arXiv subjects

Qing Zhao

Publications and source records attributed to Qing Zhao.

At least 145 records · Page 8Linked to original sources

arXiv2020

Quantum battery of interacting spins with environmental noise

A quantum battery is a temporary energy-storage system. We constructed the quantum battery model of an N-spin chain with nearest-neighbor hopping interaction and investigated the charging process of the quantum battery. We obtained the maximum energy in the quantum battery charged by a coherent cavity driving field or a thermal heat bath. We confirmed that for a finite-length spin chain, thermal charging results in a nonzero ergotropy, contradicting a previous result: that an incoherent heat source cannot charge a single-spin quantum battery. The nearest-neighbor hopping interaction induces energy band splitting, which enhances the energy storage and the ergotropy of the quantum battery. We found a critical point in the energy and ergotropy resulting from the ground-state quantum phase transition, after which the energy significantly enhance. Finally, we also found that disorder increased the energy of the quantum battery.

quant-ph↗

arXiv2020

Substrate-free THz focal plane metamaterial array with high absorption ratio

Microelectromechanical system (MEMS) focal plane array (FPA) with optical readout offers exciting opportunities for real-time terahertz (THz) imaging. However, conventional FPA suffers from a low THz absorption ratio, which further decreases the performance of THz imaging. Here, we present a simple and scalable approach for the realization of THz focal plane metamaterial array with a relatively high absorption ratio. The key idea is to combine the advantages of substrate-free structures with metamaterial. A 100 x100 THz FPA with a 150 x 150 μm pixel is designed, fabricated, and characterized. The dependence of the THz absorption ratio on the thickness of SiNx dielectric substrate film is investigated. The fabricated FPA exhibits a 90.6% resonant absorption at 1.36 THz, agreeing considerably with the theoretical simulation results. Our results imply that such a substrate-free THz focal plane metamaterial array enables the realization of THz imaging.

physics.app-ph↗

arXiv2020

Disagreement-based Active Learning in Online Settings

We study online active learning for classifying streaming instances within the framework of statistical learning theory. At each time, the learner either queries the label of the current instance or predicts the label based on past seen examples. The objective is to minimize the number of queries while constraining the number of prediction errors over a horizon of length $T$. We develop a disagreement-based online learning algorithm for a general hypothesis space and under the Tsybakov noise. We show that the proposed algorithm has a label complexity of $O(dT^{\frac{2-2α}{2-α}}\log^2 T)$ under a constraint of bounded regret in terms of classification errors, where $d$ is the VC dimension of the hypothesis space and $α$ is the Tsybakov noise parameter. We further establish a matching (up to a poly-logarithmic factor) lower bound, demonstrating the order optimality of the proposed algorithm. We address the tradeoff between label complexity and regret and show that the algorithm can be modified to operate at a different point on the tradeoff curve.

cs.LG↗

arXiv2020

Three-dimensional reconstruction of integrated implosion targets from simulated small-angle pinhole images

To indirectly evaluate the asymmetry of the radiation drive under limited measurement conditions in inertial confinement fusion research, we have proposed an integral method to approximate the three-dimensional self-radiation distribution of the compressed plasma core using only four pinhole images from a single laser entrance hole at a maximum projection angle of 10°. The simultaneous algebraic reconstruction technique (SART) that uses spatial constraints provided by the prior structural information and the central pinhole image is utilized in the simulation. The simulation results showed that the normalized mean square deviation between the original distribution and reconstruction results of the central radiation area of the simulated cavity was 0.4401, and the structural similarity of the cavity radiation distribution was 0.5566. Meanwhile, using more diagnostic holes could achieve better structural similarity and lower reconstruction error. In addition, the results indicated that our new proposed method could reconstruct the distribution of a compressed plasma core in a vacuum hohlraum with high accuracy.

physics.plasm-ph↗

arXiv2020

A class of two or three weights linear codes and their complete weight enumerators

In the past few years, linear codes with few weights and their weight analysis have been widely studied. In this paper, we further investigate a class of two-weight or three-weight linear codes from defining sets and determine their weight and complete weight enumerators by application of the theory of quadratic forms and some special Weil sums over finite fields. Some punctured codes of the discussed linear codes are optimal or almost optimal with respect to the Griesmer bound. This paper generalizes some results in \cite{ZhuXu2017,Jian2019}.

cs.IT↗

arXiv2020

Theory of exciton transport in molecular crystals strongly coupled to a cavity: A temperature-dependent variational approach

We present a semianalytical theory for exciton transport in organic molecular crystals interacting strongly with a single cavity mode. Based on the Holstein-Tavis-Cummings model and the Kubo formula, we derive an exciton mobility expression in the framework of a temperature-dependent variational canonical transformation, which can cover a wide range of exciton-vibration coupling, exciton-cavity coupling, and temperatures. A closed-form expression for the coherent part of the total mobility is obtained in the zeroth order of the exciton-vibration coupling, which demonstrates the significance of vibrationally dressed dark excitons in the determination of the transport mechanism. By performing numerical simulations on both the H- and J-aggregates, we find that the exciton-cavity coupling has significant effects on the total mobility: 1) At low temperatures, there exists an optimal exciton-cavity coupling strength for the H-aggregate at which a maximal mobility is reached, while the mobility in the J-aggregate decreases monotonically with increasing exciton-cavity coupling; 2) At high temperatures, the mobility in both types of aggregates get enhanced by the cavity. We illustrate the above-mentioned low-temperature optimal mobility observed in the H-aggregate by using realistic parameters at room temperature.

cond-mat.mes-hall↗

arXiv2020

AstroCatR: a Mechanism and Tool for Efficient Time Series Reconstruction of Large-Scale Astronomical Catalogues

Time series data of celestial objects are commonly used to study valuable and unexpected objects such as extrasolar planets and supernova in time domain astronomy. Due to the rapid growth of data volume, traditional manual methods are becoming extremely hard and infeasible for continuously analyzing accumulated observation data. To meet such demands, we designed and implemented a special tool named AstroCatR that can efficiently and flexibly reconstruct time series data from large-scale astronomical catalogues. AstroCatR can load original catalogue data from Flexible Image Transport System (FITS) files or databases, match each item to determine which object it belongs to, and finally produce time series datasets. To support the high-performance parallel processing of large-scale datasets, AstroCatR uses the extract-transform-load (ETL) preprocessing module to create sky zone files and balance the workload. The matching module uses the overlapped indexing method and an in-memory reference table to improve accuracy and performance. The output of AstroCatR can be stored in CSV files or be transformed other into formats as needed. Simultaneously, the module-based software architecture ensures the flexibility and scalability of AstroCatR. We evaluated AstroCatR with actual observation data from The three Antarctic Survey Telescopes (AST3). The experiments demonstrate that AstroCatR can efficiently and flexibly reconstruct all time series data by setting relevant parameters and configuration files. Furthermore, the tool is approximately 3X faster than methods using relational database management systems at matching massive catalogues.

astro-ph.IM↗

arXiv2020

Evolution of clustering structure through the momentum distributions in $^{8-10}$Be isotopes

We investigate the evolution of clustering structure through the momentum distributions in the $^{8-10}$Be isotopes. The nucleon dynamics within the inter-cluster antisymmetrization are discussed via the momentum distribution of a Brink type $α$-$α$ wave function. For the state with a small $α$-$α$ distance, we observe a significant depression with a dip structure at zero-momentum and an enhanced tail at relatively higher momentum region. In addition, we find the "cluster structure" in the intrinsic frame of momentum space, which is complementary to its significant $α$-cluster dissolution in the coordinate space because of the strong antisymmetrization. For the physical $^{8-10}$Be isotopes, the Tohsaki-Horiuchi-Schuck-R{ö}pke (THSR) wave functions are adopted. The evolution from the dilute clustering state to the compact one is demonstrated by a successive depression at the zero-momentum of nucleon distribution for the two $α$-clusters within $^{8-10}$Be isotopes. For the compact $^{10}$Be nucleus, the momentum distribution of all nucleons shows significant depression at zero-momentum with a dip structure, which is found to be contributed by both the inter-cluster antisymmetrization and the $p$-orbit occupation of the valence neutrons. This study proposes a new window for the investigations of the $α$-clustering effects via the low-momentum components of nuclei, which is expected to be extended to the heavier nuclear clustering states.

nucl-th↗

arXiv2020

The photon vortex beam in rotating medium

In this paper we consider the photon vortex beam in the rotating medium, where the rotating velocity acts as an effective vector potential. Using the Riemann-Silberstein vector, we construct the photon wave function. Using the Maxwell equations and the first-order Minkowski constitutive relations we get the dynamic equations of photon in moving medium. For the stationary states, the dynamic equations can be written as a Dirac-like equation. We obtain the approximate photon vortex beam solutions by the given the medium's different velocity distribution and find the diffracting and nondiffracting Laguerre-Gaussian beam solutions in the rotating medium. For the diffracting Laguerre-Gaussian beams, we acquire new terms arising from the rotation that can change the Gouy phase, and then accordingly infer the rotation behavior of the photon interference pattern. Furthermore, in our theory we obtain the Landau levels structure of transverse photon energy in the nondiffracting Laguerre-Gaussian beam solutions.

physics.optics↗

arXiv2020

Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization

A framework based on iterative coordinate minimization (CM) is developed for stochastic convex optimization. Given that exact coordinate minimization is impossible due to the unknown stochastic nature of the objective function, the crux of the proposed optimization algorithm is an optimal control of the minimization precision in each iteration. We establish the optimal precision control and the resulting order-optimal regret performance for strongly convex and separably nonsmooth functions. An interesting finding is that the optimal progression of precision across iterations is independent of the low-dimensional CM routine employed, suggesting a general framework for extending low-dimensional optimization routines to high-dimensional problems. The proposed algorithm is amenable to online implementation and inherits the scalability and parallelizability properties of CM for large-scale optimization. Requiring only a sublinear order of message exchanges, it also lends itself well to distributed computing as compared with the alternative approach of coordinate gradient descent.

stat.ML↗

arXiv2020

DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation

Most SLAM algorithms are based on the assumption that the scene is static. However, in practice, most scenes are dynamic which usually contains moving objects, these methods are not suitable. In this paper, we introduce DymSLAM, a dynamic stereo visual SLAM system being capable of reconstructing a 4D (3D + time) dynamic scene with rigid moving objects. The only input of DymSLAM is stereo video, and its output includes a dense map of the static environment, 3D model of the moving objects and the trajectories of the camera and the moving objects. We at first detect and match the interesting points between successive frames by using traditional SLAM methods. Then the interesting points belonging to different motion models (including ego-motion and motion models of rigid moving objects) are segmented by a multi-model fitting approach. Based on the interesting points belonging to the ego-motion, we are able to estimate the trajectory of the camera and reconstruct the static background. The interesting points belonging to the motion models of rigid moving objects are then used to estimate their relative motion models to the camera and reconstruct the 3D models of the objects. We then transform the relative motion to the trajectories of the moving objects in the global reference frame. Finally, we then fuse the 3D models of the moving objects into the 3D map of the environment by considering their motion trajectories to obtain a 4D (3D+time) sequence. DymSLAM obtains information about the dynamic objects instead of ignoring them and is suitable for unknown rigid objects. Hence, the proposed system allows the robot to be employed for high-level tasks, such as obstacle avoidance for dynamic objects. We conducted experiments in a real-world environment where both the camera and the objects were moving in a wide range.

cs.CV↗

arXiv2020

Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization

Online minimization of an unknown convex function over the interval $[0,1]$ is considered under first-order stochastic bandit feedback, which returns a random realization of the gradient of the function at each query point. Without knowing the distribution of the random gradients, a learning algorithm sequentially chooses query points with the objective of minimizing regret defined as the expected cumulative loss of the function values at the query points in excess to the minimum value of the function. An approach based on devising a biased random walk on an infinite-depth binary tree constructed through successive partitioning of the domain of the function is developed. Each move of the random walk is guided by a sequential test based on confidence bounds on the empirical mean constructed using the law of the iterated logarithm. With no tuning parameters, this learning algorithm is robust to heavy-tailed noise with infinite variance and adaptive to unknown function characteristics (specifically, convex, strongly convex, and nonsmooth). It achieves the corresponding optimal regret orders (up to a $\sqrt{\log T}$ or a $\log\log T$ factor) in each class of functions and offers better or matching regret orders than the classical stochastic gradient descent approach which requires the knowledge of the function characteristics for tuning the sequence of step-sizes.

stat.ML↗

arXiv2020

Distributed No-Regret Learning in Multi-Agent Systems

In this tutorial article, we give an overview of new challenges and representative results on distributed no-regret learning in multi-agent systems modeled as repeated unknown games. Four emerging game characteristics---dynamicity, incomplete and imperfect feedback, bounded rationality, and heterogeneity---that challenge canonical game models are explored. For each of the four characteristics, we illuminate its implications and ramifications in game modeling, notions of regret, feasible game outcomes, and the design and analysis of distributed learning algorithms.

cs.GT↗

arXiv2019

Phase retrieval without prior knowledge via single-shot Fraunhofer diffraction pattern of complex object

Fraunhofer diffraction is a well-known phenomenon achieved with most wavelength even without lens. A single-shot intensity measurement of diffraction is generally considered inadequate to reconstruct the original light field, because the lost phase part is indispensable for reverse transformation. Phase retrieval is usually conducted in two means: priori knowledge or multiple different measurements. However, priori knowledge works for certain type of object while multiple measurements are difficult for short wavelength. Here, by introducing non-orthogonal measurement via high density sampling scheme, we demonstrate that one single-shot Fraunhofer diffraction pattern of complex object is sufficient for phase retrieval. Both simulation and experimental results have demonstrated the feasibility of our scheme. Reconstruction of complex object reveals depth information or refraction index; and single-shot measurement can be achieved under most scenario. Their combination will broaden the application field of coherent diffraction imaging.

eess.IV↗

arXiv2019

Searching for Anomalies over Composite Hypotheses

The problem of detecting anomalies in multiple processes is considered. We consider a composite hypothesis case, in which the measurements drawn when observing a process follow a common distribution with an unknown parameter (vector), whose value lies in normal or abnormal parameter spaces, depending on its state. The objective is a sequential search strategy that minimizes the expected detection time subject to an error probability constraint. We develop a deterministic search algorithm with the following desired properties. First, when no additional side information on the process states is known, the proposed algorithm is asymptotically optimal in terms of minimizing the detection delay as the error probability approaches zero. Second, when the parameter value under the null hypothesis is known and equal for all normal processes, the proposed algorithm is asymptotically optimal as well, with better detection time determined by the true null state. Third, when the parameter value under the null hypothesis is unknown, but is known to be equal for all normal processes, the proposed algorithm is consistent in terms of achieving error probability that decays to zero with the detection delay. Finally, an explicit upper bound on the error probability under the proposed algorithm is established for the finite sample regime. Extensive experiments on synthetic dataset and DARPA intrusion detection dataset are conducted, demonstrating strong performance of the proposed algorithm over existing methods.

cs.IT↗

arXiv2019

Improvement on corrosion resistance and biocompability of ZK60 magnesium alloy by carboxyl ion implantation

Magnesium alloys have been considered to be potential biocompatible metallic materials. Further improvement on the anti-corrosion is expected to make this type of materials more suitable for biomedical applications in the fields of orthopedics, cardiovascular surgery and others. In this paper, we introduce a method of carboxyl ion (COOH+) implantation to reduce the degradation of ZK60 Mg alloy and improve its functionality in physiological environment. X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) experiments show the formation of a smooth layer containing carbaxylic group, carbonate, metal oxides and hydroxides on the ion implanted alloy surface. Corrosion experiments and in vitro cytotoxicity tests demonstrate that the ion implantation treatment can both reduce the corrosion rate and improve the biocompatibility of the alloy. The promising results indicate that organic functional group ion implantation may be a practical method of improving the biological and corrosion properties of magnesium alloys.

physics.med-ph↗

arXiv2019

Improvement in corrosion resistance and biocompatibility of AZ31 magnesium alloy by NH+2 ions

Magnesium alloys have been considered to be favorable biodegradable metallic materials used in orthopedic and cardiovascular applications. We introduce NH+2 to the AZ31 Mg alloy surface by ion implantation at the energy of 50 KeV with doses ranging from 1e16 ions/cm2 to 1e17 ions/cm2 to improve its corrosion resistance and biocompatibility. Surface morphology, mechanical properties, corrosion behavior and biocompatibility are studied in the experiments. The analysis confirms that the modified surface with smoothness and hydrophobicity significantly improves the corrosion resistance and biocompatibility while maintaining the mechanical property of the alloy.

physics.app-ph↗

arXiv2019

Stereo-based Multi-motion Visual Odometry for Mobile Robots

With the development of computer vision, visual odometry is adopted by more and more mobile robots. However, we found that not only its own pose, but the poses of other moving objects are also crucial for the decision of the robot. In addition, the visual odometry will be greatly disturbed when a significant moving object appears. In this letter, a stereo-based multi-motion visual odometry method is proposed to acquire the poses of the robot and other moving objects. In order to obtain the poses simultaneously, a continuous motion segmentation module and a coordinate conversion module are applied to the traditional visual odometry pipeline. As a result, poses of all moving objects can be acquired and transformed into the ground coordinate system. The experimental results show that the proposed multi-motion visual odometry can effectively eliminate the influence of moving objects on the visual odometry, as well as achieve 10 cm in position and 3° in orientation RMSE (Root Mean Square Error) of each moving object.

cs.CV↗