arXiv subjects

Zheng Wei

Publications and source records attributed to Zheng Wei.

71 records · Page 4Linked to original sources

arXiv2023

Symmetry classes of dissipative topological insulators with edge dark state

We classify the dissipative topological insulators (TIs) with edge dark states (EDS) by using the 38-fold way of non-Hermitian systems in this paper. The dissipative dynamics of these quadratic open fermionic systems is captured by a non-Hermitian single-particle matrix which contains both the internal dynamics and the dissipation, refereed to as damping matrix $X$. And the dark states in these systems are the eigenmodes of $X$ which the eigenvalues' imaginary part vanishes. However, there is a constraint on $X$, namely that the modes in which the eigenvalues' imaginary parts are positive are forbidden. In other words, the imaginary line-gap of $X$ is ill-defined, so the topological band theory classifying the dark states can not be applied to $X$. To reveal the topological protection of EDS, we propose the double damping matrix $\tilde{X} = \text{diag}\left( X, X^* \right)$, where the imaginary line-gap is well defined. Thus, the 38-fold way can be applied to $\tilde{X}$, and the topological protection of the EDS is uncovered. Different from previous studies of EDS in purely dissipative dynamics, the EDS in the dissipative TIs are robust against the inclusion of Hamiltonians. Furthermore, the topological classification of $\tilde{X}$ not only reflects the topological protection of EDS in dissipative TIs but also provides a paradigm to predict the appearance of EDS in other open free fermionic systems.

cond-mat.mes-hall↗

arXiv2022

One-Bit Matrix Completion with Differential Privacy

As a prevailing collaborative filtering method for recommendation systems, one-bit matrix completion requires data collected by users to provide personalized service. Due to insidious attacks and unexpected inference, the release of users' data often raises serious privacy concerns. To address this issue, differential privacy(DP) has been widely used in standard matrix completion models. To date, however, little has been known about how to apply DP to achieve privacy protection in one-bit matrix completion. In this paper, we propose a unified framework for ensuring a strong privacy guarantee of one-bit matrix completion with DP. In our framework, we develop four different private perturbation mechanisms corresponding to different stages of one-bit matrix completion. For each mechanism, we design a privacy-preserving algorithm and provide a theoretical recovery error bound under the proper conditions. Numerical experiments on synthetic and real-world datasets demonstrate the effectiveness of our proposal. Compared to the one-bit matrix completion without privacy protection, our proposed mechanisms can maintain high-level privacy protection with marginal loss of completion accuracy.

cs.CR↗

arXiv2022

Layer-by-Layer Epitaxy of Multilayer MoS2 Wafers

Two-dimensional (2D) semiconductor of MoS2 has great potential for advanced electronics technologies beyond silicon1-9. So far, high-quality monolayer MoS2 wafers10-12 are already available and various demonstrations from individual transistors to integrated circuits have also been shown13-15. In addition to the monolayer, multilayers have narrower band gaps but improved carrier mobilities and current capacities over the monolayer5,16-18. However, achieving high-quality multilayer MoS2 wafers remains a challenge. Here we report the growth of high quality multilayer MoS2 4-inch wafers via the layer-by-layer epitaxy process. The epitaxy leads to well-defined stacking orders between adjacent epitaxial layers and offers a delicate control of layer numbers up to 6. Systematic evaluations on the atomic structures and electronic properties were carried out for achieved wafers with different layer numbers. Significant improvements on device performances were found in thicker-layer field effect transistors (FETs), as expected. For example, the average field-effect mobility (μFE) at room temperature (RT) can increase from ~80 cm2V-1s-1 for monolayer to ~110/145 cm2V-1s-1 for bilayer/trilayer devices. The highest RT μFE=234.7 cm2V-1s-1 and a record-high on-current densities of 1.704 mAμm-1 at Vds=2 V were also achieved in trilayer MoS2 FETs with a high on/off ratio exceeding 107. Our work hence moves a step closer to practical applications of 2D MoS2 in electronics.

physics.app-ph↗

arXiv2022

Applying Differential Privacy to Tensor Completion

Tensor completion aims at filling the missing or unobserved entries based on partially observed tensors. However, utilization of the observed tensors often raises serious privacy concerns in many practical scenarios. To address this issue, we propose a solid and unified framework that contains several approaches for applying differential privacy to the two most widely used tensor decomposition methods: i) CANDECOMP/PARAFAC~(CP) and ii) Tucker decompositions. For each approach, we establish a rigorous privacy guarantee and meanwhile evaluate the privacy-accuracy trade-off. Experiments on synthetic and real-world datasets demonstrate that our proposal achieves high accuracy for tensor completion while ensuring strong privacy protections.

cs.LG↗

arXiv2022

From `Wow' to `Why': Guidelines for Creating the Opening of a Data Video with Cinematic Styles

Data videos are an increasingly popular storytelling form. The opening of a data video critically influences its success as the opening either attracts the audience to continue watching or bores them to abandon watching. However, little is known about how to create an attractive opening. We draw inspiration from the openings of famous films to facilitate designing data video openings. First, by analyzing over 200 films from several sources, we derived six primary cinematic opening styles adaptable to data videos. Then, we consulted eight experts from the film industry to formulate 28 guidelines. To validate the usability and effectiveness of the guidelines, we asked participants to create data video openings with and without the guidelines, which were then evaluated by experts and the general public. Results showed that the openings designed with the guidelines were perceived to be more attractive, and the guidelines were praised for clarity and inspiration.

cs.HC↗

arXiv2021

Fast Graph Subset Selection Based on G-optimal Design

Graph sampling theory extends the traditional sampling theory to graphs with topological structures. As a key part of the graph sampling theory, subset selection chooses nodes on graphs as samples to reconstruct the original signal. Due to the eigen-decomposition operation for Laplacian matrices of graphs, however, existing subset selection methods usually require high-complexity calculations. In this paper, with an aim of enhancing the computational efficiency of subset selection on graphs, we propose a novel objective function based on the optimal experimental design. Theoretical analysis shows that this function enjoys an $α$-supermodular property with a provable lower bound on $α$. The objective function, together with an approximate of the low-pass filter on graphs, suggests a fast subset selection method that does not require any eigen-decomposition operation. Experimental results show that the proposed method exhibits high computational efficiency, while having competitive results compared to the state-of-the-art ones, especially when the sampling rate is low.

cs.IT↗

arXiv2021

SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System

Recently, textual information has been proved to play a positive role in recommendation systems. However, most of the existing methods only focus on representation learning of textual information in ratings, while potential selection bias induced by the textual information is ignored. In this work, we propose a novel and general self-adaptive module, the Self-adaptive Attention Module (SAM), which adjusts the selection bias by capturing contextual information based on its representation. This module can be embedded into recommendation systems that contain learning components of contextual information. Experimental results on three real-world datasets demonstrate the effectiveness of our proposal, and the state-of-the-art models with SAM significantly outperform the original ones.

cs.IR↗

arXiv2021

Radiation-hardened and Repairable MoS$_2$ Field Effect Devices with Polymer Solid Electrolyte Gates

As human activities expand into naturally or man-made radiation-prone environment, the need for radiation-hardened (Rad-Hard) electronic hardware surged. The state-of-the-art silicon-based and two-dimensional (2D) materials based Rad-Hard transistors can withstand up to 1 Mrad (Si) of total ionization dose (TID), while higher TID tolerance is being heatedly sought after. Here we present few-layer MoS$_2$ Rad-Hard field-effect transistors (FETs) with polymer solid electrolyte (PSE) gate dielectrics. The MoS$_2$ PSE-FETs exhibit a TID tolerance of up to 3.75 Mrad (Si) at a dose rate of 523 rad (Si) s$^{-1}$ and can be repaired with a moderate thermal annealing at 100 $^{\circ}$C for 5 minutes. Combining the excellent intrinsic radiation tolerance and the reparability, the MoS$_2$ PSE-FETs reach a TID tolerance of up to 10 Mrad (Si). Complementary metal-oxide-semiconductor (CMOS)-like MoS$_2$ PSE-inverters have been built and show similar high radiation tolerance. Furthermore, the feasibility of wafer-scale Rad-Hard PSE-inverter array has been demonstrated using chemical vapor deposition (CVD) grown monolayer MoS$_2$. Our studies uncover the potential of 2D materials based PSE devices in future Rad-Hard integrated circuits (ICs).

cond-mat.mtrl-sci↗

arXiv2020

ADCC: An Effective and Intelligent Attention Dense Color Constancy System for Studying Images in Smart Cities

As a novel method eliminating chromatic aberration on objects, computational color constancy has becoming a fundamental prerequisite for many computer vision applications. Among algorithms performing this task, the learning-based ones have achieved great success in recent years. However, they fail to fully consider the spatial information of images, leaving plenty of room for improvement of the accuracy of illuminant estimation. In this paper, by exploiting the spatial information of images, we propose a color constancy algorithm called Attention Dense Color Constancy (ADCC) using convolutional neural network (CNN). Specifically, based on the 2D log-chrominance histograms of the input images as well as their specially augmented ones, ADCC estimates the illuminant with a self-attention DenseNet. The augmented images help to tell apart the edge gradients, edge pixels and non-edge ones in log-histogram, which contribute significantly to the feature extraction and color-ambiguity elimination, thereby advancing the accuracy of illuminant estimation. Simulations and experiments on benchmark datasets demonstrate that the proposed algorithm is effective for illuminant estimation compared to the state-of-the-art methods. Thus, ADCC offers great potential in promoting applications of smart cities, such as smart camera, where color is an important factor for distinguishing objects.

cs.CV↗

arXiv2020

Mo$_6$Ga$_{31}$ endohedral cluster superconductor

Synthesis, crystal and electronic structure, and physical properties of the Mo$_6$Ga$_{31}$ endohedral cluster superconductor are reported. The compound has two crystallographic modifications, monoclinic and triclinic, in which the same {Mo$_{12}$Ga$_{62}$} building units are perpendicular or codirectional to each other, respectively. Monoclinic and triclinic structures of Mo$_6$Ga$_{31}$ possess qualitatively the same electronic density of states showing a high peak at the Fermi level. Both modifications are inherently present in the bulk specimen. Due to the proximity effect, bulk Mo$_6$Ga$_{31}$ exhibits single superconducting transition at the critical temperature of 8.2 K in zero magnetic field. The upper critical field, which is 7.8 T at zero temperature, shows clear enhancement with respect to the Werthamer-Helfand-Honenberg prediction. Accordingly, heat capacity measurements indicate strong electron-phonon coupling in the superconducting state with the large ratio of $2Δ(0)/(k_BT_c)=4.5$, where 2$Δ(0)$ is the full superconducting gap at zero temperature.

cond-mat.supr-con↗

arXiv2019

Parallel Markov Chain Monte Carlo for Bayesian Hierarchical Models with Big Data, in Two Stages

Due to the escalating growth of big data sets in recent years, new Bayesian Markov chain Monte Carlo (MCMC) parallel computing methods have been developed. These methods partition large data sets by observations into subsets. However, for Bayesian nested hierarchical models, typically only a few parameters are common for the full data set, with most parameters being group-specific. Thus, parallel Bayesian MCMC methods that take into account the structure of the model and split the full data set by groups rather than by observations are a more natural approach for analysis. Here, we adapt and extend a recently introduced two-stage Bayesian hierarchical modeling approach, and we partition complete data sets by groups. In stage 1, the group-specific parameters are estimated independently in parallel. The stage 1 posteriors are used as proposal distributions in stage 2, where the target distribution is the full model. Using three-level and four-level models, we show in both simulation and real data studies that results of our method agree closely with the full data analysis, with greatly increased MCMC efficiency and greatly reduced computation times. The advantages of our method versus existing parallel MCMC computing methods are also described.

stat.ME↗

arXiv2016

Parallel Computing for Copula Parameter Estimation with Big Data: A Simulation Study

Copula-based modeling has seen rapid advances in recent years. However, in big data applications, the lengthy computation time for estimating copula parameters is a major difficulty. Here, we develop a novel method to speed computation time in estimating copula parameters, using communication-free parallel computing. Our procedure partitions full data sets into disjoint independent subsets, performs copula parameter estimation on the subsets, and combines the results to produce an approximation to the full data copula parameter. We show in simulation studies that the computation time is greatly reduced through our method, using three well-known one-parameter bivariate copulas within the elliptical and Archimedean families: Gaussian, Frank and Gumbel. In addition, our simulation studies find small values for estimated bias, estimated mean squared error, and estimated relative L1 and L2 errors for our method, when compared to the full data parameter estimates.

stat.ME↗

arXiv2015

Simulation of proton radiography terminal at IMP

Proton radiography is used for advanced hydrotesting as a new type radiography technology due to its powerful penetration capability and high detection efficiency. A new proton radiography terminal will be developed to radiograph static samples at Institute of Modern Physics of Chinese Academy of Science (IMP-CAS). The proton beam with the maximum energy of 2.6 GeV will be produced by Heavy Ion Research Facility in Lanzhou-Cooling Storage Ring (HIRFL-CSR). The proton radiography terminal consists of the matching magnetic lens and the Zumbro lens system. In this paper, the design scheme and all optic parameters of this beam terminal for 2.6GeV proton energy are presented by simulating the beam optics using WINAGILE code. My-BOC code is used to test the particle tracking of proton radiography beam line. Geant4 code and G4beamline code are used for simulating the proton radiography system. The results show that the transmission efficiency of proton without target is 100%, and the effect of secondary particles can be neglected. In order to test this proton radiography system, the proton images for an aluminum plate sample with two rectangular orifices and a step brass plate sample are respectively simulated using Geant4 code. The results show that the best spatial resolution is about 36μm, and the differences of the thickness is not greater than 10%.

physics.acc-ph↗

arXiv2014

Study on the unfolding algorithm for D-T neutron energy spectra measurement using recoil proton method

A proton recoil method for measuring D-T neutron energy spectra using polyethylene film and Si (Au) surface barrier detector was presented. An iteration algorithm for unfolding the recoil proton energy spectrum to the neutron energy spectrum was investigated. The response matrixes R of polyethylene film at 0 degree and 45 degree were obtained by simulating the recoil proton energy spectra from the mono-energetic neutron using MCNP code. Under an assumed D-T neutron spectrum, the recoil proton spectra from polyethylene film at 0 degree and 45 degree were also simulated using MCNP code. Based on the response matrixes R and the simulated recoil proton spectra at 0 degree and 45 degree, the unfolded neutron spectra were respectively obtained using the iteration algorithm, and compared with the assumed neutron spectrum. The results show that the iteration algorithm method can be applied to unfold the recoil proton energy spectrum to the neutron energy spectrum for D-T neutron energy spectra measurement using recoil proton method.

physics.ins-det↗

arXiv2013

Co-compact entropy and its variational principle for non-compact spaces

The purpose of this paper is to generalize the variational principle, which states that the topological entropy is equal to the supremum of the measure theoretical entropies and also the minimum of the metric theoretical entropies, to non-compact dynamical systems by utilizing the co-compact entropy. The equivalence between positive co-compact entropy and the existence of p-horseshoes over the real line is also proved. This implies a system over real line with positive co-compact entropy contains a compact invariant subset.

math.DS↗

arXiv2012

The entropy of co-compact open covers

Co-compact entropy is introduced as an invariant of topological conjugation for perfect mappings defined on any Hausdorff space(compactness and metrizability not necessarily required). This is achieved through the consideration of co-compact covers of the space. The advantages of co-compact entropy include: 1) it does not require the space to be compact, and thus generalizes Adler, Konheim and McAndrew's topological entropy of continuous mappings on compact dynamical systems, and 2) it is an invariant of topological conjugation, compared to Bowen's entropy that is metric-dependent. Other properties of co-compact entropy are investigated, e.g., the co-compact entropy of a subsystem does not exceed that of the whole system. For the linear system (R, f) defined by f(x) = 2x, the co-compact entropy is zero, while Bowen's entropy for this system is at least log 2. More general, it is found that co-compact entropy is a lower bound of Bowen's entropies, and the proof of this result generates the Lebesgue Covering Theorem to co-compact open covers of non-compact metric spaces, too.

math.DS↗

arXiv2008

A Markov Process Inspired Cellular Automata Model of Road Traffic

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize it for different scenarios: usually mentioned flows on freeways and start-up flows at signalized intersections. The agreement between the empirical observations and the simulation results suggests the soundness of this new approach.

physics.data-an↗