arXiv subjects

Li Yu

Publications and source records attributed to Li Yu.

At least 145 records · Page 8Linked to original sources

arXiv2021

Delay-Dependent Distributed Kalman Fusion Estimation with Dimensionality Reduction in Cyber-Physical Systems

This paper studies the distributed dimensionality reduction fusion estimation problem with communication delays for a class of cyber-physical systems (CPSs). The raw measurements are preprocessed in each sink node to obtain the local optimal estimate (LOE) of a CPS, and the compressed LOE under dimensionality reduction encounters with communication delays during the transmission. Under this case, a mathematical model with compensation strategy is proposed to characterize the dimensionality reduction and communication delays. This model also has the property to reduce the information loss caused by the dimensionality reduction and delays. Based on this model, a recursive distributed Kalman fusion estimator (DKFE) is derived by optimal weighted fusion criterion in the linear minimum variance sense. A stability condition for the DKFE, which can be easily verified by the exiting software, is derived. In addition, this condition can guarantee that estimation error covariance matrix of the DKFE converges to the unique steady-state matrix for any initial values, and thus the steady-state DKFE (SDKFE) is given. Notice that the computational complexity of the SDKFE is much lower than that of the DKFE. Moreover, a probability selection criterion for determining the dimensionality reduction strategy is also presented to guarantee the stability of the DKFE. Two illustrative examples are given to show the advantage and effectiveness of the proposed methods.

eess.SY↗

arXiv2021

Unusual normal and superconducting state properties observed in hydrothermal Fe1-xSe flakes

The electronic and superconducting properties of Fe1-xSe single-crystal flakes grown hydrothermally are studied by the transport measurements under zero and high magnetic fields up to 38.5 T. The results contrast sharply with those previously reported for nematically ordered FeSe by chemical-vapor-transport (CVT) growth. No signature of the electronic nematicity, but an evident metal-to-nonmetal crossover with increasing temperature, is detected in the normal state of the present hydrothermal samples. Interestingly, a higher superconducting critical temperature Tc of 13.2 K is observed compared to a suppressed Tc of 9 K in the presence of the nematicity in the CVT FeSe. Moreover, the upper critical field in the zero-temperature limit is found to be isotropic with respect to the field direction and to reach a higher value of ~42 T, which breaks the Pauli limit by a factor of 1.8.

cond-mat.supr-con↗

arXiv2021

Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching

Image-text matching is an important multi-modal task with massive applications. It tries to match the image and the text with similar semantic information. Existing approaches do not explicitly transform the different modalities into a common space. Meanwhile, the attention mechanism which is widely used in image-text matching models does not have supervision. We propose a novel attention scheme which projects the image and text embedding into a common space and optimises the attention weights directly towards the evaluation metrics. The proposed attention scheme can be considered as a kind of supervised attention and requiring no additional annotations. It is trained via a novel Discrete-continuous action space policy gradient algorithm, which is more effective in modelling complex action space than previous continuous action space policy gradient. We evaluate the proposed methods on two widely-used benchmark datasets: Flickr30k and MS-COCO, outperforming the previous approaches by a large margin.

cs.CV↗

arXiv2021

Anisotropic superconducting properties of Kagome metal CsV3Sb5

We systematically measure the superconducting (SC) and mixed state properties of high-quality CsV3Sb5 single crystals with Tc ~ 3.5 K. We find that the upper critical field Hc2(T) exhibits a large anisotropic ratio of Hc2^(ab)/Hc2^(c) ~ 9 at zero temperature and fitting its temperature dependence requires a minimum two-band effective model. Moreover, the ratio of the lower critical field, Hc1^(ab)/Hc1^(c), is also found to be larger than 1, which indicates that the in-plane energy dispersion is strongly renormalized near Fermi energy. Both Hc1(T) and SC diamagnetic signal are found to change little initially below Tc ~ 3.5 K and then to increase abruptly upon cooling to a characteristic temperature of ~2.8 K. Furthermore, we identify a two-fold anisotropy of in-plane angular-dependent magnetoresistance in the mixed state. Interestingly, we find that, below the same characteristic T ~ 2.8 K, the orientation of this two-fold anisotropy displays a peculiar twist by an angle of 60o characteristic of the Kagome geometry. Our results suggest an intriguing superconducting state emerging in the complex environment of Kagome lattice, which, at least, is partially driven by electron-electron correlation.

cond-mat.supr-con↗

arXiv2021

Quantum preprocessing for information-theoretic security in two-party computation

In classical two-party computation, a trusted initializer who prepares certain initial correlations, known as one-time tables, can help make the inputs of both parties information-theoretically secure. We propose some bipartite quantum protocols with possible aborts for approximately generating such bipartite classical correlations with varying degrees of privacy, without introducing a third party. Under some weak requirements for the parties, the security level is nontrivial for use in bipartite computation. We show that the security is sometimes dependent on the noise level, but we propose a method for dealing with noise. The security is "forced security", which implies that the probability that some useful one-time tables are generated can approach $1$ in the noiseless case under quite weak assumptions about the parties, although the protocols allow aborts. We show how to use the generated one-time tables to achieve nontrivial information-theoretic security in generic two-party classical or quantum computation tasks, including (interactive) quantum homomorphic encryption. Our methods provide check-based implementations of some no-signaling correlations, including the PR-box type, with the help of communication which carry no information about the inputs in the generated correlations.

quant-ph↗

arXiv2021

Distinctive momentum dependent charge-density-wave gap observed in CsV$_3$Sb$_5$ superconductor with topological Kagome lattice

CsV$_3$Sb$_5$ is a newly discovered Kagome superconductor that attracts great interest due to its topological nontrivial band structure and the coexistence of superconductivity and charge-density-wave (CDW) with many exotic properties. Here, we report the detailed characterization of the CDW gap in high-quality CsV$_3$Sb$_5$ single crystals using high-resolution angle-resolved photoemission spectroscopy. We find that the CDW gap is strongly momentum dependent. While gapped around the $M$ point, the electronic states remain gapless around the $Γ$ point and along the $Γ$-$K$ direction. Such momentum dependence indicates that the CDW is driven by the scattering of electrons between neighboring $M$ points, where the band structure hosts multiple saddle points and the density of state diverges near the Fermi level. Our observations of the partially gapped Fermi surface and strongly momentum-dependent CDW gap not only provide a foundation for uncovering the mechanism of CDW in CsV$_3$Sb$_5$, but also shed light on the understanding of how the CDW coexists with superconductivity in this topological Kagome superconductor.

cond-mat.supr-con↗

arXiv2021

Noisy Student Training using Body Language Dataset Improves Facial Expression Recognition

Facial expression recognition from videos in the wild is a challenging task due to the lack of abundant labelled training data. Large DNN (deep neural network) architectures and ensemble methods have resulted in better performance, but soon reach saturation at some point due to data inadequacy. In this paper, we use a self-training method that utilizes a combination of a labelled dataset and an unlabelled dataset (Body Language Dataset - BoLD). Experimental analysis shows that training a noisy student network iteratively helps in achieving significantly better results. Additionally, our model isolates different regions of the face and processes them independently using a multi-level attention mechanism which further boosts the performance. Our results show that the proposed method achieves state-of-the-art performance on benchmark datasets CK+ and AFEW 8.0 when compared to other single models.

cs.CV↗

arXiv2021

Spotting Silent Buffer Overflows in Execution Trace through Graph Neural Network Assisted Data Flow Analysis

A software vulnerability could be exploited without any visible symptoms. When no source code is available, although such silent program executions could cause very serious damage, the general problem of analyzing silent yet harmful executions is still an open problem. In this work, we propose a graph neural network (GNN) assisted data flow analysis method for spotting silent buffer overflows in execution traces. The new method combines a novel graph structure (denoted DFG+) beyond data-flow graphs, a tool to extract {\tt DFG+} from execution traces, and a modified Relational Graph Convolutional Network as the GNN model to be trained. The evaluation results show that a well-trained model can be used to analyze vulnerabilities in execution traces (of previously-unseen programs) without support of any source code. Our model achieves 94.39\% accuracy on the test data and successfully locates 29 out of 30 real-world silent buffer overflow vulnerabilities. Leveraging deep learning, the proposed method is, to our best knowledge, the first general-purpose analysis method for silent buffer overflows. It is also the first method to spot silent buffer overflows in global variables, stack variables, or heap variables without crossing the boundary of allocated chunks.

cs.CR↗

arXiv2021

Back-n White Neutron Source at CSNS and its Applications

Back-streaming neutrons from the spallation target of the China Spallation Neutron Source (CSNS) that emit through the incoming proton channel were exploited to build a white neutron beam facility (the so-called Back-n white neutron source), which was completed in March 2018. The Back-n neutron beam is very intense, at approximately 2*10^7 n/cm^2/s at 55 m from the target, and has a nominal proton beam with a power of 100 kW in the CSNS-I phase and a kinetic energy of 1.6 GeV and a thick tungsten target in multiple slices with modest moderation from the cooling water through the slices. In addition, the excellent energy spectrum spanning from 0.5 eV to 200 MeV, and a good time resolution related to the time-of-flight measurements make it a typical white neutron source for nuclear data measurements; its overall performance is among that of the best white neutron sources in the world. Equipped with advanced spectrometers, detectors, and application utilities, the Back-n facility can serve wide applications, with a focus on neutron-induced cross-section measurements. This article presents an overview of the neutron beam characteristics, the experimental setups, and the ongoing applications at Back-n.

physics.acc-ph↗

arXiv2020

Ultra-short pulses with high repetition frequency in transmission plasmonic systems

Ultra-short pulses with high repetition frequency have great application prospects in the field of nano-optics. Here, in the case of continuous wave incidence, the femtosecond pulses with THz repetition frequency are achieved in the transmission system consisting of a rectangular cavity, a V-groove (VG) cavity and a nanowire embedded with quantum emitters (QEs). The generation mechanism of the ultra-short pulses with high repetition frequency is elucidated by semi-classical Dicke model. Attribute to the presence of the two-level QEs, the field amplitude in plasmonic resonator is oscillating with time, resulting in the transmittance of the system behave as the form of pulse oscillation. Moreover, The pulse repetition frequency and extinction ratio can be freely controlled by the incident light intensity and QEs number density to obtain the required ultra-short pulses at nanoscale, which also has potential applications in optical computing.

physics.optics↗

arXiv2020

Electronic phase diagram of iron chalcogenide superconductors FeSe1-xSx and FeSe1-yTey

Here we establish a combined electronic phase diagram of isoelectronic FeSe1-xSx (0.19 > x > 0.0) and FeSe1-yTey (0.04 < y < 1.0) single crystals. The FeSe1-yTey crystals with y = 0.04 - 0.30 are grown by a hydrothermal ion-deintercalation (HID) method. Based on combined experiments of the specific heat, electrical transport, and angle-resolved photoemission spectroscopy, no signature of the tetragonal-symmetry-broken transition to orthorhombic (nematic) phase is observed in the HID FeSe1-yTey samples, as compared with the FeSe1-xSx samples showing this transition at Ts. A ubiquitous dip-like temperature dependence of the Hall coefficient is observed around a characteristic temperature T* in the tetragonal regimes, which is well above the superconducting transition. More importantly, we find that the superconducting transition temperature Tc is positively correlated with the Hall-dip temperature T* across the FeSe1-xSx and FeSe1-yTey systems, suggesting that the tetragonal background is a fundamental host for the superconductivity.

cond-mat.supr-con↗

arXiv2020

Gesture Recognition using Reflected Visible and Infrared Light Wave Signals

In this paper, we demonstrate the ability to recognize hand gestures in a non-contact, wireless fashion using only incoherent light signals reflected from a human subject. Fundamentally distinguished from radar, lidar and camera-based sensing systems, this sensing modality uses only a low-cost light source (e.g., LED) and sensor (e.g., photodetector). The light-wave-based gesture recognition system identifies different gestures from the variations in light intensity reflected from the subject's hand within a short (20-35 cm) range. As users perform different gestures, scattered light forms unique, statistically repeatable, time-domain signatures. These signatures can be learned by repeated sampling to obtain the training model against which unknown gesture signals are tested and categorized. Performance evaluations have been conducted with eight gestures, five subjects, different distances and lighting conditions, and with visible and infrared light sources. The results demonstrate the best hand gesture recognition performance of infrared sensing at 20 cm with an average of 96% accuracy. The developed gesture recognition system is low-cost, effective and non-contact technology for numerous Human-computer Interaction (HCI) applications.

eess.SP↗

arXiv2020

DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving

We present a visual localization framework based on novel deep attention aware features for autonomous driving that achieves centimeter level localization accuracy. Conventional approaches to the visual localization problem rely on handcrafted features or human-made objects on the road. They are known to be either prone to unstable matching caused by severe appearance or lighting changes, or too scarce to deliver constant and robust localization results in challenging scenarios. In this work, we seek to exploit the deep attention mechanism to search for salient, distinctive and stable features that are good for long-term matching in the scene through a novel end-to-end deep neural network. Furthermore, our learned feature descriptors are demonstrated to be competent to establish robust matches and therefore successfully estimate the optimal camera poses with high precision. We comprehensively validate the effectiveness of our method using a freshly collected dataset with high-quality ground truth trajectories and hardware synchronization between sensors. Results demonstrate that our method achieves a competitive localization accuracy when compared to the LiDAR-based localization solutions under various challenging circumstances, leading to a potential low-cost localization solution for autonomous driving.

cs.CV↗

arXiv2020

Classical non-equilibrium statistical mechanics and an "open system dynamics" perspective on quantum-classical analogy

It is well known that the statistics of closed classical systems evolves according to the Liouville theorem. Here we study the dynamics of the marginal statistics of classical systems coupled to external degrees of freedom, by developing a time-local equation of motion using Green's functions and a series expansion method. We also compare this equation of motion with its supposed quantum counterpart, namely the quantum master equation, which we hope could shed some light on quantum-classical analogy (QCA) from the perspective of "open system dynamics". We notice an apparent exception to QCA in this case, as the first-order classical equation of motion derived herein contains a term that does not appear to have a quantum analogue. We also propose possible ways of getting around this tension, which may help re-establish QCA (in first perturbative order). We do not draw a definitive conclusion about QCA in the context of open system dynamics but hope to provide a starting point for investigations along this line.

cond-mat.stat-mech↗

arXiv2020

Unifying the dynamical effects of quantum and classical noises

We develop a new master equation as a unified description of the effects of both quantum noise (system-bath interaction) and classical noise on a system's dynamics, using a two-dimensional series expansion method. When quantum and classical noises are both present, their combined effect on a system's dynamics is not necessarily a simple sum of the two individual effects. Thus previous master equations for open systems and those for classical noise, even when jointly used, may not capture the full physics. Our formalism can determine whether there is interference between quantum and classical noises and will be able to capture and describe such interference if there is any (in a perturbative manner). We find that, interestingly, second-order interference between quantum and classical noises vanishes identically. This work thus also serves to justify simple additive treatments of quantum and classical noises, especially in the weak coupling regime. For a Zeeman-splitted atom in a stochastic magnetic field interacting with an optical cavity, we use the formalism developed herein to find the overall decoherence rate between the atom's energy levels.

quant-ph↗

arXiv2020

A formally exact master equation for open quantum systems

We present a succinct and intuitive derivation of a formally exact master equation for general open quantum systems, without the use of an "inverse" map which was invoked in previous works on formally exact master equations. This formalism is applicable to non-Markovian regimes. We derive a second-order equation of motion for the illustrative spin-boson model at arbitrary temperatures, observing non-exponential decoherence and relaxation. Limiting our generic derivation to zero temperature, we also reproduce the result for the special case of a vacuum bath in Phys. Rev. A 81, 042103 (2010).

quant-ph↗

arXiv2020

Measurement of the neutron beam profile of the Back-n white neutron facility at CSNS with a Micromegas detector

The Back-n white neutron beam line, which uses back-streaming white neutrons from the spallation target of the China Spallation Neutron Source, is used for nuclear data measurements. A Micromegas-based neutron detector with two variants was specially developed to measure the beam spot distribution for this beam line. In this article, the design, fabrication, and characterization of the detector are described. The results of the detector performance tests are presented, which include the relative electron transparency, the gain and the gain uniformity, and the neutron beam profile reconstruction capability. The result of the first measurement of the Back-n neutron beam spot distribution is also presented.

physics.ins-det↗

arXiv2019

Emergence of superconductivity in strongly correlated hole-dominated Fe1-xSe

Here we establish a more complete phase diagram for FeSe system, based on experimental results of nonstoichiometric Fe1-xSe single crystals that we have developed recently, as well as nearly stoichiometric FeSe single crystals. The electronic correlation is found to be strongly enhanced in hole-dominated Fe1-xSe, as compared with electron-dominated FeSe, from the magnetic susceptibility and electrical transport measurements in the normal state. A superconducting dome is found to emerge starting from the strongly correlated hole-dominated regime with electron doping, while the tetragonal-orthorhombic phase transition at ~90 K is observed only at higher electron-doping levels in the electron-dominated regime.

cond-mat.supr-con↗