Distributed Control for Multiagent Consensus Motions with Nonuniform Time Delays

This paper solves control problems of agents achieving consensus motions in presence of nonuniform time delays by obtaining the maximal tolerable delay value. Two types of consensus motions are considered: the rectilinear motion and the rotational motion. Unlike former results, this paper has remarkably reduced conservativeness of the consensus conditions provided in such form: for each system, if all the nonuniform time delays are bounded by the maximal tolerable delay value which is referred to as “delay margin,” the system will achieve consensus motion; otherwise, if all the delays exceed the delay margin, the system will be unstable. When discussing the system which is intended to achieve rotational consensus motion, an expanded system whose state variables are real numbers (those of the original system are complex numbers) is introduced, and corresponding consensus condition is given also in the form of delay margin. Numerical examples are provided to illustrate the results

Subnatural-Linewidth Polarization-Entangled Photon Pairs with Controllable Temporal Length

We demonstrate an efficient experimental scheme for producing polarization-entangled photon pairs from spontaneous four-wave mixing (SFWM) in a laser-cooled $^{85}$Rb atomic ensemble, with a bandwidth (as low as 0.8 MHz) much narrower than the rubidium atomic natural linewidth. By stabilizing the relative phase between the two SFWM paths in a Mach-Zehnder interferometer configuration, we are able to produce all four Bell states. These subnatural-linewidth photon pairs with polarization entanglement are ideal quantum information carriers for connecting remote atomic quantum nodes via efficient light-matter interaction in a photon-atom quantum network.Comment: Title changed, published version, 5 pages + 3 pages Supplemental Materia

On the Temporal-spatial Analysis of Estimating Urban Traffic Patterns Via GPS Trace Data of Car-hailing Vehicles

Car-hailing services have become a prominent data source for urban traffic studies. Extracting useful information from car-hailing trace data is essential for effective traffic management, while discrepancies between car-hailing vehicles and urban traffic should be considered. This paper proposes a generic framework for estimating and analyzing urban traffic patterns using car-hailing trace data. The framework consists of three layers: the data layer, the interactive software layer, and the processing method layer. By pre-processing car-hailing GPS trace data with operations such as data cutting, map matching, and trace correction, the framework generates tensor matrices that estimate traffic patterns for car-hailing vehicle flow and average road speed. An analysis block based on these matrices examines the relationships and differences between car-hailing vehicles and urban traffic patterns, which have been overlooked in previous research. Experimental results demonstrate the effectiveness of the proposed framework in examining temporal-spatial patterns of car-hailing vehicles and urban traffic. For temporal analysis, urban road traffic displays a bimodal characteristic while car-hailing flow exhibits a 'multi-peak' pattern, fluctuating significantly during holidays and thus generating a hierarchical structure. For spatial analysis, the heat maps generated from the matrices exhibit certain discrepancies, but the spatial distribution of hotspots and vehicle aggregation areas remains similar

Consensus of Fractional-Order Multiagent Systems with Nonuniform Time Delays

Due to the complex external environment, many multiagent systems cannot be precisely described or even cannot be described by an integer-order dynamical model and can only be described by a fractional-order dynamical model. In this paper, consensus problems are investigated for two types of fractional-order multiagent systems (FOMASs) with nonuniform time delays: FOMAS with symmetric time delays and undirected topology and FOMAS with asymmetric time delays and directed topology. Employing the Laplace transform and the frequency-domain theory, two delay margins are obtained to guarantee the consensus for the two types of FOMAS, respectively. These results are also suitable for the integer-order dynamical model. Finally, simulation results are provided to illustrate the effectiveness of our theoretical results

Quantum information processing using Josephson junctions coupled through cavities

Josephson junctions have been shown to be a promising solid-state system for implementation of quantum computation. The significant two-qubit gates are generally realized by the capacitive coupling between the nearest neighbour qubits. We propose an effective Hamiltonian to describe charge qubits coupled through the cavity. We find that nontrivial two-qubit gates may be achieved by this coupling. The ability to interconvert localized charge qubits and flying qubits in the proposed scheme implies that quantum network can be constructed using this large scalable solid-state system.Comment: 5 pages, to appear in Phys Rev A; typos corrected, solutions in last eqs. correcte

Preoperative computed tomography-based tumoral radiomic features prediction for overall survival in resectable non-small cell lung cancer

ObjectivesThe purpose of this study was to evaluate whether preoperative radiomics features could meliorate risk stratification for the overall survival (OS) of non-small cell lung cancer (NSCLC) patients.MethodsAfter rigorous screening, the 208 NSCLC patients without any pre-operative adjuvant therapy were eventually enrolled. We segmented the 3D volume of interest (VOI) based on malignant lesion of computed tomography (CT) imaging and extracted 1542 radiomics features. Interclass correlation coefficients (ICC) and LASSO Cox regression analysis were utilized to perform feature selection and radiomics model building. In the model evaluation phase, we carried out stratified analysis, receiver operating characteristic (ROC) curve, concordance index (C-index), and decision curve analysis (DCA). In addition, integrating the clinicopathological trait and radiomics score, we developed a nomogram to predict the OS at 1 year, 2 years, and 3 years, respectively.ResultsSix radiomics features, including gradient_glcm_InverseVariance, logarithm_firstorder_Median, logarithm_firstorder_RobustMeanAbsoluteDeviation, square_gldm_LargeDependenceEmphasis, wavelet_HLL_firstorder_Kurtosis, and wavelet_LLL_firstorder_Maximum, were selected to construct the radiomics signature, whose areas under the curve (AUCs) for 3-year prediction reached 0.857 in the training set (n=146) and 0.871 in the testing set (n=62). The results of multivariate analysis revealed that the radiomics score, radiological sign, and N stage were independent prognostic factors in NSCLC. Moreover, compared with clinical factors and the separate radiomics model, the established nomogram exhibited a better performance in predicting 3-year OS.ConclusionsOur radiomics model may provide a promising non-invasive approach for preoperative risk stratification and personalized postoperative surveillance for resectable NSCLC patients

Distributed Control of Networked Unmanned Aerial Vehicles for Valley Area Coverage

The paper provides a novel cooperative motion scheme for networked Unmanned Aerial Vehicles (UAVs) to fully sweep-cover a priori unknown elongated areas with curved borders, which are termed “valley areas.” The UAVs’ motion is confined between the borders. Different from former research on straight-corridor-sweep-coverage, in each valley area, the width of different portions varies dramatically: the UAVs need to line up across the valley area to achieve full coverage of the widest portions while they can only pass through the narrowest parts one by one in a queue. The UAVs are provided with barrier detection and inter-UAV communication. According to the scheme, a distributed control law has been offered for discrete-time multi-UAV systems, guaranteeing crash avoidance and full coverage while considering the constrained mobility of the UAVs. Regular and extreme simulations are carried out to verify the efficacy and stability of the proposed algorithm. Solutions to U-shaped valley coverage and the case of insufficient UAVs available are discussed with validation simulations. Comparison simulations are conducted with respect to a line-sweep-coverage algorithm developed by a closely related work, and differences in performance are revealed subsequently. Conclusions are drawn with possible directions of future research