基于时间透镜原理实现微波信号时间反演

时间反演电磁学是一门新兴学科. 高效的电磁时间反演信号获取方式是时间反演技术获得应用的关键. 本文研究了一种基于时域成像原理获得时间反演微波信号的方法. 首先根据时间透镜原理, 推导出了实现波形时间反演的条件, 并对波形反演的过程进行了数值仿真. 然后设计了两种满足反演条件的啁啾电磁带隙结构来构造色散信道, 并通过实验得到了一个时隙长度为1.5 ns的时间反演信号. 由于啁啾电磁带隙结构与理想色散信道的差异, 实验结果中存在波形失真. 文章最后对造成失真的原因进行了分析.     

Unstable combustion induced by oblique shock waves at the non-attaching condition of the oblique detonation wave

The instability of oblique shock wave (OSW) induced combustion is examined for a wedge with a flow turning angle greater than the maximum attach angle of the oblique detonation wave (ODW), where archival results rarely exist for this case in previous literatures. Numerical simulations were carried out for wedges of different length scales to account for the ratio of the chemical and fluid dynamic time scales. The results reveal three different regimes of combustion. (1) No ignition or decoupled combustion was observed if a fluid dynamic time is shorter than a chemical time behind an OSW. (2) Oscillatory combustion was observed behind an OSW if a fluid dynamic time is longer than a chemical time behind an OSW and the fluid dynamic time is shorter than the chemical time behind a normal shock wave (NSW) at the same Mach number. (3) Detached bow shock-induced combustion (or detached overdriven detonation wave) was observed if a fluid dynamic time is longer than a chemical time behind a NSW. Since no ignition or decoupled combustion occurs as a very slow reaction and the detached wave occurs as an infinitely fast reaction, the finite rate chemistry is considered to be the key for the oscillating combustion induced by an OSW over a wedge of a finite length with a flow turning angle greater than the maximum attach angle for an ODW. Since this case has not been previously reported, grid independency was tested intensively to account for the interaction between the shock and reaction waves and to determine the critical time scale where the oscillating combustion can be observed.     

Stopping time of a one-dimensional bounded quantum walk

The stopping time of a one-dimensional bounded classical random walk(RW) is defined as the number of steps taken by a random walker to arrive at a fixed boundary for the first time.A quantum walk(QW) is a non-trivial generalization of RW,and has attracted a great deal of interest from researchers working in quantum physics and quantum information.In this paper,we develop a method to calculate the stopping time for a one-dimensional QW.Using our method,we further compare the properties of stopping time for QW and RW.We find that the mean value of the stopping time is the same for both of these problems.However,for short times,the probability for a walker performing a QW to arrive at the boundary is larger than that for a RW.This means that,although the mean stopping time of a quantum and classical walker are the same,the quantum walker has a greater probability of arriving at the boundary earlier than the classical walker.     

Slow-time acceleration for modeling multiple-time-scale problems

The numerical simulation of a system exhibiting a broad range of time scales can be very expensive because the time discretization will in general need to resolve the smallest time scale, and the simulation will have to extend over many times the longest time scale. However, it is common that not all the time scales are of interest for a particular problem. When the long time scales are of primary interest, a number of techniques are available to eliminate the unwanted short time scales from consideration. When the short time scales are of primary interest, a technique for mitigating the consequences of anomalously long time scales is needed. The “slow-time acceleration” technique presented here has been developed to address this problem. In the slow-time acceleration technique, a modified evolution equation is developed in which the longest time scale is much shorter than that of the original system, and which has the same multi-time scale asymptotic structure as the original system. As an example, this approach is applied to the numerical simulation of solid-propellant rockets in which the long time scale is associated with the regression of the burning propellant.     

Multistop analyzer for time-of-flight measurements at a resolution of ±5 ns

A multichannel multistop time analyzer that provides the measurement of the time intervals between start and stop pulses and the accumulation of their time distribution in the memory of its unit is described. The time of arrival of a stop signal is recorded at a resolution of ±5 ns and a dead time of 30 ns. The number of stops per start can achieve 6000. The number of channels is 131072 (2¹⁷). The time analyzer is based on a CAMAC unit and can be used to design measurement-information systems for solving problems in neutron spectrometry and mass spectrometry by time-of-flight methods and for studying the time characteristics of luminescence radiation.     

Variations on a theme by Mark Kac

Mark Kac's theorem on the mean recurrence time in a stationary stochastic process in discrete time with discrete states is taken as the starting point for a series of variations, most of which are formulated in terms of 0–1 processes. Whereas the original theorem deals with the mean recurrence time of a given state under the condition that the state is realized at time 0, this condition is dropped in part of the variations; two others refer to the variance of the recurrence time and two to the Poincaré cycle of a dynamical system. Most variations consist in inequalities and formal identities for the mean first-arrival time and subsequent recurrence times for the given state.     

Transmission time of a particle in the reflectionless Sech-squared potential: Quantum clock approach

We investigate the time for a particle to pass through the reflectionless Sech-squared potential. Using the Salecker-Wigner and Peres quantum clock an average transmission time of a Gaussian wave packet representing the particle is explicitly evaluated in terms of average momentum and travel distance. The average transmission time is shown to be shorter than the time of free-particle motion and very close to the classical time for wave packets with well-localized momentum states. Since the clock measures the duration of scattering process the average transmission time can be interpreted as the average dwell time.     

On the Boil-Off Time of Probe Surfaces in Plasmas

The time required for the melting of the surface of a glass-insulated probe inserted in a plasma is computed including the influence of plasma mass motion. This effect is relevant for probe measurements in moving current sheaths of electrical gas discharges. For dense plasma focus experiments, it is shown that the time of formation of a transition layer of evaporated material is shorter than the ion relaxation time in the plasma and the transit time of the current sheath by the probe position.     

Unconditionally convergent nonlinear solver for hyperbolic conservation laws with S-shaped flux functions

This paper addresses the convergence properties of implicit numerical solution algorithms for nonlinear hyperbolic transport problems. It is shown that the Newton–Raphson (NR) method converges for any time step size, if the flux function is convex, concave, or linear, which is, in general, the case for CFD problems. In some problems, e.g., multiphase flow in porous media, the nonlinear flux function is S-shaped (not uniformly convex or concave); as a result, a standard NR iteration can diverge for large time steps, even if an implicit discretization scheme is used to solve the nonlinear system of equations. In practice, when such convergence difficulties are encountered, the current time step is cut, previous iterations are discarded, a smaller time step size is tried, and the NR process is repeated. The criteria for time step cutting and selection are usually based on heuristics that limit the allowable change in the solution over a time step and/or NR iteration. Here, we propose a simple modification to the NR iteration scheme for conservation laws with S-shaped flux functions that converges for any time step size. The new scheme allows one to choose the time step size based on accuracy consideration only without worrying about the convergence behavior of the nonlinear solver. The proposed method can be implemented in an existing simulator, e.g., for CO₂ sequestration or reservoir flow modeling, quite easily. The numerical analysis is confirmed with simulation studies using various test cases of nonlinear multiphase transport in porous media. The analysis and numerical experiments demonstrate that the modified scheme allows for the use of arbitrarily large time steps for this class of problems.     

Estimation of entropies and dimensions by nonlinear symbolic time series analysis

Symbolic nonlinear time series analysis methods have the potential for analyzing nonlinear data efficiently with low sensitivity to noise. In symbolic nonlinear time series analysis a time series for a fixed delay is partitioned into a small number (called the alphabet size) of cells labeled by symbols, creating a symbolic time series. Symbolic methods involve computing the statistics of words made from the symbolic time series. Specifically, the Shannon entropy of the distribution of possible words for a range of word lengths is computed. The rate of increase of the entropy with word length is the metric (Kolmogorov-Sinai) entropy. Methods of computing the metric entropy for flows as well as for maps are shown. A method of computing the information dimension appropriate to symbolic analysis is proposed. In terms of this formulation, the information dimension is determined by the scaling of entropy as alphabet size is modestly increased, using the information obtained from large word length. We discuss the role of sampling time and the issue of using these methods when there may be no generating partition.     

耦合时间精度对模拟飞行器自由运动特性的影响

将亚迭代技术引入流体动力学和刚体动力学方程的耦合求解,获得细长三角翼极限环运动的规律.探讨耦合时间精度对飞行器非定常运动特性的影响,细长三角冀的大迎角自由滚运动最终形成极限环振荡的周期性自维持运动,不同攻角自由滚振幅阶跃式的变化特点较好地吻合了自由滚试验的规律.对于多系统耦合问题,亚迭代耦合求解(耦合时间精度为二阶)对物理时间步长的依赖性不明显;而存在一阶时间滞后的解耦推进方法的数值结果强烈地依赖于物理时间步长选取,稍大的时间步长将导致非物理的数值结果.     

Improved free space optical communications performance by using time diversity

A laser beam propagating through turbulence experiences random amplitude and phase fluctuations, which can severely degrade the performance of free space optical communication systems. It this letter, time diversity is demonstrated as a technique which can decrease turbulence influence. Statistically, laser propagation along an atmospheric path is uncorrelated with an earlier-time path for a time interval greater than the atmospheric turbulence correlation time. To estimate time diversity system performance, a 2.2-km optical link is set up for comparing the fade probability of a system using time diversity with a system not using time diversity. The experimental results obtained under different turbulence conditions are shown which are in good agreement with the theory.     

Multiscale reconstruction of time series

A new method is proposed which allows a reconstruction of time series based on higher order multiscale statistics given by a hierarchical process. This method is able to model the time series not only on a specific scale but for a range of scales. It is possible to generate complete new time series, or to model the next steps for a given sequence of data. The method itself is based on the joint probability density which can be extracted directly from given data, thus no estimation of parameters is necessary. The results of this approach are shown for a real world dataset, namely for turbulence. The unconditional and conditional probability densities of the original and reconstructed time series are compared and the ability to reproduce both is demonstrated. Therefore in the case of Markov properties the method proposed here is able to generate artificial time series with correct n-point statistics.     

Time-dependent Benioff strain release diagrams

New time-dependent Benioff strain (TDBS) release diagrams were analyzed for acoustic emission during various loading tests and for electromagnetic (EM) radiation emanating during compression and, tension, which end in failure. TDBS diagrams are Benioff diagrams that are built consecutively, each time using a greater number of events (acoustic or EM emissions) using the last event as if it were associated with the ‘actual failure’. An examination of such TDBS diagrams shows that at a certain time point (this time point is denoted by the term ‘alarm’ time), a comparatively short interval prior to actual collapse, their decreasing part is broken by a positive ‘bulge’. This ‘bulge’ is quantified and an algorithm proposed for its assessment. Using the alarm time and other parameters of the failure process (fall, bulge size and escalation factors, bulge slope and slope fall time), a criterion for estimating the time of the actual collapse is developed and shown to agree well with laboratory experimental results.     

Changing spectrum estimation

An autoregressive (AR) model with time varying coefficients is used for the modeling of non-stationary covariance time series. A stochastically perturbed linear constraint model is presented as a model of time varying AR coefficients. The overall model for the time series is fitted by using the Kalman filter and Akaike's AIC criterion. An estimate of a changing spectrum is obtained by the fitted model and the fixed interval smoother Examples are given to illustrate the procedure.     

Buckyball quantum computer: realization of a quantum gate

We have studied a system composed by two endohedral fullerene molecules. We have found that this system can be used as good candidate for the realization of quantum gates. Each of these molecules encapsules an atom carrying a spin, therefore they interact through the spin dipole interaction. We show that a phase gate can be realized if we apply static and time dependent magnetic fields on each encased spin. We have evaluated the operational time of a π-phase gate, which is of the order of ns. We made a comparison between the theoretical estimation of the gate time and the experimental decoherence time for each spin. The comparison shows that the spin relaxation time is much larger than the π-gate operational time. Therefore, this indicates that, during the decoherence time, it is possible to perform some thousands of quantum computational operations. Moreover, through the study of concurrence, we get very good results for the entanglement degree of the two-qubit system. This finding opens a new avenue for the realization of quantum computers.     

Time behavior of the correlation functions in a simple dissipative quantum model

The force and velocity correlation functions for a particle interacting with a bath are calculated within a model allowing for finite memory effects. The relevance of a Brownian picture is delineated in view of the respective behavior of these functions and appears fully inadequate below some cross-over temperature; then, the interplay between quantum and thermal fluctuations yields some long time tails on the same time scale for both correlation functions. The real space transient diffusion coefficient is found to exceed its asymptotic Einstein value for most times in that regime. The limiting case of an infinitely short memory time is also investigated and is seen to produce weak divergences on a time scale which is small as compared to the other characteristic times.     

Interpolating Strange Attractors via Fractional Brownian Bridges

We present a novel method for interpolating univariate time series data. The proposed method combines multi-point fractional Brownian bridges, a genetic algorithm, and Takens’ theorem for reconstructing a phase space from univariate time series data. The basic idea is to first generate a population of different stochastically-interpolated time series data, and secondly, to use a genetic algorithm to find the pieces in the population which generate the smoothest reconstructed phase space trajectory. A smooth trajectory curve is hereby found to have a low variance of second derivatives along the curve. For simplicity, we refer to the developed method as PhaSpaSto-interpolation, which is an abbreviation for phase-space-trajectory-smoothing stochastic interpolation. The proposed approach is tested and validated with a univariate time series of the Lorenz system, five non-model data sets and compared to a cubic spline interpolation and a linear interpolation. We find that the criterion for smoothness guarantees low errors on known model and non-model data. Finally, we interpolate the discussed non-model data sets, and show the corresponding improved phase space portraits. The proposed method is useful for interpolating low-sampled time series data sets for, e.g., machine learning, regression analysis, or time series prediction approaches. Further, the results suggest that the variance of second derivatives along a given phase space trajectory is a valuable tool for phase space analysis of non-model time series data, and we expect it to be useful for future research.     

From random walk to single-file diffusion

We report an experimental study of diffusion in a quasi-one-dimensional (q1D) colloid suspension which behaves like a Tonks gas. The mean squared displacement as a function of time is described well with an ansatz encompassing a time regime that is both shorter and longer than the mean time between collisions. The ansatz asserts that the inverse mean squared displacement is the sum of the inverse mean squared displacement for short time normal diffusion (random walk) and the inverse mean squared displacement for asymptotic single-file diffusion (SFD). The dependence of the 1D mobility in the SFD on the concentration of the colloids agrees quantitatively with that derived for a hard rod model, which confirms for the first time the validity of the hard rod SFD theory. We also show that a recent SFD theory by Kollmann leads to the hard rod SFD theory for a Tonks gas.     

Two-dimensional Fourier transform of arbitrarily sampled NMR data sets

A new procedure for Fourier transform with respect to more than one time variable simultaneously is proposed for NMR data processing. In the case of two-dimensional transform the spectrum is calculated for pairs of frequencies, instead of conventional sequence of one-dimensional transforms. Therefore, it enables one to Fourier transform arbitrarily sampled time domain and thus allows for analysis of high dimensionality spectra acquired in a short time. The proposed method is not limited to radial sampling, it requires only to fulfill the Nyquist theorem considering two or more time domains at the same time. We show the application of new approach to the 3D HNCO spectrum acquired for protein sample with radial and spiral time domain sampling.