter scenario where a complex scalar triplet with hypercharge can mix with another real scalar triplet without hypercharge through their renormalizable coupling to the standard model Higgs doublet. Read More

Building large models with parameter sharing accounts for most of the success of deep convolutional neural networks (CNNs). In this paper, we propose doubly convolutional neural networks (DCNNs), which significantly improve the performance of CNNs by further exploring this idea. In stead of allocating a set of convolutional filters that are independently learned, a DCNN maintains groups of filters where filters within each group are translated versions of each other. Read More

In recent years, a vast amount of research has been conducted on learning people's interests from their actions. Yet their collective actions also allow us to learn something about the world, in particular, infer attributes of places people visit or interact with. Imagine classifying whether a hotel has a gym or a swimming pool, or whether a restaurant has a romantic atmosphere without ever asking its patrons. Read More

Relativistic wakes produced by intense laser or particle beams propagating through plasmas are being considered as accelerators for next generation of colliders and coherent light sources. Such wakes have been shown to accelerate electrons and positrons to several gigaelectronvolts (GeV), with a few percent energy spread and a high wake-to-beam energy transfer efficiency. However, complete mapping of electric field structure of the wakes has proven elusive. Read More

A new method capable of capturing coherent electric field structures propagating at nearly the speed of light in plasma with a time resolution as small as a few femtoseconds is proposed. This method uses a few femtoseconds long relativistic electron bunch to probe the wake produced in a plasma by an intense laser pulse or an ultra-short relativistic charged particle beam. As the probe bunch traverses the wake, its momentum is modulated by the electric field of the wake, leading to a density variation of the probe after free-space propagation. Read More

For scattering problems of time-harmonic waves, the boundary integral equation (BIE) methods are highly competitive, since they are formulated on lower-dimension boundaries or interfaces, and can automatically satisfy outgoing radiation conditions. For scattering problems in a layered medium, standard BIE methods based on the Green's function of the background medium must evaluate the expensive Sommefeld integrals. Alternative BIE methods based on the free-space Green's function give rise to integral equations on unbounded interfaces which are not easy to truncate, since the wave fields on these interfaces decay very slowly. Read More

Much of the information processed by Information Retrieval (IR) systems is unreliable, biased, and generally untrustworthy [1], [2], [3]. Yet, factuality & objectivity detection is not a standard component of IR systems, even though it has been possible in Natural Language Processing (NLP) in the last decade. Motivated by this, we ask if and how factuality & objectivity detection may benefit IR. Read More

Noise is usually a hindrance to signal detection. As stressed by Landauer, however, noise can be an invaluable signal that reveals kinetics of charge particles. Understanding local non-equilibrium electron kinetics at nano-scale is of decisive importance for the development of miniaturized electronic devices, optical nano-devices, and heat management devices. Read More

The generation of very high quality electron bunches (high brightness and low energy spread) from a plasma-based accelerator in the three-dimensional blowout regime using self-injection in tailored plasma density profiles is analyzed theoretically and with particle-in-cell simulations. The underlying physical mechanism that leads to the generation of high quality electrons is uncovered by tracking the trajectories of the electrons as they cross the sheath and are trapped by the wake. Details on how the intensity of the driver and the density scale-length of the plasma control the ultimate beam quality are described. Read More

In this paper, stability of linearly coupled dynamical systems with feedback pinning is studied. Event-triggered rules are employed on both diffusion coupling and feedback pinning to reduce the updating load of the coupled system. Here, both the coupling matrix and the set of pinned-nodes vary with time are induced by a homogeneous Markov chain. Read More

Charge density waves (CDW) and their concomitant periodic lattice distortions (PLD) govern the electronic properties in many layered transition-metal dichalcogenides. In particular, 1T-TaS2 undergoes a metal-to-insulator phase transition as the PLD becomes commensurate with the crystal lattice. Here we directly image PLDs of the nearly-commensurate (NC) and commensurate (C) phases in thin exfoliated 1T-TaS2 using atomic resolution scanning transmission electron microscopy at room and cryogenic temperature. Read More

The efforts to pursue photo detection with extreme performance in terms of ultrafast response time, broad detection wavelength range, and high sensitivity have never been exhausted as driven by its wide range of optoelectronic and photonic applications such as optical communications, interconnects, imaging and remote sensing1. 2D Dirac semimetal graphene has shown excellent potential toward high performance photodetector with high operation speed, broadband response and efficient carrier multiplications benefiting from its linear dispersion band structure with high carrier mobility and zero bandgap2-4. As the three dimensional analogues of graphene, Dirac semimetal Cd3As2 processes all advantages of graphene as a photosensitive material but potentially has stronger interaction with light as bulk material and thus enhanced responsivity5,6, which promises great potential in improving the performance of photodetector in various aspects . Read More

Three dimensional (3D) Dirac semimetals which can be seen as 3D analogues of graphene have attracted enormous interests in research recently. In order to apply these ultrahigh-mobility materials in future electronic/optoelectronic devices, it is crucial to understand the relaxation dynamics of photoexcited carriers and their coupling with lattice. In this work, we report ultrafast transient reflection measurements of the photoexcited carrier dynamics in cadmium arsenide (Cd3As2), which is one of the most stable Dirac semimetals that have been confirmed experimentally. Read More

Spurred by the dramatic mobile IP growth and the emerging Internet of Things (IoT) and cloud-based applications, wireless networking is witnessing a paradigm shift. By fully exploiting the spatial degrees of freedom, the massive multipleinput- multiple-output (MIMO) technology promises significant gains in both data rates and link reliability. This paper presents a time-division duplex (TDD)-based 128-antenna massive MIMO prototyping system designed to operate on a 20 MHz bandwidth. Read More

The electronic, phonon, and thermoelectric properties of a two-dimensional HfS2 monolayer are investigated by using the first-principles calculations combined with the Boltzmann transport theory. The band valleys of the HfS2 monolayer can be effectively tuned by the applied biaxial strain. The Seebeck coefficient and therefore the peak value of the power factor (with the relaxation time inserted) increase when the degeneracy of the band valleys is increased by the strain. Read More

Considering a heterogeneous network (HetNet) system consisting of a macro tier overlaid with a second tier of small cells (SCs), this paper studies the mean square error (MSE) based precoding design to be employed by the macro base station and the SC nodes for multiple-input multiple-output (MIMO) downlinks. First, a new sum-MSE of all users based minimization problem is proposed aiming to design a set of macro cell (MC) and SC transmit precoding matrices or vectors. To solve it, two different algorithms are presented. Read More

Dual-energy computed tomography (DECT) has shown great potential and promising applications in advanced imaging fields for its capabilities of material decomposition. However, image reconstructions and decompositions under sparse views dataset suffers severely from multi factors, such as insufficiencies of data, appearances of noise, and inconsistencies of observations. Under sparse views, conventional filtered back-projection type reconstruction methods fails to provide CT images with satisfying quality. Read More

In this paper, a kind of helix-like chiral metamaterial, which can be realized with multiple conventional lithography or electron beam lithographic techniques, is proposed to achieve broadband bianisotropic optical response analogous to helical metamaterial. On the basis of twisted metamaterial, via tailoring the relative orientation within the lattice, the anisotropy of arc is converted into magneto-electric coupling of closely spaced arc pairs, which leads to a broad bianisotropic optical response. By connecting the adjacent upper and lower arcs, the coupling of metasurface pairs is transformed to the coupling of the three-dimensional inclusions, and provides a much broader and higher bianisotropic optical response. Read More

A new approach was proposed to accurately determine the thickness of film, especially for ultra-thin film, through spectrum fitting with the assistance of interference layer. The determination limit can reach even less than 1 nm. Its accuracy is far better than traditional methods. Read More

In this paper, we attack the anomaly detection problem by directly modeling the data distribution with deep architectures. We propose deep structured energy based models (DSEBMs), where the energy function is the output of a deterministic deep neural network with structure. We develop novel model architectures to integrate EBMs with different types of data such as static data, sequential data, and spatial data, and apply appropriate model architectures to adapt to the data structure. Read More

The divide and conquer method is a common strategy for handling massive data. In this article, we study the divide and conquer method for cubic-rate estimators under the massive data framework. We develop a general theory for establishing the asymptotic distribution of the aggregated M-estimators using a simple average. Read More

Assuming: fast radio bursts (FRBs) are produced by neutron stars at cosmological distances; FRB rate tracks core-collapse supernova rate; and all FRBs repeat with a universal energy distribution function (EDF) dN/dE ~ E^(-beta) with a high-end cutoff at burst energy E_max. We find that observations so far are consistent with a universal EDF with a power-law index 1.5 < beta < 2. Read More

In this paper we present a customized finite-difference-time-domain (FDTD) Maxwell solver for the particle-in-cell (PIC) algorithm. The solver is customized to effectively eliminate the numerical Cerenkov instability (NCI) which arises when a plasma (neutral or non-neutral) relativistically drifts on a grid when using the PIC algorithm. We control the EM dispersion curve in the direction of the plasma drift of a FDTD Maxwell solver by using a customized higher order finite difference operator for the spatial derivative along the direction of the drift ($\hat 1$ direction). Read More

Within the first 10 days after Swift discovered the jetted tidal disruption event (TDE) Sw J1644+57, simultaneous observations in the radio, near-infrared, optical, X-ray and gamma-ray bands were carried out. These multiwavelength data provide a unique opportunity to constrain the emission mechanism and make-up of a relativistic super-Eddington jet. We consider an exhaustive variety of radiation mechanisms for the generation of X-rays in this TDE, and rule out many processes such as SSC, photospheric and proton synchrotron. Read More

We predict by first principles calculations that the recently prepared borophene is a pristine two-dimensional (2D) monolayer superconductor, in which the superconductivity can be significantly enhanced by strain and charge carrier doping. The intrinsic metallic ground state with high density of states at Fermi energy and strong Fermi surface nesting lead to sizeable electron-phonon coupling, making the freestanding borophene superconduct with $T_c$ close to 19.0 K. Read More

The modulation of band gap in the two-dimensional carbon materials is of impor- tance for their applications as electronic devices. By first-principles calculations, we propose a model to control the band gap size of {\gamma}-graphyne. The model is named as p-n codoping, i. Read More

Because different patients may response quite differently to the same drug or treatment, there is increasing interest in discovering individualized treatment rule. In particular, people are eager to find the optimal individualized treatment rules, which if followed by the whole patient population would lead to the "best" outcome. In this paper, we propose new estimators based on robust regression with general loss functions to estimate the optimal individualized treatment rules. Read More