Proximity-Induced Fully Ferromagnetic Order with Eightfold Magnetic Anisotropy in Heavy Transition Metal Oxide CaRuO3

Ferromagnetic materials with a strong spin-orbit coupling (SOC) have attracted much attention in recent years because of their exotic properties and potential applications in energy-efficient spintronics. However, such materials are scarce in nature. Here, a proximity-induced paramagnetic to ferromagnetic transition for the heavy transition metal oxide CaRuO₃ in (001)-(LaMnO₃/CaRuO₃) superlattices is reported. Anomalous Hall effect is observed in the temperature range up to 180 K. Maximal anomalous Hall conductivity and anomalous Hall angle are as large as ∼15 Ω⁻¹ cm⁻¹ and ∼0.93%, respectively, by one to two orders of magnitude larger than those of the typical 3d ferromagnetic oxides such as La_0.67Sr_0.33MnO₃. Density functional theory calculations indicate the existence of avoid band crossings in the electronic band structure of the ferromagnetic CRO layer, which enhances Berry curvature thus strong anomalous Hall effects. Further evidences from polarized neutron reflectometry show that the CaRuO₃ layers are in a fully ferromagnetic state (∼0.8 μ_B/Ru), in sharp contrast to the proximity-induced canted antiferromagnetic state in 5d oxides SrIrO₃ and CaIrO₃ (∼0.1 μ_B/Ir). More than that, the magnetic anisotropy of the (001)-(LaMnO₃/CaRuO₃) superlattices is eightfold symmetric, showing potential applications in the technology of multistate data storage.     

Stubborn state estimation for complex-valued neural networks with mixed time delays: the discrete time case

Neural Computing and Applications - In this paper, the state estimation problem is investigated for a class of discrete-time complex-valued neural networks (CVNNs) with mixed time delays. We...     

卫星USB测控副载波同步算法研究

吉林一号卫星测控采用USB测控体制,遥控接收采用FFT+DPLL1+DPLL2的架构,FFT主要实现对载波的粗捕,DPLL1在FFT的基础上实现对载波相位的精跟踪,DPLL2实现副载波的跟踪。对遥控副载波跟踪所用到的数字PLL技术进行了研究,首先给出了载波多普勒折算到副载波上的方法,然后对模拟PLL数字化进行了详细的论述,并设计了遥控副载波同步用的PLL2,对其稳定性、快捕带及快捕时间、捕获带和捕获时间、同步速率等进行了分析和仿真。结果表明,该方法具有捕获时间短、跟踪精度高、稳定性好等特点,易于数字化实现,已成功在吉林一号系列卫星中得到应用。     

Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks

International Journal of Computer Vision - Visual tracking of generic objects is one of the fundamental but challenging problems in computer vision. Here, we propose a novel fully convolutional...     

A modified teaching–learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling

In this paper, a modified teaching–learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based on the simple job-based representation, a novel decoding method named equivalent due date-based permutation schedule is proposed to transfer an individual to a feasible schedule. At each generation, a number of superior individuals are selected as the teachers by the Pareto-based ranking phase. To enhance the exploitation ability in the promising area, the insertion-based local search is embedded in the search framework as the training phase for the TLBO. Due to the characteristics of the permutation-based discrete optimisation, the linear order crossover operator and the swap operator are adopted to imitate the interactions among the individuals in both the teaching phase and the learning phase. To store the non-dominated solutions explored during the search process, an external archive is used and updated when necessary. The influence of the parameter setting on the mTLBO in solving the RHFSP is investigated, and numerical tests with some benchmarking instances are carried out. The comparative results show that the proposed mTLBO outperforms the existing algorithms significantly.     

Algorithm for the extraction of page-formatted binary digital data

We present an algorithm for fast and reliable extraction of page-formatted binary digital data. The advantages of the algorithm include a low raw bit-error rate, fast extraction speed, the use of a simple and density-efficient coding scheme, and large tolerance to a change of the signal-to-noise ratio. We used this algorithm to analyze shot-noise-limited binary data that had large interpage and intrapage intensity variations and obtained an improvement in the bit-error rate of 3-4 orders of magnitude compared with that in a single-threshold-detection scheme. Implications of our results for the development of high-speed, high-density holographic memories are discussed.     

The first measurement of an absolute surface concentration of reaction intermediates in ethylene hydrogenation

The first measurement of a turnover rate with respect to surface intermediate concentration in a high pressure heterogeneous catalytic reaction is reported. By using infrared-visible sum frequency generation to study the hydrogenation of ethylene on Pt(111), it was found that the surface concentration of -bonded ethylene, the key reaction intermediate, represented approximately 4% of a monolayer. Thus the absolute turnover rate per surface adsorbed ethylene molecule is 25 times faster than the rate measured per platinum atom. To explain these results, we propose a model of weakly adsorbed ethylene intermediates reacting on atop sites.     

Load-balanced parallel streamline generation on large scale vector fields

Because of the ever increasing size of output data from scientific simulations, supercomputers are increasingly relied upon to generate visualizations. One use of supercomputers is to generate field lines from large scale flow fields. When generating field lines in parallel, the vector field is generally decomposed into blocks, which are then assigned to processors. Since various regions of the vector field can have different flow complexity, processors will require varying amounts of computation time to trace their particles, causing load imbalance, and thus limiting the performance speedup. To achieve load-balanced streamline generation, we propose a workload-aware partitioning algorithm to decompose the vector field into partitions with near equal workloads. Since actual workloads are unknown beforehand, we propose a workload estimation algorithm to predict the workload in the local vector field. A graph-based representation of the vector field is employed to generate these estimates. Once the workloads have been estimated, our partitioning algorithm is hierarchically applied to distribute the workload to all partitions. We examine the performance of our workload estimation and workload-aware partitioning algorithm in several timings studies, which demonstrates that by employing these methods, better scalability can be achieved with little overhead.     

Optimal Error Estimates of the Legendre Tau Method for Second-Order Differential Equations

In this paper, we prove that the Legendre tau method has the optimal rate of convergence in L ²-norm, H ¹-norm and H ²-norm for one-dimensional second-order steady differential equations with three kinds of boundary conditions and in C([0,T];L ²(I))-norm for the corresponding evolution equation with the Dirichlet boundary condition. For the generalized Burgers equation, we develop a Legendre tau-Chebyshev collocation method, which can also be optimally convergent in C([0,T];L ²(I))-norm. Finally, we give some numerical examples.