Thermally Controllable Break Junctions with High Bandwidths and High Integrabilities

Break junctions are important in generating nanosensors and single molecular devices. The mechanically con- trollable break junction is the most widely used method for a break junction due to its simplicity and stability. However, the bandwidths of traditional devices are limited to about a few hertz. Moreover, when using traditional methods it is hard to allow independent control of more than one junction. Here we propose on-chip thermally controllable break junctions to overcome these challenges. This is verified by using finite element analysis. Adopting microelectromechanical systems produces features of high bandwidth and independent controllability to this new break junction system. The proposed method will have a wide range of applications on on-chip high speed independent controllable and highly integrated single molecule devices.

Weighted Probability Density Estimator with Updated Bandwidths

In this paper,the authors study a class of weighted version of probability density estimator.It is shown that the weighted estimator contains some existing estimators of probability density,no matter they are recursive or non-recursive.Some statistical results including weak consistency,strong consistency,rate of strong consistency,and asymptotic normality are established under some mild conditions.Moreover,the random weighted estimator is also investigated.Some numerical simulations and a real data analysis are presented to study the numerical performances of the estimators.

ON UPPER BOUNDS OF BANDWIDTHS OF TREES

B(G) denotes the bandwidth of graph G. For tree T, Ve(T)={v|v∈V(T) and dT(v)=1}. In this paper, we discuss bandwidths of trees and obtain that for any tree T,B(T)and the bounds is sharp. For two extreme cases, a tree with a minimal number of internal vertices or one with a maximal number of internal vertices, that is, a star or a path, the equality holds.This bounds is much better than the previous one, B(G) .

Achieving Ultra-Broad Microwave Absorption Bandwidth Around Millimeter-Wave Atmospheric Window Through an Intentional Manipulation on Multi-Magnetic Resonance Behavior

The utilization of electromagnetic waves is rapidly advancing into the millimeter-wave frequency range,posing increasingly severe challenges in terms of electromagnetic pollution prevention and radar stealth.However,existing millimeter-wave absorbers are still inadequate in addressing these issues due to their monotonous magnetic resonance pattern.In this work,rare-earth La^(3+)and non-magnetic Zr^(4+)ions are simultaneously incorporated into M-type barium ferrite(BaM)to intentionally manipulate the multi-magnetic resonance behavior.By leveraging the contrary impact of La^(3+)and Zr^(4+)ions on magnetocrystalline anisotropy field,the restrictive relationship between intensity and frequency of the multi-magnetic resonance is successfully eliminated.The magnetic resonance peak-differentiating and imitating results confirm that significant multi-magnetic resonance phenomenon emerges around 35 GHz due to the reinforced exchange coupling effect between Fe^(3+)and Fe^(2+)ions.Additionally,Mosbauer spectra analysis,first-principle calculations,and least square fitting collectively identify that additional La^(3+)doping leads to a profound rearrangement of Zr^(4+)occupation and thus makes the portion of polarization/conduction loss increase gradually.As a consequence,the La^(3+)-Zr^(4+)co-doped BaM achieves an ultra-broad bandwidth of 12.5+GHz covering from 27.5 to 40+GHz,which holds remarkable potential for millimeter-wave absorbers around the atmospheric window of 35 GHz.

Nitrogen‑Doped Magnetic‑Dielectric‑Carbon Aerogel for High‑Efficiency Electromagnetic Wave Absorption

Carbonbased aerogels derived from biomass chitosan are encountering a flourishing moment in electromagnetic protection on account of lightweight,controllable fabrication and versatility.Nevertheless,developing a facile construction method of component design with carbon-based aerogels for high-efficiency electromagnetic wave absorption(EWA)materials with a broad effective absorption bandwidth(EAB)and strong absorption yet hits some snags.Herein,the nitrogen-doped magnetic-dielectric-carbon aerogel was obtained via ice template method followed by carbonization treatment,homogeneous and abundant nickel(Ni)and manganese oxide(MnO)particles in situ grew on the carbon aerogels.Thanks to the optimization of impedance matching of dielectric/magnetic components to carbon aerogels,the nitrogen-doped magnetic-dielectric-carbon aerogel(Ni/MnO-CA)suggests a praiseworthy EWA performance,with an ultra-wide EAB of 7.36 GHz and a minimum reflection loss(RLmin)of−64.09 dB,while achieving a specific reflection loss of−253.32 dB mm−1.Furthermore,the aerogel reveals excellent radar stealth,infrared stealth,and thermal management capabilities.Hence,the high-performance,easy fabricated and multifunctional nickel/manganese oxide/carbon aerogels have broad application aspects for electromagnetic protection,electronic devices and aerospace.

Prediction of Bandwidth of Metamaterial Antenna Using Pearson Kernel-Based Techniques

The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial antennas.The radiation cost and quality factor of the antenna are influenced by the size of the antenna.Metamaterial antennas allow for the circumvention of the bandwidth restriction for small antennas.Antenna parameters have recently been predicted using machine learning algorithms in existing literature.Machine learning can take the place of the manual process of experimenting to find the ideal simulated antenna parameters.The accuracy of the prediction will be primarily dependent on the model that is used.In this paper,a novel method for forecasting the bandwidth of the metamaterial antenna is proposed,based on using the Pearson Kernel as a standard kernel.Along with these new approaches,this paper suggests a unique hypersphere-based normalization to normalize the values of the dataset attributes and a dimensionality reduction method based on the Pearson kernel to reduce the dimension.A novel algorithm for optimizing the parameters of Convolutional Neural Network(CNN)based on improved Bat Algorithm-based Optimization with Pearson Mutation(BAO-PM)is also presented in this work.The prediction results of the proposed work are better when compared to the existing models in the literature.

SSA-over-array(SSoA):A stacked DRAM architecture for nearmemory computing

Aiming to enhance the bandwidth in near-memory computing,this paper proposes a SSA-over-array(SSoA)architecture.By relocating the secondary sense amplifier(SSA)from dynamic random access memory(DRAM)to the logic die and repositioning the DRAM-to-logic stacking interface closer to the DRAM core,the SSoA overcomes the layout and area limitations of SSA and master DQ(MDQ),leading to improvements in DRAM data-width density and frequency,significantly enhancing bandwidth density.The quantitative evaluation results show a 70.18 times improvement in bandwidth per unit area over the baseline,with a maximum bandwidth of 168.296 Tbps/Gb.We believe the SSoA is poised to redefine near-memory computing development strategies.

Theoretical investigations of population trapping phenomena in atomic four-color,three-step photoionization scheme

The four-color three-step selective photoionization process of atom is very important in laser isotope separation technology.The population trapping phenomena and their influences are studied theoretically in monochromatic and non-monochromatic laser fields based on the density matrix theory in this work.Time evolutions of the photoionization properties of the four-color,three-step process are given.The population trapping effects occur intensely in monochromatic excitation,while it gradually turns weak as the laser bandwidth increases.The effects of bandwidth,Rabi frequency,time delay,and frequency detuning on the population trapping effect are investigated in monochromatic and non-monochromatic laser fields.The effects of laser process parameters and atomic parameters on the effective selective photoionization are also discussed.The ionization probability and selectivity factors,as evaluation indexes,are difficult to improve synchronously by adjusting systematic parameters.Besides,the existence of metastable state may play a negative role when its population is low enough.

A peak enhancement of frequency response of waveguide integrated silicon-based germanium avalanche photodetector

Avalanche photodetectors(APDs) featuring an avalanche multiplication region are vital for reaching high sensitivity and responsivity in optical transceivers. Waveguide-coupled Ge-on-Si separate absorption, charge, and multiplication(SACM)APDs are popular due to their straightforward fabrication process, low optical propagation loss, and high detection sensitivity in optical communications. This paper introduces a lateral SACM Ge-on-Si APD on a silicon-on-insulator(SOI) wafer, featuring a 10 μm-long, 0.5 μm-wide Ge layer at 1310 nm on a standard 8-inch silicon photonics platform. The dark current measures approximately 38.6 μA at-21 V, indicating a breakdown voltage greater than-21 V for the device. The APDs exhibit a unitgain responsivity of 0.5 A/W at-10 V. At-15 V, their responsivity reaches 2.98 and 2.91 A/W with input powers of-10 and-25 dBm, respectively. The device's 3-dB bandwidth is 15 GHz with an input power of-15 dBm and a gain is 11.68. Experimental results show a peak in impedance at high bias voltages, attributed to inductor and capacitor(LC) circuit resonance, enhancing frequency response. Furthermore, 20 Gbps eye diagrams at-21 V and-9 dBm input power reveal signal to noise ratio(SNRs) of 5.30. This lateral SACM APD, compatible with the stand complementary metal oxide semiconductor(CMOS) process,shows that utilizing the peaking effect at low optical power increases bandwidth.

Spectral characteristics of laser-plasma instabilities with a broadband laser

Recent experimental progresses regarding broadband laser-plasma instabilities(LPIs)show that a 0.6%laser bandwidth can reduce backscatters of the stimulated Brillouin scattering(SBS)and the stimulated Raman scattering(SRS)at normal incidence[Phys.Rev.Lett.132035102(2024)].In this paper,we present a further discussion of the spectral distributions of the scatters developed by broadband LPIs,in addition to a brief validation of the effectiveness of bandwidth on LPIs mitigation at oblique incidence.SBS backscatter has a small redshift in the broadband case contrary to the blueshift with narrowband laser,which may be explained by the self-cross beam energy transfer between the various frequency components within the bandwidth.SRS backscatter spectrum presents a peak at a longer wavelength in the broadband case compared to the short one in the narrowband case,which is possibly attributed to the mitigation effect of bandwidth on filaments at underdense plasmas.The three-halves harmonic emission(3ω/2)has a one-peak spectral distribution under the broadband condition,which is different from the two-peak distribution under the narrowband condition,and may be related to the spectral mixing of different frequency components within the bandwidth if the main sources of the two are both two-plasmon decays.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

Robust high frequency seismic bandwidth extension with a deep neural network trained using synthetic data

Geophysicists interpreting seismic reflection data aim for the highest resolution possible as this facilitates the interpretation and discrimination of subtle geological features.Various deterministic methods based on Wiener filtering exist to increase the temporal frequency bandwidth and compress the seismic wavelet in a process called spectral shaping.Auto-encoder neural networks with convolutional layers have been applied to this problem,with encouraging results,but the problem of generalization to unseen data remains.Most published works have used supervised learning with training data constructed from field seismic data or synthetic seismic data generated based on measured well logs or based on seismic wavefield modelling.This leads to satisfactory results on datasets similar to the training data but requires re-training of the networks for unseen data with different characteristics.In this work seek to improve the generalization,not by experimenting with network architecture(we use a conventional U-net with some small modifications),but by adopting a different approach to creating the training data for the supervised learning process.Although the network is important,at this stage of development we see more improvement in prediction results by altering the design of the training data than by architectural changes.The approach we take is to create synthetic training data consisting of simple geometric shapes convolved with a seismic wavelet.We created a very diverse training dataset consisting of 9000 seismic images with between 5 and 300 seismic events resembling seismic reflections that have geophysically motived perturbations in terms of shape and character.The 2D U-net we have trained can boost robustly and recursively the dominant frequency by 50%.We demonstrate this on unseen field data with different bandwidths and signal-to-noise ratios.Additionally,this 2D U-net can handle non-stationary wavelets and overlapping events of different bandwidth without creating excessive ringing.It is also robust in the presence of noise.The significance of this result is that it simplifies the effort of bandwidth extension and demonstrates the usefulness of auto-encoder neural network for geophysical data processing.

Design of a Technology Verification Platform for Space Electromagnetic Interference Signal Testing and Analysis

This paper designs a space electromagnetic interference signal test and analysis technology verification platform.The article firstly introduces the general scheme of the technical verification platform and then describes each component unit of the hardware and the overall structure of the software in detail.The platform can achieve a 10 MHz~50 GHz working frequency band,1.2 GHz acquisition and real-time recording bandwidth,6 GB/s recording rate,and 12 TB recording capacity.

The optimal fractional Gabor transform based on the adaptive window function and its application

We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.

High-resolution frequency-domain Radon transform and variable-depth streamer data deghosting

Receiver ghost reflections adversely affect variable-depth streamer （VDS） data acquisition. In addition, the frequency notches caused by the interference between receiver ghosts and primary waves strongly affect seismic data processing and imaging. We developed a high-resolution Radon transform algorithm and used it to predict receiver ghosts from VDS data. The receiver ghost reflections are subtracted and removed from the raw data. We propose a forward Radon transform operator of VDS data in the frequency domain and, based on the ray paths of the receiver ghosts, we propose an inverse Radon transform operator. We apply the proposed methodology to model and field data with good results. We use matching and subtracting modules of commercially available seismic data processing software to remove the receiver ghosts. The frequency notches are compensated and the effective frequency bandwidth of the seismic data broadens.

Partial frequency band match filtering based on high-sensitivity data: method and applications

During seismic data acquisition, a high-sensitivity geophone with a high inherent frequency can increase high frequency energy by suppressing low frequency signals. This could cause a worse response at low frequencies. If the advantages of high-sensitivity data and conventional data are combined, the effective bandwidth will be broadened. Considering this, we propose a partial frequency band match filtering method which can combine the advantages of both high frequency and conventional frequency ranges. By introducing Ricker wavelets with different dominant frequencies and amplitudes, we established a theoretical model which possesses characteristics of both types of seismic data and demonstrates the feasibility of the partial frequency band match filtering method. A test using single shot records shows the effectiveness of this method for widening the effective frequency band.

A distributed on-demand bandwidth-constrained multicast routing protocol for wireless ad hoc networks

To meet the bandwidth requirement for the multicasting data flow in ad hoc networks, a distributed on- demand bandwidth-constrained multicast routing （BCMR） protocol for wireless ad hoc networks is proposed. With this protocol, the resource reservation table of each node will record the bandwidth requirements of data flows, which access itself, its neighbor nodes and hidden nodes, and every node calculates the remaining available bandwidth by deducting the bandwidth reserved in the resource reservation table from the total available bandwidth of the node. Moreover, the BCMR searches in a distributed manner for the paths with the shortest delay conditioned by the bandwidth constraint. Simulation results demonstrate the good performance of BCMR in terms of packet delivery reliability and the delay. BCMR can meet the requirements of real time communication and can be used in the multicast applications with low mobility in wireless ad hoc networks.

A High Purity Integer-N Frequency Synthesizer in 0.35μm SiGe BiCMOS

An integer-N frequency synthesizer in 0.35μm SiGe BiCMOS is presented. By implementing different building blocks with different types of devices,a high purity frequency synthesizer with excellent spur and phase noise performance has been realized. All the building blocks are implemented with differential topology except for the off-chip loop filter. To further reduce the phase noise,bonding wires are used to form the resonator in the LC-VCO. The frequency synthesizer operates from 2.39 to 2.72GHz with output power of about 0dBm. The measured closed-loop phase noise is - 95dBc/Hz at 100kHz offset and - 116dBc/Hz at 1MHz offset from the carrier. The power level of the reference spur is less than - 72dBc. With a 3V power supply, the whole chip including the output buffers consumes 60mA.