A 1-bit electronically reconfigurable beam steerable metasurface reflectarray with multiple polarization manipulations

A 1-bit electronically controlled metasurface reflectarray is presented to achieve beam steering with multiple polarization manipulations. A metsurface unit cell loaded by two PIN diodes is designed. By switching the two PIN diodes between ON and OFF states, the isotropic and anisotropic reflections can be flexibly achieved. For either the isotropic reflection or the anisotropic reflection, the two operation states achieve the reflection coefficients with approximately equal magnitude and 180°out of phase, thus giving rise to the isotropic/anisotropic 1-bit metasurface unit cells. With the 1-bit unit cells, a 12-by-12 metasurface reflectarray is optimally designed and fabricated. Under either y-or x-polarized incident wave illumination, the reflectarray can achieve the co-polarized and cross-polarized beam scanning, respectively, with the peak gains of 20.08 d Bi and 17.26 d Bi within the scan range of about ±50°. With the right-handed circular polarization(RHCP) excitation, the left-handed circular polarization(LHCP) radiation with the peak gain of 16.98 d Bic can be achieved within the scan range of ±50°. Good agreement between the experimental results and the simulation results are observed for 2D beam steering and polarization manipulation capabilities.

Wigner function of optical cumulant operator and its dissipation in thermo-entangled state representation

To conveniently calculate the Wigner function of the optical cumulant operator and its dissipation evolution in a thermal environment, in this paper, the thermo-entangled state representation is introduced to derive the general evolution formula of the Wigner function, and its relation to Weyl correspondence is also discussed. The method of integration within the ordered product of operators is essential to our discussion.

Effects of drive imbalance on the particle emission from a Bose-Einstein condensate in a one-dimensional lattice

Time-periodic driving has been an effective tool in the field of nonequilibrium quantum dynamics,which enables precise control of the particle interactions.We investigate the collective emission of particles from a Bose-Einstein condensate in a one-dimensional lattice with periodic drives that are separate in modulation amplitudes and relative phases.In addition to the enhancement of particle emission,we find that amplitude imbalances lead to energy shift and band broadening,while typical relative phases may give rise to similar gaps.These results offer insights into the specific manipulations of nonequilibrium quantum systems with tone-varying drives.

Optical Nonlinearity of Violet Phosphorus and Applications in Fiber Lasers

A D-shaped fiber is coated with a new two-dimensional nanomaterial,violet phosphorus(VP),to create a saturable absorber(SA)with a modulation depth of 3.68%.Subsequently,the SA is inserted into a fiber laser,enabling successful generation of dark solitons and bright–dark soliton pairs through adjustment of the polarization state within the cavity.Through further study,mode-locked pulses are achieved,proving the existence of polarization-locked vector solitons.The results indicate that VP can be used as a polarization-independent SA.

Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

Design and implementation of dual-mode configurable memory architecture for CNN accelerator

With the rapid development of deep learning algorithms,the computational complexity and functional diversity are increasing rapidly.However,the gap between high computational density and insufficient memory bandwidth under the traditional von Neumann architecture is getting worse.Analyzing the algorithmic characteristics of convolutional neural network(CNN),it is found that the access characteristics of convolution(CONV)and fully connected(FC)operations are very different.Based on this feature,a dual-mode reronfigurable distributed memory architecture for CNN accelerator is designed.It can be configured in Bank mode or first input first output(FIFO)mode to accommodate the access needs of different operations.At the same time,a programmable memory control unit is designed,which can effectively control the dual-mode configurable distributed memory architecture by using customized special accessing instructions and reduce the data accessing delay.The proposed architecture is verified and tested by parallel implementation of some CNN algorithms.The experimental results show that the peak bandwidth can reach 13.44 GB·s^(-1)at an operating frequency of 120 MHz.This work can achieve 1.40,1.12,2.80 and 4.70 times the peak bandwidth compared with the existing work.

Influence of High-Pressure Induced Lattice Dislocations and Distortions on Thermoelectric Performance of Pristine SnTe

As a sister compound of PbTe, SnTe possesses the environmentally friendly elements. However, the pristine SnTe compounds suffer from the high carrier concentration, the large valence band offset between the L and Σpositions and high thermal conductivity. Using high-pressure and high-temperature technology, we synthesized the pristine SnTe samples at different pressures and systemically investigated their thermoelectric properties.High pressure induces rich microstructures, including the high-density dislocations and lattice distortions, which serve as the strong phonon scattering centers, thereby reducing the lattice thermal conductivity. For the electrical properties, pressure reduces the harmful high carrier concentration, due to the depression of Sn vacancies.Moreover, pressure induces the valence band convergence, reducing the energy separation between the L and Σpositions. The band convergence and suppressed carrier concentration increase the Seebeck coefficient. Thus, the power factors of pressure-sintered compounds do not deteriorate significantly under the condition of decreasing electrical conductivity. Ultimately, for a pristine SnTe compound synthesized at 5 GPa, a higher ZT value of 0.51 is achieved at 750 K, representing a 140% improvement compared to the value of 0.21 obtained using SPS. Therefore, the high-pressure and high-temperature technology is demonstrated as an effectively approach to optimize thermoelectric performance.

Research and design of matrix operation accelerator based on reconfigurable array

In the case of massive data,matrix operations are very computationally intensive,and the memory limitation in standalone mode leads to the system inefficiencies.At the same time,it is difficult for matrix operations to achieve flexible switching between different requirements when implemented in hardware.To address this problem,this paper proposes a matrix operation accelerator based on reconfigurable arrays in the context of the application of recommender systems(RS).Based on the reconfigurable array processor(APR-16)with reconfiguration,a parallelized design of matrix operations on processing element(PE)array is realized with flexibility.The experimental results show that,compared with the proposed central processing unit(CPU)and graphics processing unit(GPU)hybrid implementation matrix multiplication framework,the energy efficiency ratio of the accelerator proposed in this paper is improved by about 35×.Compared with blocked alternating least squares(BALS),its the energy efficiency ratio has been accelerated by about 1×,and the switching of matrix factorization(MF)schemes suitable for different sparsity can be realized.

Interface engineering of transition metal dichalcogenide/GaN heterostructures:Modified broadband for photoelectronic performance

The GaN-based heterostructures are widely used in optoelectronic devices,but the complex surface reconstructions and lattice mismatch greatly limit the applications.The stacking of two-dimensional transition metal dichalcogenide(TMD=MoS_(2),MoSSe and MoSe_(2))monolayers on reconstructed GaN surface not only effectively overcomes the larger mismatch,but also brings about novel electronic and optical properties.By adopting the reconstructed GaN(0001)surface with adatoms(N-ter GaN and Ga-ter GaN),the influences of complicated surface conditions on the electronic properties of heterostructures have been investigated.The passivated N-ter and Ga-ter GaN surfaces push the mid-gap states to the valence bands,giving rise to small bandgaps in heterostructures.The charge transfer between Ga-ter GaN surface and TMD monolayers occurs much easier than that across the TMD/N-ter GaN interfaces,which induces stronger interfacial interaction and larger valence band offset(VBO).The band alignment can be switched between type-I and type-II by assembling different TMD monolayers,that is,MoS_(2)/N-ter GaN and MoS_(2)/Ga-ter GaN are type-II,and the others are type-I.The absorption of visible light is enhanced in all considered TMD/reconstructed GaN heterostructures.Additionally,MoSe_(2)/Ga-ter GaN and MoSSe/N-ter GaN have larger conductor band offset(CBO)of 1.32 eV and 1.29 eV,respectively,extending the range from deep ultraviolet to infrared regime.Our results revel that the TMD/reconstructed GaN heterostructures may be used for high-performance broadband photoelectronic devices.

Modeling and Simulation of Heterojunction Solar Cell with Mono Crystalline Silicon

The monocrystalline silicon is a promising material that could be used in solar cells that convert light into electricity. Although the cost of ordinary silicon (Si) solar cells has decreased significantly over the past two decades, the conversion efficiency of these cells has remained relatively high. While solar cells have a great potential as a device of renewable energy, the high cost they incur per Watt continues to be a significant barrier to their widespread implementation. As a consequence, it is vital to conduct research into alternate materials that may be used in the construction of solar cells. The heterojunction solar cell (HJSC), which is based on n-type zinc oxide (n-ZnO) and p-type silicon (p-Si), is one of the numerous alternatives of the typical Si single homojunction solar cell. There are many deficiencies that can be found in the published research on n-ZnO/p-Si heterojunction solar cell. Inconsistencies in the stated value of open circuit voltage (Voc) of the solar cell are one example of deficiency. The absence of a full theoretical study to evaluate the potential of the solar cell structure is another deficiency that can be found in these researches. A lower value of experimentally obtained VOC in comparison to the theoretical prediction based on the band-gap between n-ZnO and p-Si. There needs to be more consensus among scientists regarding the optimal conditions for the growth of zinc oxide. Many software’s are available for simulating and optimizing the solar cells based on these parameters. For this purpose, in this dissertation, I provide computational results relevant to n-ZnO/p-Si HJSC to overcome deficiencies that have been identified. While modeling and simulating the potential of the solar cell structure with AFORS-HET, it is essential to consider the constraints that exist in the real world. AFORS-HET was explicitly designed to mimic the multilayer solar cell arrangement. In AFORS-HET, we can add up to seven layers for solar cell layout. By using this software, we can figure out the open circuit voltage (VOC), the short circuit current (JSC), the quantum efficiency (QE, %), the heterojunction energy band structure, and the power conversion efficiency (PCE).

Electronic structure and optical properties of Ge-and F-doped α-Ga2O3:First-principles investigations

The prospect ofα-Ga2O3 in optical and electrical devices application is fascinating.In order to obtain better performance,Ge and F elements with similar electronegativity and atomic size are selected as dopants.Based on density functional theory(DFT),we systematically research the electronic structure and optical properties of dopedα-Ga2O3 by GGA+U calculation method.The results show that Ge atoms and F atoms are effective n-type dopants.For Ge-dopedα-Ga2O3,it is probably obtained under O-poor conditions.However,for F-dopedα-Ga2O3,it is probably obtained under O-rich conditions.The doping system of F element is more stable due to the lower formation energy.In this investigation,it is found that two kinds of doping can reduce theα-Ga2O3 band gap and improve the conductivity.What is more,it is observed that the absorption edge after doping has a blue shift and causes certain absorption effect on the visible region.Through the whole scale of comparison,Ge doping is more suitable for the application of transmittance materials,yet F doping is more appropriate for the application of deep ultraviolet devices.We expect that our research can provide guidance and reference for preparation ofα-Ga2O3 thin films and photoelectric devices.

Modeling and Simulation of Photoelectronic Lambda Bipolar Transistor

Based on the region model of lambda bipolar transistor ( LBT), a dividing region theory model of PLBT is set up,simulated and verified. Firstly, the principal operations of different kinds of photoelectronic lambda bipolar transistor ( PLBT) are characterized by a simple circuit model. Through mathematical analysis of the equivalent circuit, the typical characteristics curve is divided into positive resistance, peak, negative resistance and cutoff regions. Secondly, by analyzing and simulating this model, the ratio of MOSFET width to channel length, threshold voltage and common emitter gain are discovered as the main structure parameters that determine the characteristic curves of PLBT. And peak region width, peak current value, negative resistance value and valley voltage value of PLBT can be changed conveniently according to the actual demands by modifying these parameters. Finally comparisons of the characteristics of the fabricated devices and the simu- lation results are made, which show that the analytical results are in agreement with the observed devices characteristics.

LSTM-DPPO based deep reinforcement learning controller for path following optimization of unmanned surface vehicle

To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal policy opti-mization(DPPO)algorithm,which is a modified actor-critic-based type of reinforcement learning algorithm,is adapted to improve the controller performance in repeated trials.The LSTM network structure is introduced to solve the strong temporal cor-relation USV control problem.In addition,a specially designed path dataset,including straight and curved paths,is established to simulate various sailing scenarios so that the reinforcement learning controller can obtain as much handling experience as possible.Extensive numerical simulation results demonstrate that the proposed method has better control performance under missions involving complex maneuvers than trained with limited scenarios and can potentially be applied in practice.

Towards the Deep Convergence of Communication and Computing in RAN: Scenarios, Architecture, Key Technologies, Challenges and Future Trends

To accommodate the diversified emerging use cases in 5G,radio access networks(RAN)is required to be more flexible,open,and versatile.It is evolving towards cloudification,intelligence and openness.By embedding computing capabilities within RAN,it helps to transform RAN into a natural cost effective radio edge computing platform,offering great opportunity to further enhance RAN agility for diversified services and improve users’quality of experience(Qo E).In this article,a logical architecture enabling deep convergence of communication and computing in RAN is proposed based on O-RAN.The scenarios and potential benefits of sharing RAN computing resources are first analyzed.Then,the requirements,design principles and logical architecture are introduced.Involved key technologies are also discussed,including heterogeneous computing infrastructure,unified computing and communication task modeling,joint communication and computing orchestration and RAN computing data routing.Followed by that,a VR use case is studied to illustrate the superiority of the joint communication and computing optimization.Finally,challenges and future trends are highlighted to provide some insights on the potential future work for researchers in this field.

Individual Identification of Electronic Equipment Based on Electromagnetic Fingerprint Characteristics

With the rapid development of communication and computer,the individual identification technology of communication equipment has been brought to many application scenarios.The identification of the same type of electronic equipment is of considerable significance,whether it is the identification of friend or foe in military applications,identity determination,radio spectrum management in civil applications,equipment fault diagnosis,and so on.Because of the limited-expression ability of the traditional electromagnetic signal representation methods in the face of complex signals,a new method of individual identification of the same equipment of communication equipment based on deep learning is proposed.The contents of this paper include the following aspects:(1)Considering the shortcomings of deep learning in processing small sample data,this paper provides a universal and robust feature template for signal data.This paper constructs a relatively complete signal template library from multiple perspectives,such as time domain and transform domain features,combined with high-order statistical analysis.Based on the inspiration of the image texture feature,characteristics of amplitude histogram of signal and the signal amplitude co-occurrence matrix(SACM)are proposed in this paper.These signal features can be used as a signal fingerprint template for individual identification.(2)Considering the limitation of the recognition rate of a single classifier,using the integrated classifier has achieved better generalization ability.The final average accuracy of 5 NRF24LE1 modules is up to 98%and solved the problem of individual identification of the same equipment of communication equipment under the condition of the small sample,low signal-to-noise ratio.

Effective implementation and improvement of fast labeled multi-Bernoulli filter

Effective implementation of the fast labeled multi-Bernoulli(FLMB)filter is addressed for target tracking with interval measurements.Firstly,a sequential Monte Carlo(SMC)implementation of the FLMB filter,SMC-FLMB filter,is derived based on generalized likelihood function weighting.Then,a box particle(BP)implementation of the FLMB filter,BP-FLMB filter,is developed,with a computational complexity reduction of the SMC-FLMB filter.Finally,an improved version of the BP-FLMB filter,improved BP-FLMB(IBP-FLMB)filter,is proposed,improving its estimation accuracy and real-time performance under the conditions of low detection probability and high clutter.Simulation results show that the BP-FLMB filter has a great improvement of the real-time performance than the SMC-FLMB filter,with similar tracking performance.Compared with the BP-FLMB filter,the IBP-FLMB filter has better estimation performance and real-time performance under the conditions of low detection probability and high clutter.

An accurate analytical surface potential model of heterojunction tunnel FET

Based on the accurate and efficient thermal injection method, we develop a fully analytical surface potential model for the heterojunction tunnel field-effect transistor(H-TFET). This model accounts for both the effects of source depletion and inversion charge, which are the key factors influencing the charge, capacitance and current in H-TFET. The accuracy of the model is validated against TCAD simulation and is greatly improved in comparison with the conventional model based on Maxwell–Boltzmann approximation. Furthermore, the dependences of the surface potential and electric field on biases are well predicted and thoroughly analyzed.

Secure and Trusted Interoperability Scheme of Heterogeneous Blockchains Platform in IoT Networks

With the rapid development of the Internet of Things(IoT),there is an increasing need for interac-tion between different networks.In order to improve the level of interconnection,especially the interoper-ability of users/devices between different nodes is very important.In the IoT heterogeneous blockchain sce-nario,how to ensure the legitimacy of the chain and how to confirm the identity of cross-chain informa-tion users/devices become the key issues to be solved for blockchain interoperability.In this paper,we pro-pose a secure and trusted interoperability mechanism for IoT based on heterogeneous chains to improve the security of blockchain interoperability.In this mecha-nism,a primary sidechain architecture supporting au-thentication at both ends of the heterogeneous chain is designed.In addition,a distributed gateway archi-tecture is proposed for cross-chain authentication and protocol conversion.The security and performance analysis shows that our scheme is feasible and effec-tive in improving the security of cross-chain opera-tions in IoT.

New light fields based on integration theory within the Weyl ordering product of operators

The development of quantum optics theory based on the method of integration within an ordered product of operators(IWOP)has greatly stimulated the study of quantum states in the light field,especially non-Gaussian states with various non-classical properties.In this paper,the two-mode squeezing operator is derived with integral theory within the Weyl ordering product of operators using a combinatorial field in which one mode is a chaotic field and the other mode is a vacuum field.The density operator of the new light field,its entanglement property and photon number distribution are analyzed.We also note that tracing a three-mode pure state can yield this new light field.These methods represent a theoretical approach to investigating new density operators of light fields.

QoS-Aware Offloading Based on Communication-Computation Resource Coordination for 6G Edge Intelligence

Driven by the demands of diverse artificial intelligence(AI)-enabled application,Mobile Edge Computing(MEC)is considered one of the key technologies for 6G edge intelligence.In this paper,we consider a serial task model and design a quality of service(QoS)-aware task offloading via communication-computation resource coordination for multi-user MEC systems,which can mitigate the I/O interference brought by resource reuse among virtual machines.Then we construct the system utility measuring QoS based on application latency and user devices’energy consumption.We also propose a heuristic offloading algorithm to maximize the system utility function with the constraints of task priority and I/O interference.Simulation results demonstrate the proposed algorithm’s significant advantages in terms of task completion time,terminal energy consumption and system resource utilization.