arXiv subjects

Teng Wang

Publications and source records attributed to Teng Wang.

At least 145 records · Page 8Linked to original sources

arXiv2020

Elastoresistance measurements on CaKFe$_4$As$_4$ and KCa$_2$Fe$_4$As$_4$F$_2$ with the Fe site of $C_{2v}$ symmetry

We report resistance and elastoresistance measurements on (Ba$_{0.5}$K$_{0.5}$)Fe$_2$As$_2$, CaKFe$_4$As$_4$, and KCa$_2$Fe$_4$As$_4$F$_2$. The Fe-site symmetry is $D_{2d}$ in the first compound but $C_{2v}$ in the latter two, which lifts the degeneracy of the Fe $d_{xz}$ and $d_{yz}$ orbitals. The temperature dependence of the resistance and elastoresistance is similar between the three compounds. Especially, the [110] elastoresistance is enhanced with decreasing temperature irrespective of the Fe-site symmetry. This appears to be in conflict with recent Raman scattering studies on CaKFe$_4$As$_4$, which suggest the absence of nematic fluctuations. We consider possible ways of reconciliation and suggest that the present result is important in elucidating the origin of in-plane resistivity anisotropy in iron-based superconductors.

cond-mat.supr-con↗

arXiv2020

Dense-Captioning Events in Videos: SYSU Submission to ActivityNet Challenge 2020

This technical report presents a brief description of our submission to the dense video captioning task of ActivityNet Challenge 2020. Our approach follows a two-stage pipeline: first, we extract a set of temporal event proposals; then we propose a multi-event captioning model to capture the event-level temporal relationships and effectively fuse the multi-modal information. Our approach achieves a 9.28 METEOR score on the test set.

cs.CV↗

arXiv2020

Vanishing viscosity limit for viscous Burgers-Vlasov equations

We establish the vanishing viscosity limit of viscous Burgers-Vlasov equations for one dimensional kinetic model about interactions between a viscous fluid and dispersed particles by using compensated compactness technique and the evolution of level sets arguments. The limit we obtained is exactly a finite-energy weak solution to the inviscid equations.

math.AP↗

arXiv2020

Anisotropic physical properties and large critical current density in KCa${_2}$Fe${_4}$As${_4}$F${_2}$ single crystal

We present a systematic study of electrical resistivity, Hall coefficient, magneto-optical imaging, magnetization, and STEM analyses of KCa${_2}$Fe${_4}$As${_4}$F${_2}$ single crystals. Sharp diamagnetic transition and magneto-optical imaging reveal homogeneity of single crystal and prominent Bean-like penetrations of vortices. Large anisotropy of electrical resistivity, with ${ρ_c / ρ_{ab}}$ > 100, and semiconductor-like ${ρ_c}$ suggest that the electronic state is quasi two-dimensional. Hall effect measurements indicate that KCa${_2}$Fe${_4}$As${_4}$F${_2}$ is a multiband system with holes as main carriers. Magnetization measurements reveal significantly larger J$_c$ compared with that in other iron-based superconductors with different values of J$_c$ depending on the direction of magnetic field. Origin of these J$_c$ characteristics is discussed based on microstructural observations using STEM. In addition, further enhancement of J$_c$ in KCa${_2}$Fe${_4}$As${_4}$F${_2}$ for future application is demonstrated in terms of heavy-ion irradiation.

cond-mat.supr-con↗

arXiv2020

Observation of Two-dimensional Superconductivity in an Ultrathin Iron-Arsenic Superconductor

Two-dimensional (2D) superconductors supply important platforms for exploring new quantum physics and high-$T_c$ superconductivity. The intrinsic superconducting properties in the 2D iron-arsenic superconductors are still unknown owing to the difficulties in the preparation of ultrathin samples. Here we report the fabrication and physical investigations of the high quality single-crystalline ultrathin films of the iron-arsenic superconductor KCa$_2$Fe$_4$As$_4$F$_2$. For the sample with the thickness of 2.6$\sim$5 nm (1$\sim$2 unit cells), a sharp superconducting transition at around 30 K (onset point) is observed. Compare with the bulk material, the ultrathin sample reveals a relatively lower $T_c$, wider transition width, and broader flux liquid region under the in-plane field. Moreover, the angle dependent upper critical field follows the Tinkham model, demonstrating the two-dimensional superconductivity in ultrathin KCa$_2$Fe$_4$As$_4$F$_2$.

cond-mat.supr-con↗

arXiv2020

Low temperature specific heat of 12442-type KCa_2Fe_4As_4F_2 single crystals

Low-temperature specific heat (SH) is measured for the 12442-type KCa$_2$Fe$_4$As$_4$F$_2$ single crystal under different magnetic fields. A clear SH jump with the height of $ΔC/T|_{T_c}$ = 130 mJ/mol K$^2$ is observed at the superconducting transition temperature $T_c$. It is found that the electronic SH coefficient $Δγ(H)$ quickly increases when the field is in the low-field region below 3 T and then considerably slows down the increase with a further increase in the field, which indicates a rather strong anisotropy or multi-gap feature with a small minimum in the superconducting gap(s). The temperature-dependent SH data indicates the presence of the $T^2$ term, which supplies further information and supports the picture with a line-nodal gap structure. Moreover, the onset point of the SH transition remains almost unchanged under the field as high as 9 T, which is similar to that observed in cuprates, and placed this system in the middle between the BCS limit and the Bose-Einstein condensation.

cond-mat.supr-con↗

arXiv2019

A Survey of FPGA Based Deep Learning Accelerators: Challenges and Opportunities

With the rapid development of in-depth learning, neural network and deep learning algorithms have been widely used in various fields, e.g., image, video and voice processing. However, the neural network model is getting larger and larger, which is expressed in the calculation of model parameters. Although a wealth of existing efforts on GPU platforms currently used by researchers for improving computing performance, dedicated hardware solutions are essential and emerging to provide advantages over pure software solutions. In this paper, we systematically investigate the neural network accelerator based on FPGA. Specifically, we respectively review the accelerators designed for specific problems, specific algorithms, algorithm features, and general templates. We also compared the design and implementation of the accelerator based on FPGA under different devices and network models and compared it with the versions of CPU and GPU. Finally, we present to discuss the advantages and disadvantages of accelerators on FPGA platforms and to further explore the opportunities for future research.

cs.DC↗

arXiv2019

Reviewing and Improving the Gaussian Mechanism for Differential Privacy

Differential privacy provides a rigorous framework to quantify data privacy, and has received considerable interest recently. A randomized mechanism satisfying $(ε, δ)$-differential privacy (DP) roughly means that, except with a small probability $δ$, altering a record in a dataset cannot change the probability that an output is seen by more than a multiplicative factor $e^ε $. A well-known solution to $(ε, δ)$-DP is the Gaussian mechanism initiated by Dwork et al. [1] in 2006 with an improvement by Dwork and Roth [2] in 2014, where a Gaussian noise amount $\sqrt{2\ln \frac{2}δ} \times \fracΔε$ of [1] or $\sqrt{2\ln \frac{1.25}δ} \times \fracΔε$ of [2] is added independently to each dimension of the query result, for a query with $\ell_2$-sensitivity $Δ$. Although both classical Gaussian mechanisms [1,2] assume $0 < ε\leq 1$, our review finds that many studies in the literature have used the classical Gaussian mechanisms under values of $ε$ and $δ$ where the added noise amounts of [1,2] do not achieve $(ε,δ)$-DP. We obtain such result by analyzing the optimal noise amount $σ_{DP-OPT}$ for $(ε,δ)$-DP and identifying $ε$ and $δ$ where the noise amounts of classical mechanisms are even less than $σ_{DP-OPT}$. Since $σ_{DP-OPT}$ has no closed-form expression and needs to be approximated in an iterative manner, we propose Gaussian mechanisms by deriving closed-form upper bounds for $σ_{DP-OPT}$. Our mechanisms achieve $(ε,δ)$-DP for any $ε$, while the classical mechanisms [1,2] do not achieve $(ε,δ)$-DP for large $ε$ given $δ$. Moreover, the utilities of our mechanisms improve those of [1,2] and are close to that of the optimal yet more computationally expensive Gaussian mechanism.

cs.CR↗

arXiv2019

Strong Pauli paramagnetic effect in the upper critical field of KCa$_2$Fe$_4$As$_4$F$_2$

Recently, 12442 system of Fe-based superconductors has attracted considerable attention owing to its unique double-FeAs-layer structure. A steep increase in the in-plane upper critical field with cooling has been observed near the superconducting transition temperature, $T_c$, in KCa$_2$Fe$_4$As$_4$F$_2$ single crystals. Herein, we report a high-field investigation on upper critical field of this material over a wide temperature range, and both out-of-plane ($H\|c$, $H_{c2}^{c}$) and in-plane ($H\|ab$, $H_{c2}^{ab}$) directions have been measured. A sublinear temperature-dependent behavior is observed for the out-of-plane $H_{c2}^{c}$, whereas strong convex curvature with cooling is observed for the in-plane $H_{c2}^{ab}$. Such behaviors could not be described by the conventional Werthamer--Helfand--Hohenberg (WHH) model. The data analysis based on the WHH model by considering the spin aspects reveals a large Maki parameter $α=9$, indicating that the in-plane upper critical field is affected by a very strong Pauli paramagnetic effect.

cond-mat.supr-con↗

arXiv2019

Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas

With the rapid development of artificial intelligence (AI), ethical issues surrounding AI have attracted increasing attention. In particular, autonomous vehicles may face moral dilemmas in accident scenarios, such as staying the course resulting in hurting pedestrians or swerving leading to hurting passengers. To investigate such ethical dilemmas, recent studies have adopted preference aggregation, in which each voter expresses her/his preferences over decisions for the possible ethical dilemma scenarios, and a centralized system aggregates these preferences to obtain the winning decision. Although a useful methodology for building ethical AI systems, such an approach can potentially violate the privacy of voters since moral preferences are sensitive information and their disclosure can be exploited by malicious parties. In this paper, we report a first-of-its-kind privacy-preserving crowd-guided AI decision-making approach in ethical dilemmas. We adopt the notion of differential privacy to quantify privacy and consider four granularities of privacy protection by taking voter-/record-level privacy protection and centralized/distributed perturbation into account, resulting in four approaches VLCP, RLCP, VLDP, and RLDP. Moreover, we propose different algorithms to achieve these privacy protection granularities, while retaining the accuracy of the learned moral preference model. Specifically, VLCP and RLCP are implemented with the data aggregator setting a universal privacy parameter and perturbing the averaged moral preference to protect the privacy of voters' data. VLDP and RLDP are implemented in such a way that each voter perturbs her/his local moral preference with a personalized privacy parameter. Extensive experiments on both synthetic and real data demonstrate that the proposed approach can achieve high accuracy of preference aggregation while protecting individual voter's privacy.

cs.CR↗

arXiv2019

Conditional Analysis for Key-Value Data with Local Differential Privacy

Local differential privacy (LDP) has been deemed as the de facto measure for privacy-preserving distributed data collection and analysis. Recently, researchers have extended LDP to the basic data type in NoSQL systems: the key-value data, and show its feasibilities in mean estimation and frequency estimation. In this paper, we develop a set of new perturbation mechanisms for key-value data collection and analysis under the strong model of local differential privacy. Since many modern machine learning tasks rely on the availability of conditional probability or the marginal statistics, we then propose the conditional frequency estimation method for key analysis and the conditional mean estimation for value analysis in key-value data. The released statistics with conditions can further be used in learning tasks. Extensive experiments of frequency and mean estimation on both synthetic and real-world datasets validate the effectiveness and accuracy of the proposed key-value perturbation mechanisms against the state-of-art competitors.

cs.CR↗

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

Locally Differentially Private Data Collection and Analysis

Local differential privacy (LDP) can provide each user with strong privacy guarantees under untrusted data curators while ensuring accurate statistics derived from privatized data. Due to its powerfulness, LDP has been widely adopted to protect privacy in various tasks (e.g., heavy hitters discovery, probability estimation) and systems (e.g., Google Chrome, Apple iOS). Although $ε$-LDP has been proposed for many years, the more general notion of $(ε, δ)$-LDP has only been studied in very few papers, which mainly consider mean estimation for numeric data. Besides, prior solutions achieve $(ε, δ)$-LDP by leveraging Gaussian mechanism, which leads to low accuracy of the aggregated results. In this paper, we propose novel mechanisms that achieve $(ε, δ)$-LDP with high utility in data analytics and machine learning. Specifically, we first design $(ε, δ)$-LDP algorithms for collecting multi-dimensional numeric data, which can ensure higher accuracy than the optimal Gaussian mechanism while guaranteeing strong privacy for each user. Then, we investigate different local protocols for categorical attributes under $(ε, δ)$-LDP. Furthermore, we conduct theoretical analysis on the error bound and variance of the proposed algorithms. Experimental results on real and synthetic datasets demonstrate the high data utility of our proposed algorithms on both simple data statistics and complex machine learning models.

cs.CR↗

arXiv2019

Single-crystal growth and extremely high H_c2 of 12442-type Fe-based superconductor KCa_2Fe_4As_4F_2

Millimeter sized single crystals of KCa_2Fe_4As_4F_2 were grown using a self-flux method. The chemical compositions and crystal structure were characterized carefully. Superconductivity with the critical transition T_c = 33.5 K was confirmed by both the resistivity and magnetic susceptibility measurements. Moreover, the upper critical field H_c2 was studied by the resistivity measurements under different magnetic fields. A rather steep increase for the in-plane H_c2^ab with cooling, dμ_0H_c2^a/dT|T_c = -50.9 T/K, was observed, indicating an extremely high upper critical field. Possible origins for this behavior were discussed. The findings in our work is a great promotion both for understanding the physical properties and applications of 12442-type Fe-based superconductors.

cond-mat.supr-con↗

arXiv2019

Nonlinear stability of planar rarefaction wave to the three-dimensional Boltzmann equation

We investigate the time-asymptotic stability of planar rarefaction wave for the three-dimensional Boltzmann equation, based on the micro-macro decomposition introduced in [24, 22] and our new observations on the underlying wave structures of the equation to overcome the difficulties due to the wave propagation along the transverse directions and its interactions with the planar rarefaction wave. Note that this is the first stability result of planar rarefaction wave for 3D Boltzmann equation, while the corresponding results for the shock and contact discontinuities are still completely open.

math.AP↗

arXiv2019

Stability of planar rarefaction wave to 3D full compressible Navier-Stokes equations

We prove the time-asymptotic stability toward planar rarefaction wave for the three-dimensional full compressible Navier-Stokes equations in an infinite long flat nozzle domain $\mathbb{R}\times\mathbb{T}^2$. Compared with one-dimensional case, the proof here is based on our new observations on the cancellations on the flux terms and viscous terms due to the underlying wave structures, which are crucial to overcome the difficulties due to the wave propagation along the transverse directions $x_2$ and $x_3$ and its interactions with the planar rarefaction wave in $x_1$ direction.

math.AP↗

arXiv2017

Stability of the Superposition of a Viscous Contact Wave with two Rarefaction Waves to the bipolar Vlasov-Poisson-Boltzmann System

We investigate the nonlinear stability of the superposition of a viscous contact wave and two rarefaction waves for one-dimensional bipolar Vlasov-Poisson-Boltzmann (VPB) system, which can be used to describe the transportation of charged particles under the additional electrostatic potential force. Based on a new micro-macro type decomposition around the local Maxwellian related to the bipolar VPB system in our previous work [26], we prove that the superposition of a viscous contact wave and two rarefaction waves is time-asymptotically stable to 1D bipolar VPB system under some smallness conditions on the initial perturbations and wave strength, which implies that this typical composite wave pattern is nonlinearly stable under the combined effects of the binary collisions, the electrostatic potential force, and the mutual interactions of different charged particles. Note that this is the first result about the nonlinear stability of the combination of two different wave patterns for the Vlasov-Poisson-Boltzmann system.

math.AP↗