arXiv subjects

Zheng Chen

Publications and source records attributed to Zheng Chen.

At least 235 records · Page 13Linked to original sources

arXiv2021

RIS-aided D2D Communication Design for URLLC Packet Delivery

In this paper, we consider a smart factory scenario where a set of actuators receive critical control signals from an access point (AP) with reliability and low latency requirements. We investigate jointly active beamforming at the AP and passive phase shifting at the reconfigurable intelligent surface (RIS) for successfully delivering the control signals from the AP to the actuators within a required time duration. The transmission follows a two-stage design. In the first stage, each actuator can both receive the direct signal from AP and the reflected signal from the RIS. In the second stage, the actuators with successful reception in the first stage, relay the message through the D2D network to the actuators with failed receptions. We formulate a non-convex optimization problem where we first obtain an equivalent but more tractable form by addressing the problem with discrete indicator functions. Then, Frobenius inner product based equality is applied for decoupling the optimization variables. Further, we adopt a penalty-based approach to resolve the rank-one constraints. Finally, we deal with the $\ell_0$-norm by $\ell_1$-norm approximation and add an extra term $\ell_1-\ell_2$ for sparsity. Numerical results reveal that the proposed two-stage RIS-aided D2D communication protocol is effective for enabling reliable communication with latency requirements.

cs.IT↗

arXiv2021

Quantum transport evidence of topological band structures of kagome superconductor CsV3Sb5

We report the transport properties of kagome superconductor CsV$_{3}$Sb$_{5}$ single crystals at magnetic field up to 32 T. The Shubnikov de Haas (SdH) oscillations emerge at low temperature and four frequencies of $F_α=$ 27 T, $F_β=$ 73 T, $F_ε=$ 727 T, and $F_η=$ 786 T with relatively small cyclotron masses are observed. For $F_β$ and $F_ε$, the Berry phases are close to $π$, providing a clear evidence of nontrivial topological band structures of CsV$_{3}$Sb$_{5}$. Furthermore, the consistence between theoretical calculations and experimental results implies that these frequencies can be assigned to the Fermi surfaces locating near the boundary of Brillouin zone and confirms that the structure with an inverse Star of David distortion could be the most stable structure at charge density wave state. These results will shed light on the nature of correlated topological physics in kagome material CsV$_{3}$Sb$_{5}$.

cond-mat.supr-con↗

arXiv2021

Multi-Objective Autonomous Exploration on Real-Time Continuous Occupancy Maps

Autonomous exploration in unknown environments using mobile robots is the pillar of many robotic applications. Existing exploration frameworks either select the nearest geometric frontier or the nearest information-theoretic frontier. However, just because a frontier itself is informative does not necessarily mean that the robot will be in an informative area after reaching that frontier. To fill this gap, we propose to use a multi-objective variant of Monte-Carlo tree search that provides a non-myopic Pareto optimal action sequence leading the robot to a frontier with the greatest extent of unknown area uncovering. We also adopted Bayesian Hilbert Map (BHM) for continuous occupancy mapping and made it more applicable to real-time tasks.

cs.RO↗

arXiv2021

Efficient Map Prediction via Low-Rank Matrix Completion

In many autonomous mapping tasks, the maps cannot be accurately constructed due to various reasons such as sparse, noisy, and partial sensor measurements. We propose a novel map prediction method built upon the recent success of Low-Rank Matrix Completion. The proposed map prediction is able to achieve both map interpolation and extrapolation on raw poor-quality maps with missing or noisy observations. We validate with extensive simulated experiments that the approach can achieve real-time computation for large maps, and the performance is superior to the state-of-the-art map prediction approach - Bayesian Hilbert Mapping in terms of mapping accuracy and computation time. Then we demonstrate that with the proposed real-time map prediction framework, the coverage convergence rate (per action step) for a set of representative coverage planning methods commonly used for environmental modeling and monitoring tasks can be significantly improved.

cs.RO↗

arXiv2021

NSS-VAEs: Generative Scene Decomposition for Visual Navigable Space Construction

Detecting navigable space is the first and also a critical step for successful robot navigation. In this work, we treat the visual navigable space segmentation as a scene decomposition problem and propose a new network, NSS-VAEs (Navigable Space Segmentation Variational AutoEncoders), a representation-learning-based framework to enable robots to learn the navigable space segmentation in an unsupervised manner. Different from prevalent segmentation techniques which heavily rely on supervised learning strategies and typically demand immense pixel-level annotated images, the proposed framework leverages a generative model - Variational Auto-Encoder (VAE) - to learn a probabilistic polyline representation that compactly outlines the desired navigable space boundary. Uniquely, our method also assesses the prediction uncertainty related to the unstructuredness of the scenes, which is important for robot navigation in unstructured environments. Through extensive experiments, we have validated that our proposed method can achieve remarkably high accuracy (>90%) even without a single label. We also show that the prediction of NSS-VAEs can be further improved using few labels with results significantly outperforming the SOTA fully supervised-learning-based method.

cs.RO↗

arXiv2021

Combined tests based on restricted mean time lost for competing risks data

Competing risks data are common in medical studies, and the sub-distribution hazard (SDH) ratio is considered an appropriate measure. However, because the limitations of hazard itself are not easy to interpret clinically and because the SDH ratio is valid only under the proportional SDH assumption, this article introduced an alternative index under competing risks, named restricted mean time lost (RMTL). Several test procedures were also constructed based on RMTL. First, we introduced the definition and estimation of RMTL based on Aalen-Johansen cumulative incidence functions. Then, we considered several combined tests based on the SDH and the RMTL difference (RMTLd). The statistical properties of the methods are evaluated using simulations and are applied to two examples. The type I errors of combined tests are close to the nominal level. All combined tests show acceptable power in all situations. In conclusion, RMTL can meaningfully summarize treatment effects for clinical decision making, and three combined tests have robust power under various conditions, which can be considered for statistical inference in real data analysis.

stat.AP↗

arXiv2021

Elongation of Curvature-Bounded Path

The paper is concerned with elongating the shortest curvature-bounded path between two oriented points to an expected length. The elongation of curvature-bounded paths to an expected length is fundamentally important to plan missions for nonholonomic-constrained vehicles in many practical applications, such as coordinating multiple nonholonomic-constrained vehicles to reach a destination simultaneously or performing a mission with a strict time window. In the paper, the explicit conditions for the existence of curvature-bounded paths joining two oriented points with an expected length are established by applying the properties of the reachability set of curvature-bounded paths. These existence conditions are numerically verifiable, allowing readily checking the existence of curvature-bounded paths between two prescribed oriented points with a desired length. In addition, once the existence conditions are met, elongation strategies are provided in the paper to get curvature-bounded paths with expected lengths. Finally, some examples of minimum-time path planning for multiple fixed-wing aerial vehicles to cooperatively achieve a triangle-shaped flight formation are presented, illustrating and verifying the developments of the paper.

math.OC↗

arXiv2021

Unusual Magnetic Properties in Layered Magnetic Topological Insulator EuSn2As2

EuSn2As2 with layered rhombohedral crystal structure is proposed to be a candidate of intrinsic antiferromagnetic (AFM) topological insulator. Here, we have investigated systematic magnetoresistance (MR) and magnetization measurements on the high quality EuSn2As2 single crystal with the magnetic field both parallel and perpendicular to (00l) plane. Both the kink of magnetic susceptibility and longitudinal resistivity reveal that EuSn2An2 undergoes an AFM transition at TN = 21 K. At T = 2 K, the magnetization exhibits two successive plateaus of ~ 5.6 μB/Eu and ~ 6.6 μB/Eu at the corresponding critical magnetic fields. Combined with the negative longitudinal MR and abnormal Hall resistance, we demonstrate that EuSn2An2 undergoes complicated magnetic transitions from an AFM state to a canted ferromagnetic (FM) state at Hc and then to a polarized FM state at Hs as the magnetic field increase.

cond-mat.mtrl-sci↗

arXiv2021

Scalable Solvent-Based Fabrication of Thermo-Responsive Polymer Nanocomposites for Battery Safety Regulation

Improving lithium-ion batteries (LIBs) safety remains in a challenging task when compared with the tremendous progress made in their performance in recent years. Embedding thermo-responsive polymer switching materials (TRPS) into LIB cells has been proved to be a promising strategy to provide consistent thermal abuse protections at coin-cell level. However, it is unrealistic to achieve large-scale applications without further demonstration in high-capacity pouch cells. Here, we employed tungsten carbide (WC) as a novel conductive filler, and successfully overcame the intrinsic processing difficulty of polyethylene (PE) matrix in a scalable solvent-based method to obtain ultra-thin, uniform, highly conductive TRPS. Moreover, by integrating TRPS directly into LIB electrodes, no extra fabrication facilities or processes are required for making the cells. As a result, multi-layer pouch cells with consistent electrochemical performance and thermal abuse protection function were fabricated using industry relevant manufacturing techniques, which brings TRPS one step further to the real application scenarios.

physics.app-ph↗

arXiv2021

Device Scheduling and Update Aggregation Policies for Asynchronous Federated Learning

Federated Learning (FL) is a newly emerged decentralized machine learning (ML) framework that combines on-device local training with server-based model synchronization to train a centralized ML model over distributed nodes. In this paper, we propose an asynchronous FL framework with periodic aggregation to eliminate the straggler issue in FL systems. For the proposed model, we investigate several device scheduling and update aggregation policies and compare their performances when the devices have heterogeneous computation capabilities and training data distributions. From the simulation results, we conclude that the scheduling and aggregation design for asynchronous FL can be rather different from the synchronous case. For example, a norm-based significance-aware scheduling policy might not be efficient in an asynchronous FL setting, and an appropriate "age-aware" weighting design for the model aggregation can greatly improve the learning performance of such systems.

cs.LG↗

arXiv2021

Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards

In the process of clinical diagnosis and treatment, the restricted mean survival time (RMST), which reflects the life expectancy of patients up to a specified time, can be used as an appropriate outcome measure. However, the RMST only calculates the mean survival time of patients within a period of time after the start of follow-up and may not accurately portray the change in a patient's life expectancy over time. The life expectancy can be adjusted for the time the patient has already survived and defined as the conditional restricted mean survival time (cRMST). A dynamic RMST model based on the cRMST can be established by incorporating time-dependent covariates and covariates with time-varying effects. We analysed data from a study of primary biliary cirrhosis (PBC) to illustrate the use of the dynamic RMST model. The predictive performance was evaluated using the C-index and the prediction error. The proposed dynamic RMST model, which can explore the dynamic effects of prognostic factors on survival time, has better predictive performance than the RMST model. Three PBC patient examples were used to illustrate how the predicted cRMST changed at different prediction times during follow-up. The use of the dynamic RMST model based on the cRMST allows for optimization of evidence-based decision-making by updating personalized dynamic life expectancy for patients.

stat.AP↗

arXiv2021

Throughput and Age of Information in a Cellular-based IoT Network

This paper studies the interplay between device-to-device (D2D) communications and real-time monitoring systems in a cellular-based Internet of Things (IoT) network. In particular, besides the possibility that the IoT devices communicate directly with each other in a D2D fashion, we consider that they frequently send time-sensitive information/status updates (about some underlying physical processes) to their nearest base stations (BSs). By modeling the locations of the IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another independent PPP, we characterize the performance of the D2D links and status update links in terms of network throughput and Age-of-Information (AoI), respectively. We consider a maximum power constraint and distance-dependent fractional power control for all status update transmissions. Hence, the locations of the IoT devices allowed to send status updates are constrained to lie within the Johnson-Mehl cells. For this set-up, the average network throughput is obtained by deriving the mean success probability of the D2D links, whereas the spatial moments of the temporal mean AoI are obtained by deriving the moments of the temporal means of both success and scheduling probabilities of the status update links.

cs.IT↗

arXiv2021

Pressure-induced Reemergence of Superconductivity in Topological Kagome Metal CsV3Sb5

Quasi-two-dimensional kagome metals AV3Sb5 (A = K, Rb, and Cs) have attracted much recent interest due to exotic quantum phenomena such as unconventional superconductivity, topological charge order and giant anomalous Hall effect. Here we report pressure-induced reemergent superconductivity in CsV3Sb5 by electrical transport measurements under high pressures up to 47.9 GPa. We show that the superconducting critical temperature Tc is first enhanced by pressure and reaches its first maximum ~ 8.9 K at 0.8 GPa, then the Tc is suppressed by pressure and cannot be detected above 7.5 GPa, forming a dome-shaped superconducting phase diagram. Remarkably, upon further compression above 16.5 GPa, a new superconducting state arises, of which Tc is enhanced by pressure to a second maximum ~ 5.0 K and the reemergent superconductivity keeps robust up to 47.9 GPa. Combined with high-pressure synchrotron x-ray diffraction measurements that demonstrate the stability of the pristine hexagonal phase up to 43.1 GPa, we suggest that the reemergence of superconductivity in the V-based superconductor could be attributed to a pressure-induced Lifshitz transition.

cond-mat.supr-con↗

arXiv2021

SPSA-Based Successive Beamforming for Mobile Satellite Receivers with Phased Arrays

Efficient and low-complexity beamforming design is an important element of satellite communication systems with mobile receivers equipped with phased arrays. In this work, we apply the simultaneous perturbation stochastic approximation (SPSA) method with successive sub-array selection for finding the optimal antenna weights that maximize the received signal power at a uniform plane array (UPA). The proposed algorithms are based on iterative gradient approximation by injecting some carefully designed perturbations on the parameters to be estimated. Additionally, the successive sub-array selection technique enhances the performance of SPSA-based algorithms and makes them less sensitive to the initial beam direction. Simulation results show that our proposed algorithms can achieve efficient and reliable performance even when the initial beam direction is not well aligned with the satellite direction.

eess.SP↗

arXiv2021

A liquid nitrogen-cooled Ca^+ optical clock with systematic uncertainty of 3*10^-18

Here we present a liquid nitrogen-cooled Ca^+ optical clock with an overall systematic uncertainty of 3*10^-18. In contrast with the room-temperature Ca^+ optical clock that we have reported previously, the temperature of the blackbody radiation (BBR) shield in vacuum has been reduced to 82(5) K using liquid nitrogen. An ion trap with a lower heating rate and improved cooling lasers were also introduced. This allows cooling the ion temperature to the Doppler cooling limit during the clock operation, and the systematic uncertainty due to the ion's secular (thermal) motion is reduced to < 1*10^-18. The uncertainty due to the probe laser light shift and the servo error are also reduced to < 1*10^-19 and 4*10^-19 with the hyper-Ramsey method and the higher-order servo algorithm, respectively. By comparing the output frequency of the cryogenic clock to that of a room-temperature clock, the differential BBR shift between the two was measured with a fractional statistical uncertainty of 7*10^-18. The differential BBR shift was used to calculate the static differential polarizability, and it was found in excellent agreement with our previous measurement with a different method. This work suggests that the BBR shift of optical clocks can be well suppressed in a liquid nitrogen environment. This is advantageous because conventional liquid-helium cryogenic systems for optical clocks are more expensive and complicated. Moreover, the proposed system can be used to suppress the BBR shift significantly in other types of optical clocks such as Yb^+, Sr^+, Yb, Sr, etc.

physics.atom-ph↗

arXiv2021

Carbon Free High Loading Silicon Anodes Enabled by Sulfide Solid Electrolytes for Robust All Solid-State Batteries

The development of silicon anodes to replace conventional graphite in efforts to increase energy densities of lithium-ion batteries has been largely impeded by poor interfacial stability against liquid electrolytes. Here, stable operation of 99.9 weight% micro-Si (uSi) anode is enabled by utilizing the interface passivating properties of sulfide based solid-electrolytes. Bulk to surface characterization, as well as quantification of interfacial components showed that such an approach eliminates continuous interfacial growth and irreversible lithium losses. In uSi || layered-oxide full cells, high current densities at room temperature (5 mA cm 2), wide operating temperature (-20°C to 80°C) and high loadings (>11 mAh cm-2) were demonstrated for both charge and discharge operations. The promising battery performance can be attributed to both the desirable interfacial property between uSi and sulfide electrolytes, as well as the unique chemo-mechanical behavior of the Li-Si alloys.

cond-mat.mtrl-sci↗

arXiv2021

Optimizing Information Freshness in a Multiple Access Channel with Heterogeneous Devices

In this work, we study age-optimal scheduling with stability constraints in a multiple access channel with two heterogeneous source nodes transmitting to a common destination. The first node is connected to a power grid and it has randomly arriving data packets. Another energy harvesting (EH) sensor monitors a stochastic process and sends status updates to the destination. We formulate an optimization problem that aims at minimizing the average age of information (AoI) of the EH node subject to the queue stability condition of the grid-connected node. First, we consider a Probabilistic Random Access (PRA) policy where both nodes make independent transmission decisions based on some fixed probability distributions. We show that with this policy, the average AoI is equal to the average peak AoI, if the EH node only sends freshly generated samples. In addition, we derive the optimal solution in closed form, which reveals some interesting properties of the considered system. Furthermore, we consider a Drift-Plus-Penalty (DPP) policy and develop AoI-optimal and peak-AoI-optimal scheduling algorithms using the Lyapunov optimization theory. Simulation results show that the DPP policy outperforms the PRA policy in various scenarios, especially when the destination node has low multi-packet reception capabilities.

cs.IT↗

arXiv2021

Solving the linear transport equation by a deep neural network approach

In this paper, we study the linear transport model by adopting the deep learning method, in particular the deep neural network (DNN) approach. While the interest of using DNN to study partial differential equations is arising, here we adapt it to study kinetic models, in particular the linear transport model. Moreover, theoretical analysis on the convergence of the neural network and its approximated solution towards the analytic solution is shown. We demonstrate the accuracy and effectiveness of the proposed DNN method in the numerical experiments.

math.NA↗