Weak Excitation Research Articles

Single-photon scattering on a qubit: Space-time structure of the scattered field

We study the space-time structure of the scattered field induced by the scattering of a narrow single-photon Gaussian pulse on a qubit embedded in a one-dimensional open waveguide. For weak excitation power we obtain explicit analytical expressions for the space and time dependence of reflected and transmitted fields which are, in general, different from plane traveling waves. The scattered field consists of two parts: a damping part which represents spontaneous decay of the excited qubit and a coherent, lossless part. We show that for a large distance $x$ from the qubit and at times $t$ long after the scattering event our theory provides the result which is well known from stationary photon transport. However, the approach to the stationary limit is very slow. The scattered field decreases as the inverse powers of $x$ and $t$ as both the distance from the qubit and the time after the interaction increase.

Harvesting weak vibration energy by amplified inertial force and multi-stable buckling piezoelectric structure

One of the main challenges in vibration energy harvesting is to improve the efficiency for low-frequency and weak ambient vibration. A desired harvester should own a broadband working frequency and large-amplitude under weak excitation. In this paper, a novel harvester is proposed, which can enhance the energy harvesting performance for weak ambient vibration by amplified inertial force and multi-stability. This harvester is constituted of an inertial mass, two piezoelectric buckled beams and two linkages. Under external excitation, the inertial force produced by inertial mass is amplified and acts on the piezoelectric buckling beams via linkages, by which the amplified inertial force can drive the piezoelectric buckling beams to execute inter-well oscillation densely and generate high output power over a broadband frequency. Furthermore, the harvester possesses a super-harmonic vibration characteristic and can realize the frequency up-conversion effect, so the low-frequency excitation can excite the high-frequency vibration of piezoelectric beam and increase the output. The influence of the beam’s buckling level is studied through potential energy analysis. The output performance and nonlinear dynamic characteristics are studied under different types of excitations, i.e., the frequency sweeping, harmonic and random excitations. The validation experiment was carried out. The results prove that the harvester owns the super-harmonic characteristic and can execute snap-through motion under weak random excitation. Thus it can produce a larger output for weak excitation.

Inertial and kinematic interactions of bridge‐pile group subjected to liquefaction induced lateral spreading: Large‐scale shaking table experiments

AbstractThis paper investigates the seismic bridge‐pile‐soil system failure mechanisms due to liquefaction‐induced lateral spreading. Two large‐scale shaking table tests were performed on pile groups with and without bridges in sloped liquefiable soils overlain by soil crust. The systems were subjected to a weak earthquake signal (Tabas 0.05 g) and a strong earthquake signal (Tabas 0.3 g). Their responses were recorded in terms of excess pore pressure, acceleration, and displacement time histories. The piles seismic failure mode and mechanism are described based on the obtained results. In addition, the inertial and kinematic interaction effects on the piles’ deflection were evaluated. The results demonstrated that the bridge had no significant effect on the seismic response of the pile‐soil system under weak earthquakes. Meanwhile, the test model without a bridge experienced more significant soil lateral displacement, and the saturated sand exhibited dilatant behavior, and amplified the acceleration peak response during the strong earthquake. Moreover, the liquefaction‐induced lateral spreading moved the vulnerable position of the pile group bridge system from the pier bottom to the pile head, which changed the failure mode of the pile head. The results also revealed that, compared with weak earthquake excitation, the kinematic effect was significantly enhanced, and the inertia effect was weakened during strong earthquakes. Moreover, the pile curvature during both weak and strong earthquakes was inversely proportional to the bridge inertial load.

High-Sensitivity Visualization of Ultrafast Carrier Diffusion by Wide-Field Holographic Microscopy

Ultrafast transient microscopy is a key tool to study the photophysical properties of materials in space and time, but current implementations are limited to ≈1-μm fields of view, offering no statistical information for heterogeneous samples. Recently, we demonstrated wide-field transient imaging based on multiplexed off-axis holography. Here, we perform ultrafast microscopy in parallel around a hundred diffraction-limited excitation spots over a ≈60-μm field of view, which not only automatically samples the photophysical heterogeneity of the sample over a large area but can also be used to obtain a 10-fold increase in signal-to-noise ratio by computing an average spot. We apply our microscope to study the carrier diffusion processes in methylammonium lead bromide perovskites. We observe strong diffusion due to the presence of hot carriers during the first picosecond and slower diffusion afterward. We also describe how many-body kinetics can be misleadingly interpreted as strong diffusion at high excitation densities, while at weak excitation, real diffusion is observed. Therefore, the vast increase in sensitivity offered by this technique benefits the study of carrier transport not only by reducing data acquisition times but also by enabling the measurement of the much smaller signals generated at low carrier densities.

Expanding the color palette of bicolor-emitting nanocrystals.

Owing to their bright and tunable luminescence spectra, nanocrystals appear as a unique playground for light source design. Displays and lighting require white light sources that combine several narrow lines. As Kasha's rule prevents the emission of hot carriers, blends of multiple nanocrystal populations are currently the obvious strategy for broad-band source design. However, a few reports suggest that bicolor emission can also be obtained from a single particle even under weak excitation if a careful design of the exciton scattering mechanism sufficiently slows down its relaxation pathways. A key challenge remains to maintain quantum confinement for color tunability in the same structure, while simultaneously achieving a large size to leverage the critical, slower exciton diffusion or relaxation down to the ground state. Herein, we demonstrate that 2D nanoplatelets offer an original opportunity for the design of confined and large heterostructures. We demonstrate that bicolor emission is not limited to green-red pair and show that blue-yellow and purple-green emissions can be obtained from CdSe/CdTe/CdSe core/crown/crown and CdSe/CdS core/crown heterostructures, respectively.

Linearized frequency domain Landau-Lifshitz-Gilbert equation formulation

We present a general finite element linearized Landau-Lifshitz-Gilbert equation (LLGE) solver for magnetic systems under weak time-harmonic excitation field. The linearized LLGE is obtained by assuming a small deviation around the equilibrium state of the magnetic system. Inserting such expansion into LLGE and keeping only first order terms gives the linearized LLGE, which gives a frequency domain solution for the complex magnetization amplitudes under an external time-harmonic applied field of a given frequency. We solve the linear system with an iterative solver using generalized minimal residual method. We construct a preconditioner matrix to effectively solve the linear system. The validity, effectiveness, speed, and scalability of the linear solver are demonstrated via numerical examples.

Attitude Estimation from Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design

The paper addresses the problem of attitude estimation for rigid bodies using (possibly time-varying) vector measurements, for which we provide a necessary and sufficient condition of distinguishability. Such a condition is shown to be strictly weaker than those previously used for attitude observer design. Thereafter, we show that even for the single vector case the resulting condition is sufficient to design almost globally convergent attitude observers, and an explicit design is obtained. To overcome the weak excitation issue, the design makes full use of historical information. Simulation results illustrate the accurate estimation despite with noisy measurements.

Near-infrared light responsive intensified multiphoton ultraviolet upconversion in nanostructures towards efficient reactive oxygen species generation.

Near-infrared-to-ultraviolet (NIR-to-UV) multiphoton upconversion has recently received increasing attention owing to its promising frontier applications in the fields of biomedicine and nanophotonics. However, the realization of high-efficiency NIR-to-UV upconversion remains a dispiriting challenge due to weak excitation light harvesting and photo-conversion efficiency. Herein, we propose a mechanistic strategy to achieve intensified UV upconversion by manipulating the injected excitation energy flux. A simple LiYbF4:Tm@LiYF4 host-sensitized sublattice core-shell nanostructure was initially proposed to compete with the concentration quenching effect and increase energy transfer efficiency. Then, the organic dye ICG was further coated to introduce the antenna sensitization effect to highly increase the absorption ability of nanocrystals. After optimizing the ICG number loaded on the surface and separation distance, up to 167-fold UV upconversion emission enhancement was achieved under low-power excitation of 808 nm. More importantly, the efficient UV upconversion exhibits enhanced reactive oxygen species (ROS) generation activity by fabricating a TiO2-modified upconversion nanocomposite, revealing great application potential in frontier fields such as in vivo photodynamic therapy and bioimaging-guided therapeutics. Our results can provide versatile designs to achieve efficient UV upconversion, overcome conventional limitations, and offer exciting opportunities for potential applications in biomedical fields.

Increase output of vibration energy harvester by a different piezoelectric mode and branch structure design

In this study, we improve the performance of vibration energy harvesting by adopting a different working mode of piezoelectric material. We propose a harvester that is composed of an inverted beam and a branch structure. The branch can produce an amplified inertial force under vibration and passes it to a lead zirconate titanate (PZT) sheet. The resultant force acts on the PZT sheet as a dynamic normal force, not as a dynamic flexural one in the classical harvester. This change can increase the output significantly. First, the theoretical model is established and solved. The results show that the design can induce a super-harmonic vibration and produce a large output. Then, the validation experiments are carried out. The experimental results prove the occurrence of super-harmonic vibration and show that under weak stochastic excitation the branch structure can promote the electric output significantly. For a stochastic excitation of PSD = 0.06 g2 Hz−1, the average power of the novel harvester can reach 0.344 mW by a small PZT sheet with the dimensions of . This study may provide a novel scheme in improving the vibration energy harvesting efficiency.

A near-zero energy system based on a kinetic energy harvester for smart ranch.

Smart ranch relying on sensor systems to realize monitoring of animals and the environment has emerged with the promotion of the Internet of Things (IoT). This paper proposes a near-zero energy system (NZES) based on a kinetic energy harvester (KEH) for smart ranch. The KEH is based on motion enhancement mechanism (MEM) for kinetic energy recovery from animal movement to realize self-powered applications of smart ranch. The MEM realizes the input and enhancement of weak kinetic energy based on bistable inertial swing. The KEH is analyzed theoretically and experimentally based on cattle leg movement. Under weak excitation (low-frequency and amplitude swing), the maximum voltage growth rate of the KEH based on the MEM reaches 103.7% compared with the linear KEH. The results of application feasibility tests, dressing field experiments, and application outlook show that the KEH has the potential to realize self-powered applications in the NZES of smart ranch.

Research on Quantitative Detection of Wire Rope Damage Based on Weak Magnetic Excitation

Research on Quantitative Detection of Wire Rope Damage Based on Weak Magnetic Excitation

An adaptive observer for uncertain linear time-varying systems with unknown additive perturbations

In this paper we are interested in the problem of adaptive state observation of linear time-varying (LTV) systems where the system and the input matrices depend on unknown time-varying parameters. It is assumed that these parameters satisfy some known LTV dynamics, but with unknown initial conditions. Moreover, the state equation is perturbed by an additive signal generated from an exosystem with uncertain constant parameters. Our main contribution is to propose a globally convergent state observer that requires only a weak excitation assumption on the system, which is satisfied in the present context of regulation.

Harvesting weak vibration energy by amplified inertial force and super-harmonic vibration

To harvest vibration energy from a low-frequency and weak excitation, a rigid-elastic bi-stable harvester is proposed. This harvester is composed of an inertial mass, two linkages and two PZT beams. Under external excitation, the inertial force generated by the rigid mass can be amplified through the linkages and applied to the PZT beam, making it take a large deflection and even jump between the potential wells. To tailor the potential energy to an optimal one, the moving and fixed magnets are introduced. The repulsive force between them could elevate the bottom of potential wells and thus decrease the potential barrier, then the harvester could execute snap-through motion more easily. Furthermore, the harvester possesses a superharmonic characteristic. Under a low-frequency base excitation, the PZT beam can execute a super-harmonic vibration, this will increase the change times of stress of PZT material, thereby increasing the output power. The experiment results prove that the harvester could execute super-harmonic vibrations and snap-through motions under weak stochastic excitations. The large output could keep under weak excitations. At PSD = 0.01 g2/Hz, the average output power can reach 0.016 mW.

Key role of neuronal diversity in structured reservoir computing.

Chaotic time series have been captured by reservoir computing models composed of a recurrent neural network whose output weights are trained in a supervised manner. These models, however, are typically limited to randomly connected networks of homogeneous units. Here, we propose a new class of structured reservoir models that incorporates a diversity of cell types and their known connections. In a first version of the model, the reservoir was composed of mean-rate units separated into pyramidal, parvalbumin, and somatostatin cells. Stability analysis of this model revealed two distinct dynamical regimes, namely, (i) an inhibition-stabilized network (ISN) where strong recurrent excitation is balanced by strong inhibition and (ii) a non-ISN network with weak excitation. These results were extended to a leaky integrate-and-fire model that captured different cell types along with their network architecture. ISN and non-ISN reservoir networks were trained to relay and generate a chaotic Lorenz attractor. Despite their increased performance, ISN networks operate in a regime of activity near the limits of stability where external perturbations yield a rapid divergence in output. The proposed framework of structured reservoir computing opens avenues for exploring how neural microcircuits can balance performance and stability when representing time series through distinct dynamical regimes.

Adaptive state observation of linear time‐varying systems with delayed measurements and unknown parameters

AbstractIn this article, we address the problem of adaptive state observation of linear time‐varying systems with delayed measurements and unknown parameters. Our new developments extend the results reported in our recently works. The case with known parameters has been studied by many researchers. However in this article we show that the generalized parameter estimation‐based observer design provides a very simple solution for the unknown parameter case. Moreover, when this observer design technique is combined with the dynamic regressor extension and mixing estimation procedure the estimated state and parameters converge in fixed‐time imposing extremely weak excitation assumptions.

Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements

SummaryThis article considers the identification problems of nonlinear systems with scarce measurements by using the instrumental variable technique. When the product of the instrumental matrix and the information matrix is a nonsingular matrix and the weak persistent excitation condition about the instrumental vector is true, the obtained parameter estimates can be unbiased consistent estimates. The key is how to choose the instrumental variables. Difficulty arises in that the system outputs are unavailable. By applying the negative gradient search, a recursive instrumental variable‐based gradient algorithm is derived to estimate the parameters of the nonlinear systems with missing observed data. Moreover, the multi‐innovation identification theory is introduced to further improve the parameter estimation accuracy. The simulation results illustrate that the proposed methods are effective.

(Invited, Digital Presentation) Photocurrent Detection of Cooperative Exciton Quantum Interference in Nanocrystal Thin Films

Colloidal semiconductor quantum dots (QDs) are excellent materials for studying the photophysics of exciton complexes such as biexcitons, triexcitons, and charged excitons (trions). Dynamics of exciton complexes usually determines the performance of optoelectronic devices [1]. For example, trions reduce the optical gain threshold in QD lasers and multiexcitons increase photon-to-current conversion efficiencies via carrier multiplication processes in QD solar cells. In addition, unconventional properties of multiexcitons emerge in coherent processes in QD systems. We recently discovered the high-frequency coherent oscillations with integer multiples of the exciton resonance frequency, which is called multiexciton harmonic quantum coherence [2,3]. The multiexciton coherent properties have been investigated using optical methods. However, to clarify their roles in optoelectronic devices, it is necessary to conduct the electrical detection of multiexciton coherence.Here, we performed photocurrent detection of exciton quantum interference signals in QD thin films. The samples used in this study were closely packed PbS QD thin films. The QD films were sandwiched between the electron and hole transport layers to extract photogenerated carriers. Multiexcitons were generated by phase-locked femtosecond laser pulses, and then their photocurrent quantum interference signals were measured by using a quantum interference technique [4]. The photocurrent interference signal in the weak excitation shows a single sinusoidal oscillation originating from single excitons, while the interference signal changes to the profile involving multiple sinusoidal oscillations with increasing excitation intensity. This means that the multiexciton quantum coherence exhibiting harmonic oscillations is successfully detected in a photocurrent technique [5]. Furthermore, the amplitudes of harmonic quantum coherent signals in coupled QDs are significantly larger than those in isolated QDs. We clarified that the enhancement of the amplitudes is caused by cooperative processes in coupled QDs, where excitons in adjacent QDs interact with each other through their inter-QD coherent coupling. This cooperative effect can provide a new way to use inter-QD coherent coupling in advanced optoelectronic applications, e.g., amplifiers of coherent signals.Part of this work was supported by JSPS KAKENHI (JP19H05465 and JP22H01990) and JST CREST (JPMJCR21B4).

Logarithmic Observation of Feature Depth for Image-Based Visual Servoing

Due to the robustness to robot modeling and camera calibration errors and avoidance of complete target geometry, image-based visual servoing has always been an important topic in the fields such as robotics, computer vision and so forth. When the image information obtained by the camera is mapped to the robotic task space to design the servoing control law, the resulting interaction matrix, which links the spatial velocity of the camera to the temporal variation of the selected image features, depends on the unknown feature depths. The use of inaccurate feature depths may influence the stability and robustness of the controller, and even cause the failure of the task. In this article, based on the perspective camera model, by employing the principle of reduced order observer, a novel logarithmic observer is presented for on-line recovery of feature depth. Compared with the typical observers now available, the presented observer offers several advantages: global convergence, a faster convergence rate of error structure than exponential error structure, a less restricted observability condition and greater robustness against measurements with noise. The comparison results of numerical simulations indicate the superiority of the presented observer, and real experiments with Kinect v2 sensor further validate the effectiveness of the presented observer in practical situation. Note to Practitioners—This article was motivated by the depth problem in the image-based visual servoing scheme, but it can also be used in other situations where the image depth information is needed, such as 3D reconstruction, robot navigation, etc. The existing depth acquisition methods include TOF sensors, stereo vision, depth observers and so on. However, TOF sensors are sensitive to light conditions, and the mounting space of stereo vision is slightly large, and there is contradiction between observation performance and computational complexity in most existing observers. In this article, a novel structure of logarithmic reduced order observer is described in detail, which can be utilized to estimate the depth information of images easily. The simulations and experiments verify the good performance of the observer. The limitations of the given observer are that the estimation accuracy is not very good under weak excitation, and the camera needs to be calibrated in advance. Future work will focus on overcoming these two limitations.

Accelerated convergence with improved robustness for discrete-time parameter estimation

The dynamic regressor extension and mixing (DREM) method provides a fixed-time converging parameter estimator for a persistently excited regressor under bounded measurement noises. This note aims to develop this approach for cases with weaker excitation and regressor constraints. Several nonlinear estimation schemes with fixed-time convergence rates and improved measurement noise robustness properties are proposed here.

Application of a convolutional neural network in wire rope magnetic memory testing

In this paper, a magnetic memory detection device under weak magnetic field excitation is designed to better solve the problem of weak magnetic memory detection signals and susceptibility to other factors. In order to reduce the noise in the original signal, a noise reduction method combining local mean decomposition and wavelet transform (LMDW) is proposed. Pseudo-colour transformation is used to enhance the greyscale image after cubic spline interpolation. Finally, a convolutional neural network (CNN) is designed to identify broken wire. Moreover, compared with the support vector machine (SVM) algorithm, the recognition rate of the CNN is 35.8% higher than that of the SVM under the condition that the allowable error is 0. The experimental results show that the system has high detection sensitivity and remains effective for small defects. The filtering algorithm has a better effect on noise removal and improves the signal-to-noise ratio (SNR). The CNN has good recognition ability to identify defects.