Quantization Effects Research Articles

Topological dipole insulator

We expand the concept of two-dimensional topological insulators to encompass a novel category known as topological dipole insulators (TDIs), characterized by conserved dipole moments along the xx-direction in addition to charge conservation. By generalizing Laughlin’s flux insertion argument, we prove a no-go theorem and predict possible edge patterns and anomalies in a TDI with both charge U^e(1)Ue(1) and dipole U^d(1)Ud(1) symmetries. The edge of a TDI is characterized as a quadrupolar channel that displays a dipole U^d(1)Ud(1) anomaly. A quantized amount of dipole gets transferred between the edges under the dipolar flux insertion, manifesting as ‘quantized quadrupolar Hall effect’ in TDIs. A microscopic coupled-wire Hamiltonian realizing the TDI is constructed by introducing a mutually commuting pair-hopping terms between wires to gap out all the bulk modes while preserving the dipole moment. The effective action at the quadrupolar edge can be derived from the wire model, with the corresponding bulk dipolar Chern-Simons response theory delineating the topological electromagnetic response in TDIs. Finally, we enrich our exploration of topological dipole insulators to the spinful case and construct a dipolar version of the quantum spin Hall effect, whose boundary evidences a mixed anomaly between spin and dipole symmetry. Effective bulk and the edge action for the dipolar quantum spin Hall insulator are constructed as well.

Intermediate state between steady and breathing solitons in fiber lasers

Ultrafast fiber laser, a vital tool in both science and industry, exhibits two distinct pulse states: the steady soliton (SS) and the breathing soliton (BS). While these states have been extensively studied individually, understanding the complex transition between them is crucial for controlling lasing states effectively. Herein, our experimental observations reveal an intermediate state that toggles between SS and BS, enabled by the dispersive Fourier transform technique. We find that energy hop and decaying breathing processes, driven respectively by the energy quantization effect and Q-switched modulation, govern this transition. Additionally, we observe that the transition between different BS states primarily involves a pure decaying breathing process. Numerical simulations are used to generate similar transition dynamics in a model that combines equations describing the population inversion in a mode-locked laser. This study sheds light on the transition dynamics in non-equilibrium systems, offering insights for intelligently manipulating lasing states.

Quantized feedback stabilization of impulsive switched linear systems based on event triggering

AbstractThis article studies the feedback stabilization problem of an impulsive switched linear system whose feedback loop is closed over a digital network. Particularly, the combined effects of mode switches, impulses, quantization, network delay and external disturbances on the stability of that system are investigated. By extending the previous delay‐free and impulse‐free methods of reachable‐set approximation and propagation, some novel communication and control policies are designed to stabilize the concerned switched system with both network delay and impulses. In order to save the occupied network bandwidth, some event‐triggered control policies are proposed. To handle the effects of the mode switches and the impulse, we design event‐triggering conditions for both the case with no switch and no impulse on an inter‐event interval and the case with one switch or one impulse on an inter‐event interval. Note that the occurrence of a mode switch or an impulse leads to the switch of the event‐triggering conditions. Under the event‐triggered control policies, a stabilizing bit rate condition is derived. It is proven that even under impulses and network delay, the event‐triggered control policies can stabilize the switched system at a lower bit rate than earlier works based on conventional time‐triggered control policies.

Effects of Phase Shifter Quantization on Secret Millimeter-Wave Communication Systems With Phased-Array Antennas

Effects of Phase Shifter Quantization on Secret Millimeter-Wave Communication Systems With Phased-Array Antennas

First Hitting Times on a Quantum Computer: Tracking vs. Local Monitoring, Topological Effects, and Dark States.

We investigate a quantum walk on a ring represented by a directed triangle graph with complex edge weights and monitored at a constant rate until the quantum walker is detected. To this end, the first hitting time statistics are recorded using unitary dynamics interspersed stroboscopically by measurements, which are implemented on IBM quantum computers with a midcircuit readout option. Unlike classical hitting times, the statistical aspect of the problem depends on the way we construct the measured path, an effect that we quantify experimentally. First, we experimentally verify the theoretical prediction that the mean return time to a target state is quantized, with abrupt discontinuities found for specific sampling times and other control parameters, which has a well-known topological interpretation. Second, depending on the initial state, system parameters, and measurement protocol, the detection probability can be less than one or even zero, which is related to dark-state physics. Both return-time quantization and the appearance of the dark states are related to degeneracies in the eigenvalues of the unitary time evolution operator. We conclude that, for the IBM quantum computer under study, the first hitting times of monitored quantum walks are resilient to noise. However, a finite number of measurements leads to broadening effects, which modify the topological quantization and chiral effects of the asymptotic theory with an infinite number of measurements.

Distributed adaptive moving horizon estimation for multi-sensor networks subject to quantization effects

This paper investigates the distributed state estimation problem for multi-sensor networks with quantized measurements. Within the Bayesian framework, a distributed adaptive moving horizon estimation algorithm is developed. Unlike the existing methods regarding quantized errors roughly as bounded uncertainties, the posterior distributions of the errors are demanded to be derived. To overcome the difficulty of evaluating the posterior distributions for series of the states and quantized errors jointly, the variational Bayesian methodology is adopted to approximate the true distributions. Based on the fixed-point iteration method, the update rules are analytically derived, with the convergence criterion provided. Furthermore, by incorporating the average consensus algorithm into the prediction process, all sensors can achieve consensus on their estimates in a distributed manner. Finally, a numerical example of target tracking under logarithmic and uniform quantization effects is given to illustrate the validity of the proposed algorithm.

Influence of Dimensional Quantization Effects on the Effective Mass of Major Charge Carriers in LED Heterostructures with InxGa1−xN/GaN Multiple Quantum Wells

By numerically solving the self-consistent system of the Schr¨odinger equations and Poisson electroneutrality, zone diagrams of LED heterostructures with InxGa1−xN/GaN multiple quantum wells have been calculated. The effect of electron–phonon interaction, nonparabolicity of the dispersion relation, and hybridization of the wave function on the values of the effective mass of major charge carriers in the InxGa1−xN/GaN quantum wells has been studied. The long-wave shift of 2D-plasmon resonances is associated with the temperature renormalization of the effective mass of two-dimensional carriers. To describe the temperature dependence of the effective mass, the function for the displacement of the 2D-plasmon resonance frequency is introduced.

Theory of Linear-Circular Dichroism in Monoatomic Layers of Transition Metal Dichalcogenides Taking into Account the Rabi Effect

We have developed a theory of dimensional quantization for nanostructures, both one-dimensional and zero-dimensional, constructed from monoatomic layers of transition metal dichalcogenides (TMDCs). This theory has enabled us to derive expressions for the energy spectra of charge carriers in both even and odd states (relative to coordinate inversion), as these states occur within quantum-confined lines and points of the TMDC monoatomic layers, dependent on their geometric dimensions. Our numerical analysis provides a detailed exploration of the quantum-confined energy states of electrons within these nanostructures, offering insights into their potential applications in advanced nanoelectronic devices. This work not only advances our understanding of the energy characteristics of TMDC monoatomic layers but also contributes to the broader field of material science by exploring the effects of dimensional quantization on electronic properties.

Dynamic Event-Triggered State Estimation for Power Harmonics With Quantization Effects: A Zonotopic Set-Membership Approach

Dynamic Event-Triggered State Estimation for Power Harmonics With Quantization Effects: A Zonotopic Set-Membership Approach

Categorical-Parallel Adversarial Defense for Perception Models on Single-Board Embedded Unmanned Vehicles

Significant advancements in robustness against input perturbations have been realized for deep neural networks (DNNs) through the application of adversarial training techniques. However, implementing these methods for perception tasks in unmanned vehicles, such as object detection and semantic segmentation, particularly on real-time single-board computing devices, encounters two primary challenges: the time-intensive nature of training large-scale models and performance degradation due to weight quantization in real-time deployments. To address these challenges, we propose Ca-PAT, an efficient and effective adversarial training framework designed to mitigate perturbations. Ca-PAT represents a novel approach by integrating quantization effects into adversarial defense strategies specifically for unmanned vehicle perception models on single-board computing platforms. Notably, Ca-PAT introduces an innovative categorical-parallel adversarial training mechanism for efficient defense in large-scale models, coupled with an alternate-direction optimization framework to minimize the adverse impacts of weight quantization. We conducted extensive experiments on various perception tasks using the Imagenet-te dataset and data collected from physical unmanned vehicle platforms. The results demonstrate that the Ca-PAT defense framework significantly outperforms state-of-the-art baselines, achieving substantial improvements in robustness across a range of perturbation scenarios.

Practically fast finite-time stability of stochastic constrained nonlinear systems with actuator dead zone

This article addresses the challenge of achieving practically fast finite-time stabilization for stochastic constrained nonlinear systems, which are subject to both quantization effects and actuator dead zones. To tackle these issues, adaptive parameterization and partial control strategies are introduced with the aim of efficiently approximating and counteracting nonlinear disturbances. This approach ensures the robust stabilization of the controlled system within a finite time frame, despite the presence of uncertainties. Additionally, a novel barrier function is propose that mitigates the constraints usually imposed by boundary functions, while also leveraging a fuzzy logic system to manage nonlinear terms adeptly. Building on these innovations, we formulate a new theorem dedicated to practically fast finite-time control mechanisms for stochastic nonlinear systems. The efficacy of our theoretical developments is substantiated through an illustrative example involving a current-controlled DC motor system, demonstrating the practical applicability and robustness of the proposed control scheme.

Landau quantization effects on damping Kawahara solitons in electron–positron–ion plasma in rotating ionized medium

For the dynamics of three-dimensional electron–positron–ion plasmas, a fluid quantum hydrodynamic model is proposed by considering Landau quantization effects in dense plasma. Ion–neutral collisions in the presence of the Coriolis force are also considered. The application of the reductive perturbation technique produces a wave evolution equation represented by a damped Korteweg–de Vries equation. This equation, however, is insufficient for describing waves in our system at very low dispersion coefficients. As a result, we considered the highest-order perturbation, which resulted in the damped Kawahara equation. The effects of the magnetic field, Landau quantization, the ratio of positron density to electron density, the ratio of positron density to ion density, and the direction cosine on linear dispersion laws as well as soliton and conoidal solutions of the damped Kawahara equation are explored. The understanding from this research can contribute to the broader field of astrophysics and aid in the interpretation of observational data from white dwarfs.

Distributed resilient adaptive consensus tracking control of nonlinear multi-agent systems dealing with deception attacks via K-filters approach

It poses technical difficulty to achieve distributed consensus tracking control with input quantizations and deception attacks for nonlinear multi-agent systems subject to mismatched parametric uncertainties via backstepping design. The underlying problem becomes even more complicated because i) the system contains mismatched uncertainties; ii) the output becomes unavailable after attacks, making the conventional recursive control design strategy using traditional error surfaces unsuitable; iii) since only the compromised output signal is available, the impacts of nonlinear items related to unknown attack weights become difficult to be explicitly addressed in the existing available output feedback control results. In this paper, we present a solution to circumvent these obstacles by constructing a set of new K-filters using compromised output only, which, together with a coordinate transformation involving the attacked output and filter variables, allow a new form of backstepping based distributed resilient adaptive control protocol to be developed. Meanwhile, an extra compensation term is incorporated into the real controller to handle the effect of quantization on the system stability. It is shown that, with proper choices of Lyapunov functions, the global uniform boundedness of all the closed-loop signals and the asymptotically output consensus tracking can be achieved. A practice example is provided to verify the benefits of our scheme.

Influence of Potentiostat Hardware on Electrochemical Measurements.

We describe two operating modes for the same potentiostat, where the redox processes of hydroquinone in a hydrochloric acid medium are contrasted for cyclic voltammetry (CV) as functions of a digital/staircase scan and an analogue/linear scan. Although superficially there is not much to separate the two modes of operation as an end user, differences can be seen in the voltammograms while switching between the digital and analogue modes. The effects of quantization clearly have some impact on the measurements, with the outputs between the two modes being a function of the equivalent-circuit model of the electrochemical system under investigation. Increasing scan rates when using both modes produces higher peak redox currents, with the differences between the analogue and digital modes of operation being consistent as a function of the scan rate. Differences between the CV loops between the analogue and digital modes show key differences at certain points along the scans, which can be attributed to the nature of the electrolyte affecting the charging and discharging processes and consequently changing the peak currents of the redox processes. The faradaic processes were shown to be independent of the scan rates. Simulations of the equivalent-circuit behaviour show differences in the responses to different input signals, i.e., the step and ramp responses of the system. Both the voltage and current steps and ramp responses showed the time-domain behaviour of distinct elements of the equivalent electrochemical circuit model as an approximation of the applied digital and analogue CV input signals. Ultimately, it was concluded that similar parameters between the two modes of operation available with the potentiostat would lead to different output voltammograms and, despite advances in technology, digital systems can never fully emulate a true analogue system for electrochemical applications. These observations showcase the value of having hardware capable of true analogue characteristics over digital systems.

Magnetron Sputter Deposition of Amorphous Silicon–SiO2 Quantized Nanolaminates

Quantization effects in nanolaminate structures of oxide materials are proposed and experimentally demonstrated only recently. Herein, the material combination of amorphous silicon and SiO2 deposited by magnetron sputtering is investigated and it is shown that the quantization effect can be observed indeed. Transmission electron microscopy characterization gives evidence of continuous layers of amorphous silicon and SiO2 with well‐defined interfaces. The deposition process is described and the tunability of the refractive index and the bandgap energy is demonstrated. By doing so, the advantages of this novel material over classical optical materials are shown and feasibility is proved. As an example, a longpass optical interference filter with edge at 720 nm is deposited using quantized nanolaminates as the high and SiO2 as the low refractive index material. This filter can be deposited successfully with close match to the design. It shows a blocking range throughout the visible spectrum whereas a comparable filter based on SiO2–TiO2 only blocks 500–700 nm.

Quantized control for interconnected PDE systems via mobile measurement and control strategies

This paper deals with the Rϵ-stabilization for interconnected partial differential equation systems (IPDESs) by mobile measurement and control strategies. First, compared to the static measurement and control strategies, the mobile ones are employed to improve the dynamic response of the closed-loop system, while reducing the number of sensors and actuators effectively. Moreover, considering the constrained transmission channel bandwidth, the hysteresis quantizer with an adjustable parameter is introduced to save the communication resources in the network, while can balance the quantization effect and the control performance by adjusting the parameter. Further, the output quantization controller is designed to ensure that the closed-loop system is Rϵ-stable, which converges to a given interval in finite time. Finally, a simulation example of chemical non-isothermal tubular reactors is provided to illustrate the validity of the presented design method.

Enhancement of CuO/Si Solar Cell Efficiency by Cu2O Doping Prepared Via Thermal Evaporation Technique

CuO:Cu2O/Si heterojunctions have been prepared with different concentrations of Cu2O nanoparticles using the thermal evaporation technique. The X-ray diffraction (XRD) results show that the prepared films are polycrystalline with orthorhombic structure and preferential orientation (110) direction along the [Formula: see text] axis at [Formula: see text], which corresponds to the pure CuO with crystallite size 18[Formula: see text]nm, while the particle size ranged from 14[Formula: see text]nm to 34 nm (resulted from SEM test). The optical properties were studied by recording the absorbance spectra using the UV–visible spectrophotometer. The absorbance increased with Cu2O doping. The high values of the energy gap refer to the quantization effect. The electrical properties including the Hall effect were studied. CuO:Cu2O/Si heterojunctions have been prepared at different concentrations. [Formula: see text]–[Formula: see text] characteristics show that the Cu2O doping increases the energy conversion efficiency by retarding the electron–hole recombination and the improved device performance is caused by the high short-circuit current ([Formula: see text] and open circuit voltage ([Formula: see text] and found that the highest efficiency ([Formula: see text] at doping 0.006 Cu2O 3.471% with [Formula: see text] of 2.20[Formula: see text]V, [Formula: see text] of 0.0170[Formula: see text]mA cm[Formula: see text] and F.F of 0.6497 at [Formula: see text][Formula: see text]mW/cm2.

First-principles calculation of monolayer PdSe2 with Se and Pd vacancy and its effect on quantum capacitance

Abstract The emergence of 2-D materials such as graphene has caught the attention of the scientific community. 2-D materials have a higher surface area per unit mass, which is ideal for electrodes. Another popular material among researchers is the monolayer palladium diselenide or PdSe2, a semiconductor with a tunable bandgap energy. Since there are fewer states in the fermi level of PdSe2, the quantization effect is more prevalent, hence, it would most likely draw its capacitance from its electronic configuration. In this study, the electronic properties such as band structure, density of states, and quantum capacitance of pristine monolayer PdSe2, PdSe2 with Se, and Pd vacancy were calculated based on density functional theory via Quantum Espresso. The formation energies of all systems were energetically favourable. The system with Se vacancy has the highest formation energy with a value of -3.47 eV. The density of states of all systems were observed to have a local minima at the fermi level. More occupiable states around the valence band were observed for the systems with vacancy. Bader charge analysis showed a notable decrease of charge in Se atoms near the Pd vacancy, while the Pd atoms in the Se vacated system showed stronger charge transfer between Pd and another Se atom. The quantum capacitance and surface charge values were calculated using the density of states. Higher surface charge values at the negative voltage were observed for the systems with induced vacancies. Based on the results, the systems with vacancies have improved the quantum capacitance and surface charge at the negative potential.

On the effect of clock offsets and quantization on learning-based adversarial games

In this work, we consider systems whose components suffer from clock offsets and quantization and study the effect of those on a reinforcement learning (RL) algorithm. Specifically, we consider an off-policy iterative RL algorithm for continuous-time systems, which uses input and state data to approximate the Nash-equilibrium of a zero-sum game. However, the data used by this algorithm are not consistent with one another, in that each of them originates from a slightly different time instant of the past, hence putting the convergence of the algorithm in question. We prove that, given that these timing inconsistencies remain below a certain threshold, the iterative off-policy RL algorithm will still converge epsilon-closely to the desired Nash policy. However, this result is conditional to a certain Lipschitz continuity and differentiability condition on the input-state data collected, which is indispensable in the presence of clock offsets. A similar result is also derived when quantization of the measured state is considered. Finally, unlike prior work, we provide a sufficiently rich data condition for the execution of the iterative RL algorithm, which can be verified a priori across all iteration indices. Simulations are performed, which verify and clarify theoretical findings.

Deep learning and quantization for accurate and efficient multi-target radar inference of moving targets

Real-time, radar-based human activity and target classification is useful for wide-area ground surveillance. However, the feasibility of deploying deep learning (DL) models in radar-based systems with limited computational resources remains unexplored. This paper investigated the effect of quantization on model throughput and accuracy for deployment in radar systems. A seven-layer residual network was proposed to classify ground-moving targets and achieved a test accuracy of 87.72%. The model was then quantized to 16-bit and 8-bit precision, resulting in a 3.8 times speedup in inference throughput, with less than a 0.4% drop in test and validation accuracy. The results showed that quantization can improve inference throughput with a negligible decrease in target classification accuracy. The increase in throughput and reduction in computational expense that comes with quantization promotes the feasibility of the deployment of DL models in systems with limited computational resources. The findings of this paper hold significant promise for the successful use of quantized models in modern radar systems, while adhering to stringent size, weight and power consumption constraints.