arXiv subjects

Hui Wang

Publications and source records attributed to Hui Wang.

At least 451 records · Page 25Linked to original sources

arXiv2019

A Piezoelectric, Strain-Controlled Antiferromagnetic Memory Insensitive to Magnetic Fields

Spintronic devices based on antiferromagnetic (AFM) materials hold the promise of fast switching speeds and robustness against magnetic fields. Different device concepts have been predicted and experimentally demonstrated, such as low-temperature AFM tunnel junctions that operate as spin-valves, or room-temperature AFM memory, for which either thermal heating in combination with magnetic fields, or Néel spin-orbit torque is used for the information writing process. On the other hand, piezoelectric materials were employed to control magnetism by electric fields in multiferroic heterostructures, which suppresses Joule heating caused by switching currents and may enable low energy-consuming electronic devices. Here, we combine the two material classes to explore changes of the resistance of the high-Néel-temperature antiferromagnet MnPt induced by piezoelectric strain. We find two non-volatile resistance states at room temperature and zero electric field, which are stable in magnetic fields up to 60 T. Furthermore, the strain-induced resistance switching process is insensitive to magnetic fields. Integration in a tunnel junction can further amplify the electroresistance. The tunneling anisotropic magnetoresistance reaches ~11.2% at room temperature. Overall, we demonstrate a piezoelectric, strain-controlled AFM memory which is fully operational in strong magnetic fields and has potential for low-energy and high-density memory applications.

cond-mat.mtrl-sci↗

arXiv2019

AuthPDB: Query Authentication for Outsourced Probabilistic Databases

Spurred by developments such as cloud computing, there are increasing efforts for outsourcing of data management. A company (data owner) who lacks expertise and comptational resources can outsource his data to a third-party service provider (server), who provides storage and query evaluation on the outsourced data as the services. One of the security concerns of the outsourcing paradigm is the integrity of the returned query results on the outsourced data. In this paper, we consider the outsourcing of probabilistic databases, on which query evaluation is of high complexity. A dishonest server may return cheap (and incorrect) query answers, hoping that the client who has weak computational power cannot catch the incorrect results. To address this issue, we design efficient integrity verification methods for both all-answer and top-k query evaluation on outsourced probabilistic databases. Our empirical results demonstrate the effectiveness and efficiency of our verification methods.

cs.CR↗

arXiv2018

Negative differential conductance effect and electrical anisotropy of 2D ZrB2 monolayers

Two-dimensional (2D) metal-diboride ZrB2 monolayers was predicted theoretically as a stable new electronic material [A. Lopez-Bezanilla, Phys. Rev. Mater., 2018, 2, 011002 (R)]. Here, we investigate its electronic transport properties along the zigzag (z-ZrB2) and armchair (a-ZrB2) directions, using the density functional theory and non-equilibrium Green's function methods. Under low biases, the 2D ZrB2 shows a similar electrical transport along zigzag and armchair directions as electric current propagates mostly via the metallic Zr-Zr bonds. However, it shows an electrical anistropy under high biases, and its I-V curves along zigzag and armchair directions diverge as the bias voltage is higher than 1.4 V, as more directional B-B transmission channels are opened. Importantly, both z-ZrB2 and a-ZrB2 show a pronounced negative differential conductance (NDC) effect and hence they can be promising for the use in NDC-based nanodevices.

cond-mat.mes-hall↗

arXiv2018

Mean escape time for randomly switching narrow gates in a cellular flow

The escape of particles through a narrow absorbing gate in confined domains is a abundant phenomenon in various systems in physics, chemistry and molecular biophysics. We consider the narrow escape problem in a cellular flow when the two gates randomly switch between different states with a switching rate k between the two gates. After briefly deriving the coupled partial differential equations for the escape time through two gates, we compute the mean escape time for particles escaping from the gates with different initial states. By numerical simulation under nonuniform boundary conditions, we quantify how narrow escape time is affected by the switching rate k between the two gates, arc length s between two gates, angular velocity w of the cellular flow and diffusion coefficient D. We reveal that the mean escape time decreases with the switching rate k between the two gates, angular velocity w and diffusion coefficient D for fixed arc length, but takes the minimum when the two gates are evenly separated on the boundary for any given switching rate k between the two gates. In particular, we find that when the arc length size ε for the gates is sufficiently small, the average narrow escape time is approximately independent of the gate arc length size. We further indicate combinations of system parameters (regions located in the parameter space) such that the mean escape time is the longest or shortest. Our findings provide mathematical understanding for phenomena such as how ions select ion channels and how chemicals leak in annulus ring containers, when drift vector fields are present.

cond-mat.stat-mech↗

arXiv2018

Mechanically Generating Entangled Photons from the Vacuum: A Microwave Circuit-Acoustic Resonator Analogue of the Unruh Effect

We consider a model for an oscillatory, relativistic accelerating photodetector inside a cavity and show that the entangled photon pair production from the vacuum (Unruh effect) can be accurately described in the steady state by a non-degenerate parametric amplifier (NDPA), with the detector's accelerating center of mass serving as the parametric drive (pump). We propose an Unruh effect analogue NDPA microwave superconducting circuit scheme, where the breathing mode of the coupling capacitance between the cavity and detector provides the mechanical pump. For realizable circuit parameters, the resulting photon production from the vacuum should be detectable.

quant-ph↗

arXiv2018

Geometric Methods for Stochastic Dynamical Systems

Noisy fluctuations are ubiquitous in complex systems. They play a crucial or delicate role in the dynamical evolution of gene regulation, signal transduction, biochemical reactions, among other systems. Therefore, it is essential to consider the effects of noise on dynamical systems. It has been a challenging topic to have better understanding of the impact of the noise on the dynamical behaviors of complex systems.

math.DS↗

arXiv2018

Bifurcation in mean phase portraits for stochastic dynamical systems with multiplicative Gaussian noise

We investigate the bifurcation phenomena for stochastic systems with multiplicative Gaussian noise, by examining qualitative changes in mean phase portraits. Starting from the Fokker-Planck equation for the probability density function of solution processes, we compute the mean orbits and mean equilibrium states. A change in the number or stability type, when a parameter varies, indicates a stochastic bifurcation. Specifically, we study stochastic bifurcation for three prototypical dynamical systems (i.e., saddle-node, transcritical, and pitchfork systems) under multiplicative Gaussian noise, and have found some interesting phenomena in contrast to the corresponding deterministic counterparts.

math.DS↗

arXiv2018

Assessing the Potential of Classical Q-learning in General Game Playing

After the recent groundbreaking results of AlphaGo and AlphaZero, we have seen strong interests in deep reinforcement learning and artificial general intelligence (AGI) in game playing. However, deep learning is resource-intensive and the theory is not yet well developed. For small games, simple classical table-based Q-learning might still be the algorithm of choice. General Game Playing (GGP) provides a good testbed for reinforcement learning to research AGI. Q-learning is one of the canonical reinforcement learning methods, and has been used by (Banerjee $\&$ Stone, IJCAI 2007) in GGP. In this paper we implement Q-learning in GGP for three small-board games (Tic-Tac-Toe, Connect Four, Hex)\footnote{source code: https://github.com/wh1992v/ggp-rl}, to allow comparison to Banerjee et al.. We find that Q-learning converges to a high win rate in GGP. For the $ε$-greedy strategy, we propose a first enhancement, the dynamic $ε$ algorithm. In addition, inspired by (Gelly $\&$ Silver, ICML 2007) we combine online search (Monte Carlo Search) to enhance offline learning, and propose QM-learning for GGP. Both enhancements improve the performance of classical Q-learning. In this work, GGP allows us to show, if augmented by appropriate enhancements, that classical table-based Q-learning can perform well in small games.

cs.AI↗

arXiv2018

First-principles investigation of the effect of substitution and surface adsorption on magnetostrictive properties of Fe-Ga alloys

Materials with large magnetostriction are widely used in sensors, actuators, micro electromechanical systems, and energy-harvesters. Binary Fe-Ga alloys (Galfenol) are the most promising rare-earth-free candidates combining numerous advantages such as low saturation magnetic field (~200 Oe), excellent ductility and low cost, while further improving their performance is imperative for practical applications. Using density functional theory calculation, we report results of the effect of substituting small amount of additional elements X (eg. X = Ag, Pd and Cu) on magnetostriction of Fe-Ga alloys, and find that it may double the magnetostriction with a substitutional percentage of only 1.6%. Moreover, adsorbents with high chemical activity (eg. O or Os atoms) may affect the surface energy of different face-orientations of Fe-Ga alloys, indicating proper surface treatments are necessary to tune the alignment of Fe-Ga grains to achieve better performance. These results may be helpful to further optimize the magnetostrictive properties of Fe-Ga alloys for device applications.

cond-mat.mtrl-sci↗

arXiv2018

How does the electric current propagate through the fully-hydrogenated borophene?

We study the electronic transport properties of two-dimensional (2D) fully-hydrogenated borophene (namely, borophane), using the density functional theory and non-equilibrium Green's function approaches. Borophane shows a perfect electrical transport anisotropy and is promising for applications. Along the peak- or equivalently the valley-parallel direction, the 2D borophane exhibits a metallic characteristic and its current-voltage (I-V) curve shows a linear behavior, corresponding to the ON state in borophane-based nano-switch. In this case, electrons mainly propagate via the B-B bonds along the linear boron chains. In contrast, the electron transmission is almost forbidden along the perpendicular buckled direction (i.e., the OFF state), due to its semi-conductor property. Our work demonstrates that 2D borophane could combine the metal and semiconductor features and can be a promising candidate of nano-switching materials with stable structure and high ON/OFF ratio.

cond-mat.mtrl-sci↗

arXiv2018

Polarized indistinguishable single photons from a quantum dot in an elliptical micropillar

The key challenge to scalable optical quantum computing, boson sampling, and quantum metrology is sources of single photons with near-unity system efficiency and simultaneously near-perfect indistinguishability in all degrees of freedom (including spectral, temporal, spatial, and polarization). However, previous high-indistinguishability solid-state single-photon sources had to rely on polarization filtering that reduced the system efficiency by at least 50%. Here, we overcome this challenge by developing a new single-photon source based on a coherently driven quantum dot embedded in an elliptical micropillar. The asymmetric cavity lifts the polarization degeneracy into two orthogonal linearly polarized modes with a suitable energy separation. We design an excitation-collection scheme that allows the creation and collection of single photons with an indistinguishability of 0.976(1) and a degree of polarization of 91%. Our method provides a solution of combining near-unity system efficiency and indistinguishability compatible with background-free resonant excitation, and opens the way to truly optimal single-photon sources for scalable photonic quantum technologies.

physics.optics↗

arXiv2018

Nonreciprocal photon blockade via quadratic optomechanical coupling

We propose to manipulate the statistic properties of the photons transport nonreciprocally via quadratic optomechanical coupling. We present a scheme to generate quadratic optomechanical interactions in the normal optical modes of a whispering-gallery-mode (WGM) optomechanical system by eliminating the linear optomechanical couplings via anticrossing of different modes. By optically pumping the WGM optomechanical system in one direction, the effective quadratic optomechanical coupling in that direction will be enhanced significantly, and nonreciprocal photon blockade will be observed consequently. Our proposal has potential applications for the on-chip nonreciprocal single-photon devices.

quant-ph↗

arXiv2018

Integrity Authentication for SQL Query Evaluation on Outsourced Databases: A Survey

Spurred by the development of cloud computing, there has been considerable recent interest in the Database-as-a-Service (DaaS) paradigm. Users lacking in expertise or computational resources can outsource their data and database management needs to a third-party service provider. Outsourcing, however, raises an important issue of result integrity: how can the client verify with lightweight overhead that the query results returned by the service provider are correct (i.e., the same as the results of query execution locally)? This survey focuses on categorizing and reviewing the progress on the current approaches for result integrity of SQL query evaluation in the DaaS model. The survey also includes some potential future research directions for result integrity verification of the outsourced computations.

cs.CR↗

arXiv2018

Colossal barocaloric effects in plastic crystals

Solid-state refrigeration technology based on caloric effects are promising to replace the currently used vapor compression cycles. However, their application is restricted due to limited performances of caloric materials. Here, we have identified colossal barocaloric effects (CBCEs) in a class of disordered solids called plastic crystals. The obtained entropy changes are about 380 J kg-1 K-1 in the representative neopentylglycol around room temperature. Inelastic neutron scattering reveals that the CBCEs in plastic crystals are attributed to the combination of the vast molecular orientational disorder, giant compressibility, and high anharmonic lattice dynamics. Our study establishes the microscopic scenario for CBCEs in plastic crystals and paves a new route to the next-generation solid-state refrigeration technology.

cond-mat.mtrl-sci↗

arXiv2018

Minimum Margin Loss for Deep Face Recognition

Face recognition has achieved great progress owing to the fast development of the deep neural network in the past a few years. As an important part of deep neural networks, a number of the loss functions have been proposed which significantly improve the state-of-the-art methods. In this paper, we proposed a new loss function called Minimum Margin Loss (MML) which aims at enlarging the margin of those overclose class centre pairs so as to enhance the discriminative ability of the deep features. MML supervises the training process together with the Softmax Loss and the Centre Loss, and also makes up the defect of Softmax + Centre Loss. The experimental results on MegaFace, LFW and YTF datasets show that the proposed method achieves the state-of-the-art performance, which demonstrates the effectiveness of the proposed MML.

cs.CV↗

arXiv2018

BinMatch: A Semantics-based Hybrid Approach on Binary Code Clone Analysis

Binary code clone analysis is an important technique which has a wide range of applications in software engineering (e.g., plagiarism detection, bug detection). The main challenge of the topic lies in the semantics-equivalent code transformation (e.g., optimization, obfuscation) which would alter representations of binary code tremendously. Another chal- lenge is the trade-off between detection accuracy and coverage. Unfortunately, existing techniques still rely on semantics-less code features which are susceptible to the code transformation. Besides, they adopt merely either a static or a dynamic approach to detect binary code clones, which cannot achieve high accuracy and coverage simultaneously. In this paper, we propose a semantics-based hybrid approach to detect binary clone functions. We execute a template binary function with its test cases, and emulate the execution of every target function for clone comparison with the runtime information migrated from that template function. The semantic signatures are extracted during the execution of the template function and emulation of the target function. Lastly, a similarity score is calculated from their signatures to measure their likeness. We implement the approach in a prototype system designated as BinMatch which analyzes IA-32 binary code on the Linux platform. We evaluate BinMatch with eight real-world projects compiled with different compilation configurations and commonly-used obfuscation methods, totally performing over 100 million pairs of function comparison. The experimental results show that BinMatch is robust to the semantics-equivalent code transformation. Besides, it not only covers all target functions for clone analysis, but also improves the detection accuracy comparing to the state-of-the-art solutions.

cs.SE↗

arXiv2018

A Study of Deep Feature Fusion based Methods for Classifying Multi-lead ECG

An automatic classification method has been studied to effectively detect and recognize Electrocardiogram (ECG). Based on the synchronizing and orthogonal relationships of multiple leads, we propose a Multi-branch Convolution and Residual Network (MBCRNet) with three kinds of feature fusion methods for automatic detection of normal and abnormal ECG signals. Experiments are conducted on the Chinese Cardiovascular Disease Database (CCDD). Through 10-fold cross-validation, we achieve an average accuracy of 87.04% and a sensitivity of 89.93%, which outperforms previous methods under the same database. It is also shown that the multi-lead feature fusion network can improve the classification accuracy over the network only with the single lead features.

cs.CV↗

arXiv2018

Generalized Su-Schrieffer-Heeger model in one dimensional optomechanical arrays

We propose an implementation of a generalized Su-Schrieffer-Heeger (SSH) model based on optomechanical arrays. The topological properties of the generalized SSH model depend on the effective optomechanical interactions enhanced by strong driving optical fields. Three phases including one trivial and two distinct topological phases are found in the generalized SSH model. The phase transition can be observed by turning the strengths and phases of the effective optomechanical interactions via adjusting the external driving fields. Moreover, four types of edge states can be created in generalized SSH model of an open chain under single-particle excitation, and the dynamical behaviors of the excitation in the open chain are related to the topological properties under the periodic boundary condition. We show that the edge states can be pumped adiabatically along the optomechanical arrays by periodically modulating the amplitude and frequency of the driving fields. The generalized SSH model based on the optomechanical arrays provides us a tunable platform to engineer topological phases for photons and phonons, which may have potential applications in controlling the transport of photons and phonons.

quant-ph↗