Modulation of High-Order Harmonic Generation from a Monolayer ZnO by Co-rotating Two-Color Circularly Polarized Laser Fields

By numerically solving the two-dimensional semiconductor Bloch equation,we study the high-order harmonic emission of a monolayer ZnO under the driving of co-rotating two-color circularly polarized laser pulses.By changing the relative phase between the fundamental frequency field and the second one,it is found that the harmonic intensity in the platform region can be significantly modulated.In the higher order,the harmonic intensity can be increased by about one order of magnitude.Through time-frequency analysis,it is demonstrated that the emission trajectory of monolayer ZnO can be controlled by the relative phase,and the harmonic enhancement is caused by the second quantum trajectory with the higher emission probability.In addition,near-circularly polarized harmonics can be generated in the co-rotating two-color circularly polarized fields.With the change of the relative phase,the harmonics in the platform region can be altered from left-handed near-circularly polarization to right-handed one.Our results can obtain high-intensity harmonic radiation with an adjustable ellipticity,which provides an opportunity for syntheses of circularly polarized attosecond pulses.

Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

SMSTracker:A Self-Calibration Multi-Head Self-Attention Transformer for Visual Object Tracking

Visual object tracking plays a crucial role in computer vision.In recent years,researchers have proposed various methods to achieve high-performance object tracking.Among these,methods based on Transformers have become a research hotspot due to their ability to globally model and contextualize information.However,current Transformer-based object tracking methods still face challenges such as low tracking accuracy and the presence of redundant feature information.In this paper,we introduce self-calibration multi-head self-attention Transformer(SMSTracker)as a solution to these challenges.It employs a hybrid tensor decomposition self-organizing multihead self-attention transformermechanism,which not only compresses and accelerates Transformer operations but also significantly reduces redundant data,thereby enhancing the accuracy and efficiency of tracking.Additionally,we introduce a self-calibration attention fusion block to resolve common issues of attention ambiguities and inconsistencies found in traditional trackingmethods,ensuring the stability and reliability of tracking performance across various scenarios.By integrating a hybrid tensor decomposition approach with a self-organizingmulti-head self-attentive transformer mechanism,SMSTracker enhances the efficiency and accuracy of the tracking process.Experimental results show that SMSTracker achieves competitive performance in visual object tracking,promising more robust and efficient tracking systems,demonstrating its potential to providemore robust and efficient tracking solutions in real-world applications.

A Self-Attention Based Dynamic Resource Management for Satellite-Terrestrial Networks

The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.

Fully spin-polarized, valley-polarized and spin-valley-polarized electron beam splitters utilizing zero-line modes in a three-terminal device

Topological zero-line modes(ZLMs) with spin and valley degrees of freedom give rise to spin, valley and spinvalley transport, which support a platform for exploring quantum transport physics and potential applications in spintronic/valleytronic devices. In this work, we investigate the beam-splitting behaviors of the charge current due to the ZLMs in a three-terminal system. We show that with certain combinations of ZLMs, the incident charge current along the interface between different topological phases can be divided into different polarized currents with unit transmittance in two outgoing terminals. As a result, fully spin-polarized, valley-polarized and spin-valley-polarized electron beam splitters are generated. The mechanism of these splitters is attributed to the cooperative effects of the distribution of the ZLMs and the intervalley and intravalley scatterings that are modulated by the wave-vector mismatch and group velocity mismatch. Interestingly, half-quantized transmittance of these scatterings is found in a fully spin-valley-polarized electron beam splitter.Furthermore, the results indicate that these splitters can be applicable to graphene, silicene, germanene and stanene due to their robustness against the spin–orbit coupling. Our findings offer a new way to understand the transport mechanism and investigate the promising applications of ZLMs.

Missing Value Imputation for Radar-Derived Time-Series Tracks of Aerial Targets Based on Improved Self-Attention-Based Network

The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random missing(RM)that differs significantly from common missing patterns of RTT-AT.The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation.Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss.In this paper,a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed.Our model consists of two probabilistic sparse diagonal masking self-attention(PSDMSA)units and a weight fusion unit.It learns missing values by combining the representations outputted by the two units,aiming to minimize the difference between the missing values and their actual values.The PSDMSA units effectively capture temporal dependencies and attribute correlations between time steps,improving imputation quality.The weight fusion unit automatically updates the weights of the output representations from the two units to obtain a more accurate final representation.The experimental results indicate that,despite varying missing rates in the two missing patterns,our model consistently outperforms other methods in imputation performance and exhibits a low frequency of deviations in estimates for specific missing entries.Compared to the state-of-the-art autoregressive deep learning imputation model Bidirectional Recurrent Imputation for Time Series(BRITS),our proposed model reduces mean absolute error(MAE)by 31%~50%.Additionally,the model attains a training speed that is 4 to 8 times faster when compared to both BRITS and a standard Transformer model when trained on the same dataset.Finally,the findings from the ablation experiments demonstrate that the PSDMSA,the weight fusion unit,cascade network design,and imputation loss enhance imputation performance and confirm the efficacy of our design.

Prediction and scheduling of multi-energy microgrid based on BiGRU self-attention mechanism and LQPSO

To predict renewable energy sources such as solar power in microgrids more accurately,a hybrid power prediction method is presented in this paper.First,the self-attention mechanism is introduced based on a bidirectional gated recurrent neural network(BiGRU)to explore the time-series characteristics of solar power output and consider the influence of different time nodes on the prediction results.Subsequently,an improved quantum particle swarm optimization(QPSO)algorithm is proposed to optimize the hyperparameters of the combined prediction model.The final proposed LQPSO-BiGRU-self-attention hybrid model can predict solar power more effectively.In addition,considering the coordinated utilization of various energy sources such as electricity,hydrogen,and renewable energy,a multi-objective optimization model that considers both economic and environmental costs was constructed.A two-stage adaptive multi-objective quantum particle swarm optimization algorithm aided by a Lévy flight,named MO-LQPSO,was proposed for the comprehensive optimal scheduling of a multi-energy microgrid system.This algorithm effectively balances the global and local search capabilities and enhances the solution of complex nonlinear problems.The effectiveness and superiority of the proposed scheme are verified through comparative simulations.

Fully polarized Compton scattering in plane waves and its polarization transfer

Fully polarized Compton scattering from a beam of spin-polarized electrons is investigated in plane-wave backgrounds in a broad intensity region from the perturbative to the nonperturbative regimes.In the perturbative regime,polarized linear Compton scattering is considered for investigating polarization transfer from a single laser photon to a scattered photon,and in the high-intensity region,the polarized locally monochromatic approximation and locally constant field approximation are established and are employed to study polarization transfer from an incoming electron to a scattered photon.The numerical results suggest an appreciable improvement of about 10%in the scattering probability in the intermediate-intensity region if the electron’s longitudinal spin is parallel to the laser rotation.The longitudinal spin of the incoming electron can be transferred to the scattered photon with an efficiency that increases with laser intensity and collisional energy.For collision between an optical laser with frequency1 eV and a 10 GeV electron,this polarization transfer efficiency can increase from about 20%in the perturbative regime to about 50%in the nonperturbative regime for scattered photons with relatively high energy.

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

Polarization control of above-threshold ionization spectrum in elliptically polarized two-color laser fields

We study the above-threshold ionization(ATI)process of atoms exposed to fundamental and high-frequency lasers with arbitrary ellipticity by applying the frequency-domain theory.It is found that the angular-resolved ATI spectrum is sensitive to ellipticities of two lasers and emitted angles of the photoelectron.Particularly for the photon energy of the highfrequency laser more than atomic ionization potential,the width of plateau tends to a constant with increasing ellipticity of fundamental field,the dip structure disappears with increasing ellipticity of the high-frequency field.With the help of the quantum channel analysis,it is shown that the angular distribution depends mainly on the ellipticity of high-frequency field in the case that its frequency is high.Moreover,one can see that the maximal and minimal energies in quantum numerical results are in good agreement with the classical prediction.Our investigation may provide theoretical support for experimental research on polarization control of ionization in elliptically polarized two-color laser fields.

Self-polarized RGB device realized by semipolar micro-LEDs and perovskite-in-polymer films for backlight applications

In backlighting systems for liquid crystal displays,conventional red,green,and blue(RGB)light sources that lack polarization properties can result in a significant optical loss of up to 50%when passing through a polarizer.To address this inefficiency and optimize energy utilization,this study presents a high-performance device designed for RGB polarized emissions.The device employs an array of semipolar blueμLEDs with inherent polarization capabilities,coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid nanocrystals.The CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission,while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions,due to their high dielectric constant.The resulting device achieved RGB polarization degrees of 0.26,0.48,and 0.38,respectively,and exhibited a broad color gamut,reaching 137.2%of the NTSC standard and 102.5%of the Rec.2020 standard.When compared to a device utilizing c-plane LEDs for excitation,the current approach increased the intensity of light transmitted through the polarizer by 73.6%.This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

Bioinspired Polarized Optical Flow Enables Turbid Underwater Target Motion Estimation

Underwater target motion estimation is a challenge for ocean military and scientific research.In this work,we propose a method based on the combination of polarization imaging and optical flow for turbid underwater target detection.Polarization imaging can reduce the influence of backscattered light and obtain high-quality images underwater.The optical flow shows the motion and structural information of the target.We use polarized optical flow to obtain the optical flow field and estimate the target motion.The experimental results of different targets under varying water turbidity levels illustrate that our method is realizable and robust.The precision is verified by comparing the results with the precise displacement data and calculating two error measures.The proposed method based on polarized optical flow can obtain accurate displacement information and a good recognition effect.Moving target segmentation based on the Otsu method further proves the superiority of the polarized optical flow under turbid water.This study is valuable for target detection and motion estimation in scattering environments.

Recent progress on valley polarization and valley-polarized topological states in two-dimensional materials

Valleytronics, using valley degree of freedom to encode, process, and store information, may find practical applications in low-power-consumption devices. Recent theoretical and experimental studies have demonstrated that twodimensional(2D) honeycomb lattice systems with inversion symmetry breaking, such as transition-metal dichalcogenides(TMDs), are ideal candidates for realizing valley polarization. In addition to the optical field, lifting the valley degeneracy of TMDs by introducing magnetism is an efficient way to manipulate the valley degree of freedom. In this paper, we first review the recent progress on valley polarization in various TMD-based systems, including magnetically doped TMDs,intrinsic TMDs with both inversion and time-reversal symmetry broken, and magnetic TMD heterostructures. When topologically nontrivial bands are empowered into valley-polarized systems, valley-polarized topological states, namely valleypolarized quantum anomalous Hall effect can be realized. Therefore, we have also reviewed the theoretical proposals for realizing valley-polarized topological states in 2D honeycomb lattices. Our paper can help readers quickly grasp the latest research developments in this field.

Internal collision double ionization of molecules driven by co-rotating two-color circularly polarized laser pulses

The double ionization process of molecules driven by co-rotating two-color circularly polarized fields is investigated with a three-dimensional classical ensemble model. Numerical results indicate that a considerable part of the sequential double ionization(DI) events of molecules occur through internal collision double ionization(ICD), and the ICD recollision mechanism is significantly different from that in non-sequential double ionization(NSDI). By analyzing the results of internuclear distances R = 5 a.u. and 2 a.u., these two recollision mechanisms are studied in depth. It is found that the dynamic behaviors of the recollision mechanisms of NSDI and ICD are similar. For NSDI, the motion range of electrons after the ionization is relatively large, and the electrons will return to the core after a period of time. In the ICD process,electrons will rotate around the parent ion before ionization, and the distance of the electron motion is relatively small. After a period of time, the electrons will come back to the core and collide with another electron. Furthermore, the molecular internuclear distance has a significant effect on the electron dynamic behavior of the two ionization mechanisms. This study will help to understand the multi-electron ionization process of complex systems.

Elliptically polarized high-order harmonic generation of Ar atom in an intense laser field

High-order harmonic generation(HHG) of Ar atom in an elliptically polarized intense laser field is experimentally investigated in this work.Interestingly,the anomalous ellipticity dependence on the laser ellipticity(ε) in the lower-order harmonics is observed,specifically in the 13rd-order,which displays a maximal harmonic intensity at ε ≈ 0.1,rather than at ε = 0 as expected.This contradicts the general trend of harmonic yield,which typically decreases with the increase of laser ellipticity.In this study,we attribute this phenomenon to the disruption of the symmetry of the wave function by the Coulomb effect,leading to the generation of a harmonic with high ellipticity.This finding provides valuable insights into the behavior of elliptically polarized harmonics and opens up a potential way for exploring new applications in ultrafast spectroscopy and light–matter interactions.

Cloud Top Pressure Retrieval Using Polarized and Oxygen A-band Measurements from GF5 and PARASOL Satellites

Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.

Steering the energy sharing of electrons in nonsequential double ionization with orthogonally polarized two-color field

Using the semiclassical ensemble model,the dependence of relative amplitude for the recollision dynamics in nonsequential double ionization(NSDI)of neon atom driven by the orthogonally polarized two-color field(OTC)laser field is theoretically studied.And the dynamics in two typical collision pathways,recollision-impact-ionization(RII)and recollisionexcitation with subsequent ionization(RESI),is systematically explored.Our results reveal that the V-shaped structure in the correlated momentum distribution is mainly caused by the RII mechanism when the relative amplitude of the OTC laser field is zero,and the first ionized electrons will quickly skim through the nucleus and share few energy with the second electron.As the relative amplitude increases,the V-shaped structure gradually disappears and electrons are concentrated on the diagonal in the electron correlation spectrum,indicating that the energy sharing after electrons collision is symmetric for OTC laser fields with large relative amplitudes.Our studies show that changing the relative amplitude of the OTC laser field can efficiently control the electron–electron collisions and energy exchange efficiency in the NSDI process.

一种基于Polar译码度量选择的第三方高效PDCCH盲检方法

为研究和设计面向第三方场景的高效盲检方法,提出了一种基于Polar译码度量选择的第三方高效PDCCH盲检方法,其技术路线包括Polar译码算法与物理的下行控制信道(PDCCH)盲检算法2个板块.基于Polar译码盲检算法,引入一种基于下行控制信息(DCI)长度的Polar译码度量,提出了改进的基于Polar译码度量选择的第三方盲检方法.基于PDCCH盲检算法,引入一种重排序盲检算法.将改进的Polar译码算法与重排序盲检算法有机结合,提出面向第三方场景的高效PDCCH盲检方法.基于MATLAB平台搭建5G PDCCH盲检仿真链路,对所提方法进行验证与分析.结果表明,该方法能够同时有效减小PDCCH盲检次数与DCI候选长度数量,在保证目标捕获准确率的前提下提高盲检效率.

Circularly Polarized Light-Enabled Chiral Nanomaterials:From Fabrication to Application

For decades,chiral nanomaterials have been extensively studied because of their extraordinary properties.Chiral nanostructures have attracted a lot of interest because of their potential applications including biosensing,asymmetric catalysis,optical devices,and negative index materials.Circularly polarized light(CPL)is the most attractive source for chirality owing to its high availability,and now it has been used as a chiral source for the preparation of chiral matter.In this review,the recent progress in the field of CPL-enabled chiral nanomaterials is summarized.Firstly,the recent advancements in the fabrication of chiral materials using circularly polarized light are described,focusing on the unique strategies.Secondly,an overview of the potential applications of chiral nanomaterials driven by CPL is provided,with a particular emphasis on biosensing,catalysis,and phototherapy.Finally,a perspective on the challenges in the field of CPL-enabled chiral nanomaterials is given.

Performance analysis of quantum key distribution using polarized coherent-states in free-space channel

In free space channel,continuous-variable quantum key distribution(CV-QKD)using polarized coherent-states can not only make the signal state more stable and less susceptible to interference based on the polarization non-sensitive of the free-space channel,but also reduce the noise introduced by phase interference.However,arbitrary continuous modulation can not be carried out in the past polarization coding,resulting in that the signal state can not obtain arbitrary continuous value in Poincare space,and the security analysis of CV-QKD using polarized coherent-states in free space is not complete.Here we propose a new modulation method to extend the modulation range of signal states with an optical-fiber-based polarization controller.In particular,in terms of the main influence factors in the free-space channel,we utilize the beam extinction and elliptical model when considering the transmittance and adopt the formulation of secret key rate.In addition,the performance of the proposed scheme under foggy weather is also taken into consideration to reveal the influence of severe weather.Numerical simulation shows that the proposed scheme is seriously affected by attenuation under foggy weather.The protocol fails when visibility is less than 1 km.At the same time,the wavelength can affect the performance of the proposed scheme.Specifically,under foggy weather,the longer the wavelength,the smaller the attenuation coefficient,and the better the transmission performance.Our proposed scheme can expand the modulation range of signal state,and supplement the security research of the scheme in the free-space channel,thus can provide theoretical support for subsequent experiments.