横向沙丘表面与上方矩形截面柱复合电磁散射的FDTD研究

分别使用指数型分布和高斯型分布表示沙漠表面的高度起伏状况,采用蒙特卡罗方法模拟横向沙丘表面和沙丘与沙丘间平坦沙漠表面,运用Herkelrath提出的土壤湿度与介电常数的通用式计算沙土的介电常数,选用FDTD数值计算方法分析高度起伏均方根、入射角度、目标长度、目标宽度、目标高度、横向沙丘的高度和横向沙丘迎风坡坡底到坡顶的水平距离的变化对散射系数的影响,得到横向沙丘表面与上方目标的复合电磁散射特性。分析了粗糙面为指数型分布和高斯型分布时散射系数的角分布曲线的不同之处。

一种基于非均匀磁化等离子体的修正Z-FDTD算法

对已有的Z变换时域有限差分法(Z-transformation Finite Difference Time Domain,Z-FDTD)在电磁波与非均匀磁化等离子体中的传输特性分析的计算误差问题进行了研究,并探讨了一种修正计算误差的Z变换时域有限差分方法(Modified Z-transform Finite Difference Time Domain,MZ-FDTD),以提升Z-FDTD方法对非均匀磁化等离子体的适用性。对MZ-FDTD和Z-FDTD之间的计算误差问题,通过严格的公式推导求得该误差的计算公式,并引入误差分析因子,对比分析了该误差受空间步长和非均匀磁化等离子体的物理特性的影响特征,在充分的误差分析与网格参数对比后,以电磁波在非均匀磁化等离子体中的传输特性为分析目标,举例说明了MZ-FDTD的优越性。研究结果表明,相比于经典Z-FDTD,通过MZ-FDTD方法计算得到的数值结果具有更高的计算准确度,较低的运行时间和较少的运行内存占用。此外,对电磁波在非均匀等离子体中传输特性分析的举例说明也证明了相比于Z-FDTD,优化的Z-FDTD方法无论是在较低频段还是较高频段都保持较好的稳定性。在今后的工作中,使用MZ-FDTD方法研究非均匀磁化等离子体问题将会获得更好的计算结果,这项工作中的误差分析方法也将对某些计算电磁学在等离子体中的应用与优化工作起到一定的帮助作用。

基于HIE-FDTD方法的电磁热耦合分析快速计算方法研究

基于混合显隐式时域有限差分(hybrid implicit-explicit finite-difference time-domain,HIE-FDTD)方法,提出了一种电磁热耦合分析快速计算方法。仿真电磁场时,采用HIE-FDTD方法求解Maxwell旋度方程;计算温度场时,采用时域有限差分(finite-difference time-domain,FDTD)方法求解热传导方程。由于HIE-FDTD方法只对1维空间偏导数采用隐式差分方法进行离散,因此时间步长不受电磁目标精细结构所在方向网格大小的限制。采用电磁热耦合分析快速计算方法对十字缝隙频率选择表面的电磁热耦合效应进行分析,并将仿真结果与采用传统FDTD方法、CST软件以及COMSOL软件的仿真结果进行对比,所有结果均相互符合。十字缝隙频率选择表面算例结果表明:在保证计算精度的前提下,采用HIE-FDTD方法的仿真时间仅为传统FDTD方法仿真时间的1/6,有效提高了电磁热耦合仿真的计算效率。

基于ADI-FDTD法的探地雷达正演数值模拟及验证

探地雷达(GPR)是一种应用前景广泛、用于探测和定位地下物体的浅层地球物理方法。通过开展探地雷达正演模拟研究,可以获得复杂地下结构的探地雷达图像回波特征。时域有限差分(FDTD)法受到稳定性和收敛性条件的限制,导致效率和精度低。交替方向隐式-时域有限差分(ADI-FDTD)法克服FDTD法的稳定性限制,可以选择更大的时间步长来提高计算效率。从原理出发,对ADI-FDTD法进行公式推导,在基于ADI-FDTD法的基础上进行卷积完全匹配层(CPML)的结合。通过进行ADI-FDTD法的时间稳定性仿真和不同材质、不同填充介质的双管,沙槽正演模拟实验,结果表明,ADI-FDTD法可以保证时间无条件稳定性,相同情况下可采用更大的时间步长进行正演模拟,提高正演效率。对不同管线、不同材质情况下的正演剖面曲线特征进行解译分析,最后与沙槽实测进行对比,证明得到的探测解译结果与实际状况达到较好的吻合。

利用FDTD计算超薄金壳中的等离子银纳米空腔

通过时域有限差分方法,对超薄金壳中的等离子银纳米空腔进行模拟分析。发现带有金壳的银纳米颗粒场增强效果要高于纯银纳米颗粒,并且理论上超薄的金壳还可以保护银纳米颗粒,防止其被氧化。通过与金膜相结合,形成腔型结构,发现场增强更加明显。这种结构是一种实验上可以实现的简单结构。这项工作为开发具有宽光谱增强电磁场的等离子金属纳米腔体结构铺平了道路。此外,这项研究还为生命科学领域的成像和检测提供了一种有效的SERS基底。

Estimation-free spatial-domain image reconstruction of structured illumination microscopy

Structured illumination microscopy(SIM)achieves super-resolution(SR)by modulating the high-frequency information of the sample into the passband of the optical system and subsequent image reconstruction.The traditional Wiener-filtering-based reconstruction algorithm operates in the Fourier domain,it requires prior knowledge of the sinusoidal illumination patterns which makes the time-consuming procedure of parameter estimation to raw datasets necessary,besides,the parameter estimation is sensitive to noise or aberration-induced pattern distortion which leads to reconstruction artifacts.Here,we propose a spatial-domain image reconstruction method that does not require parameter estimation but calculates patterns from raw datasets,and a reconstructed image can be obtained just by calculating the spatial covariance of differential calculated patterns and differential filtered datasets(the notch filtering operation is performed to the raw datasets for attenuating and compensating the optical transfer function(OTF)).Experiments on reconstructing raw datasets including nonbiological,biological,and simulated samples demonstrate that our method has SR capability,high reconstruction speed,and high robustness to aberration and noise.

基于JEC-FDTD等效循环神经网络的电磁建模和等离子体参数反演

磁化等离子体中的电磁波传播是重要的研究课题,针对特定场景下的电磁等离子耦合问题,进行有效且准确的方程建模与参数求解具有极强的研究价值和挑战性,这是探究电磁波与等离子体复杂非线性相互作用机制的关键。文中设计了一种可用于电磁等离子体正逆向建模的循环神经网络(recurrent neural network,RNN),该网络正向传播过程等价于任意磁倾角情况下的电流密度卷积时域有限差分(current density convolution finite-difference time-domain,JEC-FDTD)方法,因此可以求解给定的电磁建模问题,并易于大规模并行计算。通过构建前向可微模拟过程,JEC-FDTD方法可以使用自动微分技术准确且高效地计算梯度,然后通过训练网络来解决反问题。因此,该方法可以有效利用观测到的时域散射场信号反演重要的等离子体参数。JEC-FDTD方法和RNN相结合,形成了较强的协同效应,使得模型具有可解释性和高效的计算效率,受益于深度学习提供的优化策略和专用硬件支持,可以适用于不同仿真场景下的电磁建模和等离子体参数反演。

Delineating homogeneous domains of fractured rocks using topological manifolds and deep learning

Determining homogeneous domains statistically is helpful for engineering geological modeling and rock mass stability evaluation.In this text,a technique that can integrate lithology,geotechnical and structural information is proposed to delineate homogeneous domains.This technique is then applied to a high and steep slope along a road.First,geological and geotechnical domains were described based on lithology,faults,and shear zones.Next,topological manifolds were used to eliminate the incompatibility between orientations and other parameters(i.e.trace length and roughness)so that the data concerning various properties of each discontinuity can be matched and characterized in the same Euclidean space.Thus,the influence of implicit combined effect in between parameter sequences on the homogeneous domains could be considered.Deep learning technique was employed to quantify abstract features of the characterization images of discontinuity properties,and to assess the similarity of rock mass structures.The results show that the technique can effectively distinguish structural variations and outperform conventional methods.It can handle multisource engineering geological information and multiple discontinuity parameters.This technique can also minimize the interference of human factors and delineate homogeneous domains based on orientations or multi-parameter with arbitrary distributions to satisfy different engineering requirements.

高阶SF-SFDTD方法在含时薛定谔方程求解中的应用研究

时域有限差分方法(finite-difference time-domain,FDTD(2,2))被广泛用于量子力学中薛定谔方程的求解,然而受Courant-Friedrichs-Lewy(CFL)条件的影响,计算空间中的网格尺寸会限制时间步长的取值范围,极大降低了FDTD(2,2)方法的数值计算效率.另外,FDTD(2,2)方法在时间域和空间域只具有二阶数值精度,在计算中往往会导致较大的误差累计,影响仿真结果的正确性.为了克服这些问题,结合空间滤波方法(spatial filtering,SF)和高阶辛时域有限差分(symplectic finite-difference time-domain,SFDTD(3,4))方法(3和4分别表示时间和空间数值精度),提出了一种时间稳定性条件可扩展的SF-SFDTD(3,4)方法用于求解含时薛定谔方程.SF-SFDTD(3,4)方法无需对传统SFDTD(3,4)方法的迭代公式进行进一步的推导,只需要在每一次的数值迭代过程中加入空间滤波操作,滤除因采用不满足CFL条件的时间步长而产生的不稳定空间域高频分量,保证数值方法的稳定性,因此所提方法与传统SFDTD(3,4)方法具有较高的兼容性.同时,理论分析了SF-SFDTD(3,4)方法的数值色散误差.最后,通过数值算例验证了本文所提方法的正确性和有效性.

Consistency between domain wall oscillation modes and spin wave modes in nanostrips

Investigations on domain wall(DW) and spin wave(SW) modes in a series of nanostrips with different widths and thicknesses have been carried out using micromagnetic simulation. The simulation results show that the frequencies of SW modes and the corresponding DW modes are consistent with each other if they have the same node number along the width direction. This consistency is more pronounced in wide and thin nanostrips, favoring the DW motion driven by SWs.Further analysis of the moving behavior of a DW driven by SWs is also carried out. The average DW speed can reach a larger value of ~ 140 m/s under two different SW sources. We argue that this study is very meaningful for the potential application of DW motion driven by SWs.

Low-Rank Optimal Transport for Robust Domain Adaptation

When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.

Multiple Matching Attenuation Based on Curvelet Domain Extended Filtering

The paper develops a multiple matching attenuation method based on extended filtering in the curvelet domain,which combines the traditional Wiener filtering method with the matching attenuation method in curvelet domain.Firstly,the method uses the predicted multiple data to generate the Hilbert transform records,time derivative records and time derivative records of Hilbert transform.Then,the above records are transformed into the curvelet domain and multiple matching attenuation based on least squares extended filtering is performed.Finally,the attenuation results are transformed back into the time-space domain.Tests on the model data and field data show that the method proposed in the paper effectively suppress the multiples while preserving the primaries well.Furthermore,it has higher accuracy in eliminating multiple reflections,which is more suitable for the multiple attenuation tasks in the areas with complex structures compared to the time-space domain extended filtering method and the conventional curvelet transform method.

BIG HANKEL OPERATORS ON HARDY SPACES OF STRONGLY PSEUDOCONVEX DOMAINS

In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f ) is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO and we obtain some characterizations for Hf on H^(2)(Ω) of other pseudoconvex domains.In these arguments,Amar's L^(p)-estimations and Berndtsson's L^(2)-estimations for solutions of the ■_(b)-equation play a crucial role.In addition,we solve Gleason's problem for Hardy spaces H^(p)(Ω)(1 ≤p≤∞) of bounded strongly pseudoconvex domains.

Complementary-Label Adversarial Domain Adaptation Fault Diagnosis Network under Time-Varying Rotational Speed and Weakly-Supervised Conditions

Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly expensive.Meanwhile,the number of samples collected from different health states is often unbalanced.To deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised conditions.In the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction results.In adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target domain.Comparative experiments on two case studies validated the superior performance of the proposed method.

ON THE SOBOLEV DOLBEAULT COHOMOLOGY OF A DOMAIN WITH PSEUDOCONCAVE BOUNDARIES

In this note,we mainly make use of a method devised by Shaw[15]for studying Sobolev Dolbeault cohomologies of a pseudoconcave domain of the type Ω=Ω\∪_(j=1^(m))Ω_(j),where Ω and {Ω_(j)}_(j=1^(m)■Ω are bounded pseudoconvex domains in ℂ^(n) with smooth boundaries,and Ω_(1),…,Ω_(m) are mutually disjoint.The main results can also be quickly obtained by virtue of[5].

Diabetic retinopathy identification based on multi-sourcefree domain adaptation

AIM:To address the challenges of data labeling difficulties,data privacy,and necessary large amount of labeled data for deep learning methods in diabetic retinopathy(DR)identification,the aim of this study is to develop a source-free domain adaptation(SFDA)method for efficient and effective DR identification from unlabeled data.METHODS:A multi-SFDA method was proposed for DR identification.This method integrates multiple source models,which are trained from the same source domain,to generate synthetic pseudo labels for the unlabeled target domain.Besides,a softmax-consistence minimization term is utilized to minimize the intra-class distances between the source and target domains and maximize the inter-class distances.Validation is performed using three color fundus photograph datasets(APTOS2019,DDR,and EyePACS).RESULTS:The proposed model was evaluated and provided promising results with respectively 0.8917 and 0.9795 F1-scores on referable and normal/abnormal DR identification tasks.It demonstrated effective DR identification through minimizing intra-class distances and maximizing inter-class distances between source and target domains.CONCLUSION:The multi-SFDA method provides an effective approach to overcome the challenges in DR identification.The method not only addresses difficulties in data labeling and privacy issues,but also reduces the need for large amounts of labeled data required by deep learning methods,making it a practical tool for early detection and preservation of vision in diabetic patients.

Magnetic domain structures in ultrathin Bi_(2)Te_(3)/CrTe_(2) heterostructures

Chromium tellurium compounds are important two-dimensional van der Waals ferromagnetic materials with high Curie temperature and chemical stability in air,which is promising for applications in spintronic devices.Here,highquality spin-orbital-torque(SOT)device,Bi_(2)Te_(3)/CrTe_(2)heterostructure was epitaxially grown on Al_(2)O_(3)(0001)substrates.Anomalous Hall measurements indicate the existence of strong ferromagnetism in this device with the CrTe_(2)thickness down to 10 nm.In order to investigate its micromagnetic structure,cryogenic magnetic force microscope(MFM)was utilized to measure the magnetic domain evolutions at various temperatures and magnetic fields.The virgin domain state of the device shows a worm-like magnetic domain structure with the size around 0.6μm-0.8μm.Larger irregular-shape magnetic domains(>1μm)can be induced and pinned,after the field is increased to coercive field and ramped back to low fields.The temperature-dependent MFM signals exhibit a nice mean-field-like ferromagnetic transition with Curie temperature around 201.5 K,indicating a robust ferromagnetic ordering.Such a device can be potentially implemented in future magnetic memory technology.

MINIMIZERS OF L^(2)-SUBCRITICAL VARIATIONAL PROBLEMS WITH SPATIALLY DECAYING NONLINEARITIES IN BOUNDED DOMAINS

This paper is concerned with the minimizers of L^(2)-subcritical constraint variar tional problems with spatially decaying nonlinearities in a bounded domain Ω of R~N(N≥1).We prove that the problem admits minimizers for any M> 0.Moreover,the limiting behavior of minimizers as M→∞ is also analyzed rigorously.

Spatial correlations in time and frequency domains between chlorophyll-a concentration and environmental factors in the Bohai Sea

Based on the reconstructed MODIS data and ECMWF reanalysis data from 2003 to 2021,spatial correlations between chlorophyll a(Chl a)and sea surface temperature(SST),photosynthetically available radiation(PAR),aerosol optical thickness(AOT),and wind speed(WS)in the Bohai Sea were analyzed from the perspective of time domain and frequency domain.Results indicate that the frequency domain analysis was more conducive to revealing the correlations between Chl a and environmental factors.The spatial pattern of time-domain correlations was similar to the isobaths of the Bohai Sea,which was positive in shallow waters and negative in deep waters for SST,PAR,and AOT,and was reversed for WS.Frequency-domain correlations were obtained by performing Fourier Transform and were higher than correlations in time domain.The spatial distributions indicated that the effects of SST and PAR on Chl a were greater than AOT and WS in the Bohai Sea.Additionally,cross-spectrum analysis was applied to explore the response relationships.A depth-dependent pattern was shown in correlations and time lags,indicating that the influential mechanism of environmental factors on Chl-a concentration is related to seawater depth.

A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.