arXiv subjects

Chi Zhang

Publications and source records attributed to Chi Zhang.

At least 865 records · Page 48Linked to original sources

arXiv2017

Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification

Person re-identification (ReID) is an important task in computer vision. Recently, deep learning with a metric learning loss has become a common framework for ReID. In this paper, we also propose a new metric learning loss with hard sample mining called margin smaple mining loss (MSML) which can achieve better accuracy compared with other metric learning losses, such as triplet loss. In experi- ments, our proposed methods outperforms most of the state-of-the-art algorithms on Market1501, MARS, CUHK03 and CUHK-SYSU.

cs.CV↗

arXiv2017

Dynamical and structural signatures of the glass transition in emulsions

We investigate structural and dynamical properties of moderately polydisperse emulsions across an extended range of droplet volume fractions phgr, encompassing fluid and glassy states up to jamming. Combining experiments and simulations, we show that when $ϕ$ approaches the glass transition volume fraction ${ϕ_{g}}$ , dynamical heterogeneities and amorphous order arise within the emulsion. In particular, we find an increasing number of clusters of particles having five-fold symmetry (i.e. the so-called locally favoured structures, LFS) as $ϕ$ approaches ${ϕ_{g}}$ , saturating to a roughly constant value in the glassy regime. However, contrary to previous studies, we do not observe a corresponding growth of medium-range crystalline order; instead, the emergence of LFS is decoupled from the appearance of more ordered regions in our system. We also find that the static correlation lengths associated with the LFS and with the fastest particles can be successfully related to the relaxation time of the system. By contrast, this does not hold for the length associated with the orientational order. Our study reveals the existence of a link between dynamics and structure close to the glass transition even in the absence of crystalline precursors or crystallization. Furthermore, the quantitative agreement between our confocal microscopy experiments and Brownian dynamics simulations indicates that emulsions are and will continue to be important model systems for the investigation of the glass transition and beyond.

cond-mat.soft↗

arXiv2017

An silicon nanocrystal laser

Silicon lasers have been the most challenging element for the monolithic integrated Si photonics. Here we report the first successful all-Si laser at room temperature based on silicon nanocrystals (Si NCs) with high optical gains. The active Si NC layer was made from hydrogen silsesquioxane (HSQ) that had undergone a phase separation annealing, followed by high-pressure hydrogen passivation. Using the nanoimprint technique, a second-order Bragg grating was made on the active layer as the distributed feedback (DFB) laser cavity. This Si NC DFB laser device was optically pumped with femtosecond pulses. Criteria for lasing action, i.e., the threshold effect, the polarization dependence and the significant spectral narrowing of stimulated emission were evidently fulfilled, which indicated the realization of an all-Si laser.

physics.optics↗

arXiv2017

Learning Unmanned Aerial Vehicle Control for Autonomous Target Following

While deep reinforcement learning (RL) methods have achieved unprecedented successes in a range of challenging problems, their applicability has been mainly limited to simulation or game domains due to the high sample complexity of the trial-and-error learning process. However, real-world robotic applications often need a data-efficient learning process with safety-critical constraints. In this paper, we consider the challenging problem of learning unmanned aerial vehicle (UAV) control for tracking a moving target. To acquire a strategy that combines perception and control, we represent the policy by a convolutional neural network. We develop a hierarchical approach that combines a model-free policy gradient method with a conventional feedback proportional-integral-derivative (PID) controller to enable stable learning without catastrophic failure. The neural network is trained by a combination of supervised learning from raw images and reinforcement learning from games of self-play. We show that the proposed approach can learn a target following policy in a simulator efficiently and the learned behavior can be successfully transferred to the DJI quadrotor platform for real-world UAV control.

cs.AI↗

arXiv2017

Three-Dimensional Anisotropic Magnetoresistance in the Dirac Node-Line Material ZrSiSe

The family of materials defined as ZrSiX (X = S, Se, Te) has been established as Dirac node-line semimetals, and subsequent study is urgent to exploit the promising application of unusual magnetoresistance property. In this work, we systematically investigated the anisotropic magnetoresistance in the newly-discovered Dirac node-line material ZrSiSe. By applying a magnetic field of 3 T by a vector field, the three-dimensional (3D) magnetoresistance (MR) shows strong anisotropy. The MR ratio of maximum and minimum directions can reach 7 at 3 T and keeps increasing at the higher magnetic field. The anisotropic MR forms a butterfly-shaped curve, which indicates the quasi-2D electronic structures. This is further confirmed by the angular-dependent Shubnikov-de Haas (SdH) oscillations. The first-principles calculations establish the quasi-2D tubular-shaped Fermi surface near the X point in the Brillouin zone. Our findings shed light on the 3D mapping of MR and the potential applications in magnetic sensors based on ZrSiSe Dirac materials.

cond-mat.mes-hall↗

arXiv2017

Low-Frequency Microwave Induced Quantum Oscillations in A Two-Dimensional Electron System

We study the magnetoresistance of an ultrahigh mobility GaAs/AlGaAs two-dimensional electron sample in a weak magnetic field under low-frequency (f < 20 GHz) microwave (MW) irradiation. We observe that with decreasing MW frequency, microwave induced resistance oscillations (MIRO) damp and multi-photon processes become dominant. At very low MW frequency (f < 4 GHz), MIRO disappears gradually and a new SdH-like oscillation develops. The analysis indicates that the new oscillation may originate from alternating Hall-field induced resistance oscillations (ac-HIRO), or can be viewed as a multi-photon process of MIRO in low MW frequency limit. Our findings bridge the non-equilibrium states of MIRO and HIRO, which can be brought into a frame of quantum tunneling junction model.

cond-mat.mes-hall↗

arXiv2017

Coherent control of a single trapped Rydberg ion

Trapped Rydberg ions are a promising novel approach to quantum computing and simulations. They are envisaged to combine the exquisite control of trapped ion qubits with the fast two-qubit Rydberg gates already demonstrated in neutral atom experiments. Coherent Rydberg excitation is a key requirement for these gates. Here, we carry out the first coherent Rydberg excitation of an ion and perform a single-qubit Rydberg gate, thus demonstrating basic elements of a trapped Rydberg ion quantum computer.

quant-ph↗

arXiv2017

A Generalization of the Doubling Construction for Sums of Squares Identities

The doubling construction is a fast and important way to generate new solutions to the Hurwitz problem on sums of squares identities from any known ones. In this short note, we generalize the doubling construction and obtain from any given admissible triple $[r,s,n]$ a series of new ones $[r+ρ(2^{m-1}),2^ms,2^mn]$ for all positive integer $m$, where $ρ$ is the Hurwitz-Radon function.

math.RA↗

arXiv2017

Efficient Eye Typing with 9-direction Gaze Estimation

Vision based text entry systems aim to help disabled people achieve text communication using eye movement. Most previous methods have employed an existing eye tracker to predict gaze direction and design an input method based upon that. However, these methods can result in eye tracking quality becoming easily affected by various factors and lengthy amounts of time for calibration. Our paper presents a novel efficient gaze based text input method, which has the advantage of low cost and robustness. Users can type in words by looking at an on-screen keyboard and blinking. Rather than estimate gaze angles directly to track eyes, we introduce a method that divides the human gaze into nine directions. This method can effectively improve the accuracy of making a selection by gaze and blinks. We build a Convolutional Neural Network (CNN) model for 9-direction gaze estimation. On the basis of the 9-direction gaze, we use a nine-key T9 input method which is widely used in candy bar phones. Bar phones were very popular in the world decades ago and have cultivated strong user habits and language models. To train a robust gaze estimator, we created a large-scale dataset with images of eyes sourced from 25 people. According to the results from our experiments, our CNN model is able to accurately estimate different people's gaze under various lighting conditions by different devices. In considering disable people's needs, we removed the complex calibration process. The input methods can run in screen mode and portable off-screen mode. Moreover, The datasets used in our experiments are made available to the community to allow further experimentation.

cs.CV↗

arXiv2017

Saliency Detection by Forward and Backward Cues in Deep-CNNs

As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used to detect salient objects on images regardless of the object class is in the network knowledge or not. In this paper, we propose a top-down saliency model using CNN, a weakly supervised CNN model trained for 1000 object labelling task from RGB images. The model detects attentive regions based on their objectness scores predicted by selected features from CNNs. To estimate the salient objects effectively, we combine both forward and backward features, while demonstrating that partially-guided backpropagation will provide sufficient information for selecting the features from forward run of CNN model. Finally, these top-down cues are enhanced with a state-of-the-art bottom-up model as complementing the overall saliency. As the proposed model is an effective integration of forward and backward cues through objectness without any supervision or regression to ground truth data, it gives promising results compared to state-of-the-art models in two different datasets.

cs.CV↗

arXiv2017

Tuning Edge States in Strained-Layer InAs/GaInSb Quantum Spin Hall Insulators

We report on a class of quantum spin Hall insulators (QSHIs) in strained-layer InAs/GaInSb quantum wells, in which the bulk gaps are enhanced by up to five folds as compared to the binary InAs/GaSb QSHI. Remarkably, with consequently increasing edge velocity, the edge conductance at zero and applied magnetic fields manifests time reversal symmetry (TRS) -protected properties consistent with Z2 topological insulator. The InAs/GaInSb bilayers offer a much sought-after platform for future studies and applications of the QSHI.

cond-mat.mes-hall↗

arXiv2017

One loop amplitude from null string

We generalize the CHY formalism to one-loop level, based on the framework of the null string theory. The null string, a tensionless string theory, produces the same results as the ones from the chiral ambitwistor string theory, with the latter believed to give a string interpretation of the CHY formalism. A key feature of our formalism is the interpretation of the modular parameters. We find that the $S$ modular transformation invariance of the ordinary string theory does not survive in the case of the null string theory. Treating the integration over the modular parameters this way enable us to derive the n-gons scattering amplitude in field theory, thus proving the n-gons conjecture.

hep-th↗

arXiv2017

Session-Based Cooperation in Cognitive Radio Networks: A Network-Level Approach

In cognitive radio networks (CRNs), secondary users (SUs) can proactively obtain spectrum access opportunities by helping with primary users' (PUs') data transmissions. Currently, such kind of spectrum access is implemented via a cooperative communications based link-level frame-based cooperative (LLC) approach where individual SUs independently serve as relays for PUs in order to gain spectrum access opportunities. Unfortunately, this LLC approach cannot fully exploit spectrum access opportunities to enhance the throughput of CRNs and fails to motivate PUs to join the spectrum sharing processes. To address these challenges, we propose a network-level session-based cooperative (NLC) approach where SUs are grouped together to cooperate with PUs session by session, instead of frame by frame as what has been done in existing works, for spectrum access opportunities of the corresponding group. Thanks to our group-based session-by-session cooperating strategy, our NLC approach is able to address all those challenges in the LLC approach. To articulate our NLC approach, we further develop an NLC scheme under a cognitive capacity harvesting network (CCHN) architecture. We formulate the cooperative mechanism design as a cross-layer optimization problem with constraints on primary session selection, flow routing and link scheduling. To search for solutions to the optimization problem, we propose an augmented scheduling index ordering based (SIO-based) algorithm to identify maximal independent sets. Through extensive simulations, we demonstrate the effectiveness of the proposed NLC approach and the superiority of the augmented SIO-based algorithm over the traditional method.

cs.IT↗

arXiv2017

$\Z_2^n$-graded quasialgebras and the Hurwitz problem on compositions of quadratic forms

We introduce a series of $\Z_2^n$-graded quasialgebras $\bbP_n(m)$ which generalizes Clifford algebras, higher octonions, and higher Cayley algebras. The constructed series of algebras and their minor perturbations are applied to contribute explicit solutions to the Hurwitz problem on compositions of quadratic forms. In particular, we provide explicit expressions of the well-known Hurwitz-Radon square identities in a uniform way, recover the Yuzvinsky-Lam-Smith formulas, confirm the third family of admissible triples proposed by Yuzvinsky in 1984, improve the two infinite families of solutions obtained recently by Lenzhen, Morier-Genoud and Ovsienko, and construct several new infinite families of solutions.

math.QA↗

arXiv2017

Magnetic tunneling induced Weyl node annihilation in TaP

Weyl nodes are topological objects in three-dimensional metals. Their topological property can be revealed by studying the high-field transport properties of a Weyl semimetal. While the energy of the lowest Landau band (LLB) of a conventional Fermi pocket always increases with magnetic field due to the zero point energy, the LLB of Weyl cones remains at zero energy unless a strong magnetic field couples the Weyl fermions of opposite chirality. In the Weyl semimetal TaP, we achieve such a magnetic coupling between the electron-like Fermi pockets arising from the W1 Weyl fermions. As a result, their LLBs move above chemical potential, leading to a sharp sign reversal in the Hall resistivity at a specific magnetic field corresponding to the W1 Weyl node separation. By contrast, despite having almost identical carrier density, the annihilation is unobserved for the hole-like pockets because the W2 Weyl nodes are much further separated. These key findings, corroborated by other systematic analyses, reveal the nontrivial topology of Weyl fermions in high-field measurements.

cond-mat.str-el↗

arXiv2017

Signature of chiral fermion instability in the Weyl semimetal TaAs above the quantum limit

We report the electrical transport properties for Weyl semimetal TaAs in an intense magnetic field. Series of anomalies occur in the longitudinal magnetoresistance and Hall signals at ultra-low temperatures when the Weyl electrons are confined into the lowest Landau level. These strongly temperature-dependent anomalies are ascribed to the electron-hole pairing instability. Our measurements show that the Weyl semimetal TaAs in the ultraquantum regime provides a good platform for studying electron-electron interaction in topological nontrivial semimetals.

cond-mat.mes-hall↗

arXiv2017

On $H_σ$-permutably embedded and $H_σ$-subnormaly embedded subgroups of finite groups

Let $G$ be a finite group. Let $σ=\{σ_{i} | i\in I\}$ be a partition of the set of all primes $\Bbb{P}$ and $n$ an integer. We write $σ(n) =\{σ_{i} |σ_{i}\cap π(n)\ne \emptyset \}$, $σ(G) =σ(|G|)$. A set $ {\cal H}$ of subgroups of $G$ is said to be a complete Hall $σ$-set of $G$ if every member of ${\cal H}\setminus \{1\}$ is a Hall $σ_{i}$-subgroup of $G$ for some $σ_{i}$ and ${\cal H}$ contains exact one Hall $σ_{i}$-subgroup of $G$ for every $σ_{i}\in σ(G)$. A subgroup $A$ of $G$ is called: (i) a $σ$-Hall subgroup of $G$ if $σ(|A|) \cap σ(|G:A|)=\emptyset$; (ii) $σ$-permutable in $G$ if $G$ possesses a complete Hall $σ$-set ${\cal H}$ such that $AH^{x}=H^{x}A$ for all $H\in {\cal H}$ and all $x\in G$. We say that a subgroup $A$ of $G$ is $H_σ$-permutably embedded in $G$ if $A$ is a $σ$-Hall subgroup of some $σ$-permutable subgroup of $G$. We study finite groups $G$ having an $H_σ$-permutably embedded subgroup of order $|A|$ for each subgroup $A$ of $G$. Some known results are generalized.

math.GR↗

arXiv2017

A Controlled Particle Filter for Global Optimization

A particle filter is introduced to numerically approximate a solution of the global optimization problem. The theoretical significance of this work comes from its variational aspects: (i) the proposed particle filter is a controlled interacting particle system where the control input represents the solution of a mean-field type optimal control problem; and (ii) the associated density transport is shown to be a gradient flow (steepest descent) for the optimal value function, with respect to the Kullback--Leibler divergence. The optimal control construction of the particle filter is a significant departure from the classical importance sampling-resampling based approaches. There are several practical advantages: (i) resampling, reproduction, death or birth of particles is avoided; (ii) simulation variance can potentially be reduced by applying feedback control principles; and (iii) the parametric approximation naturally arises as a special case. The latter also suggests systematic approaches for numerical approximation of the optimal control law. The theoretical results are illustrated with numerical examples.

math.OC↗