基于Lorenz映射的混沌系统分支变换预报规律研究

尽管Lorenz系统具有混沌和非周期性质, 但其分支变换是可预报的.本文以强迫Lorenz系统为数学模型, 基于Lorenz映射, 研究了混沌系统分支变换的预报规律, 将原有关于分支开始变换条件和新分支持续时间的两条一般规律扩展到了3条, 并首次分析了系统当前状态达到变换条件所需时间的预报规律, 从而为预报混沌系统非周期演变提供了另一途径.结果表明: 映射尖点位置为分支变换的临界值, 当变量z超过相应临界值时, 系统在当前分支的运动即将结束, 下一循环将跳跃到另一分支运动; 系统在同一分支循环的次数随极值z_max单调减小, z_max 越小, 达到变换条件需循环的次数越多; 系统在新分支持续的时间是先前分支最大极值z_M 的单调增加函数, z_M越大, 持续时间增加的幅度也越大.此外, 外强迫影响着混沌系统分支变换的预报规律, 其不但使正负分支的变换条件出现差异, 且与新分支持续时间的增加速率和达到变换条件所需时间的递减速率密切相关. 关键词： Lorenz映射 分支变换 外强迫 预报规律     

A model for the transition to baroclinic chaos

The transition to chaos in a 2-layer baroclinic fluid with a slightly different viscosity in each layer is investigated. A low-order model is constructed by truncating the quasi-geostrophic partial differential equations to include one azimuthal wave in each layer while retaining a general zonal-flow correction. When the viscosities are equal the model reduces to a modified form of the Lorenz equations and displays a cusped return map. For slightly different viscosities the transition to chaos follows the Feigenbaum scenario. The return map in the chaotic regime is nearly parabolic and highly contracted. Multiple attractors are found for the same control parameters. The predicted route to chaos is similar to that observed in laboratory experiments, although significant quantitative differences remain.     

Stochastic aspects of pattern formation during the catalytic oxidation of CO on Pd(111) surfaces

We present experimental results on rare transitions between two states due to intrinsic noise between two states in a bistable surface reaction, namely the catalytic oxidation of CO on Pd(111) surfaces. The mean time scales involved are typically of order 10⁴ s and the probability distribution shows two peaks over a large part of the bistable regime of this surface reaction. We use measurements of the resulting CO₂ rate as well as photoelectron emission microscopy (PEEM) to characterize these rare transitions. From our dynamic data we can extract probability distributions for the CO₂ rate. We use x-t plots from PEEM measurements to describe the transitions, which are-as we demonstrate-characterized by one wall moving through the field of view in PEEM measurements. The resulting probability distributions for the CO₂ rate are shown to depend strongly on the value, Y, of the CO fraction in the reactant flux inside the bistable regime. We find that the probability distribution is strongly asymmetric indicating that the two basins of attraction are rather different in depth and width. This is also concluded from the PEEM measurements, which show in one case a rather sharp and narrow domain wall going one way, while it is rather wide and diffuse for the motion in the opposite direction. To have two basins of attraction in the bistable regime, which are rather different in nature is reminiscent of other bistable systems such as, for example, optical bistability, although the time scales involved in the present system are entirely different.     

The Weibull-log Weibull distribution for interoccurrence times of earthquakes

By analyzing the Japan Meteorological Agency (JMA) seismic catalog for different tectonic settings, we have found that the probability distributions of time intervals between successive earthquakes-interoccurrence times-can be described by the superposition of the Weibull distribution and the log-Weibull distribution. In particular, the distribution of large earthquakes obeys the Weibull distribution with the exponent α₁<1, indicating the fact that the sequence of large earthquakes is not a Poisson process. It is found that the ratio of the Weibull distribution to the probability distribution of the interoccurrence time gradually increases with increase in the threshold of magnitude. Our results infer that Weibull statistics and log-Weibull statistics coexist in the interoccurrence time statistics, and that the change of the distribution is considered as the change of the dominant distribution. In this case, the dominant distribution changes from the log-Weibull distribution to the Weibull distribution, allowing us to reinforce the view that the interoccurrence time exhibits the transition from the Weibull regime to the log-Weibull regime.     

The Weibull-log Weibull transition of the interoccurrence time statistics in the two-dimensional Burridge-Knopoff Earthquake model

In analyzing synthetic earthquake catalogs created by a two-dimensional Burridge-Knopoff model, we have found that a probability distribution of the interoccurrence times, the time intervals between successive events, can be described clearly by the superposition of the Weibull distribution and the log-Weibull distribution. In addition, the interoccurrence time statistics depend on frictional properties and stiffness of a fault and exhibit the Weibull-log Weibull transition, which states that the distribution function changes from the log-Weibull regime to the Weibull regime when the threshold of magnitude is increased. We reinforce a new insight into this model; the model can be recognized as a mechanical model providing a framework of the Weibull-log Weibull transition.     

外强迫对Lorenz系统初值可预报性的影响

利用强迫Lorenz模型, 研究了外强迫对Lorenz系统混沌性质、 映射结构及初值可预报性的影响, 并以海表温度为大气运动的外强迫, 用实际大气海洋资料分析了外强迫对大气可预报性的影响. 结果发现, 系统混沌现象的出现与外强迫有关, 外强迫改变了Lorenz系统的运动规律, 使围绕两奇怪吸引子运动的随机性减少. 考虑外强迫后, 系统运动轨迹的概率密度函数呈不对称的双峰结构, 且Lorenz映射由无外强迫时的一个尖点分离为两个尖点, 尖点的偏离方向和偏离位置分别与外强迫的正负和大小有关. 外强迫可减小Lorenz系统对初值的敏感性, 提高系统的初值可预报性, 尤其是外强迫越大, 可预报性提高的幅度也越大. 这些结果在不同强度海表温度强迫下的实际大气可预报性分析中得到了证实, 即海温异常越大, 实际大气变量的可预报性也越大.     

Bounds for the chaotic region in the Lorenz model

In a previous paper, the authors made an extensive numerical study of the Lorenz model, changing all three parameters of the system. We conjectured that the region of parameters where the Lorenz model is chaotic is bounded for fixed r. In this paper, we give a theoretical proof of the conjecture by obtaining theoretical bounds for the chaotic region and by using Fenichel theory. The theoretical bounds are complemented with numerical studies performed using the Maximum Lyapunov Exponent and OFLI2 techniques, and a comparison of both sets of results is shown. Finally, we provide a complete three-dimensional model of the chaotic regime depending on the three parameters.     

Scaling and memory in the return intervals of realized volatility

We perform return interval analysis of 1-min realized volatility defined by the sum of absolute high-frequency intraday returns for the Shanghai Stock Exchange Composite Index (SSEC) and 22 constituent stocks of SSEC. The scaling behavior and memory effect of the return intervals between successive realized volatilities above a certain threshold q are carefully investigated. In comparison with the volatility defined by the closest tick prices to the minute marks, the return interval distribution for the realized volatility shows a better scaling behavior since 20 stocks (out of 22 stocks) and the SSEC pass the Kolmogorov-Smirnov (KS) test and exhibit scaling behaviors, among which the scaling function for 8 stocks could be approximated well by a stretched exponential distribution revealed by the KS goodness-of-fit test under the significance level of 5%. The improved scaling behavior is further confirmed by the relation between the fitted exponent γ and the threshold q. In addition, the similarity of the return interval distributions for different stocks is also observed for the realized volatility. The investigation of the conditional probability distribution and the detrended fluctuation analysis (DFA) show that both short-term and long-term memory exists in the return intervals of realized volatility.     

The role of ergodicity and mixing in the central limit theorem for Casati-Prosen triangle map variables

In this Letter we analyse the behaviour of the probability density function of the sum of N deterministic variables generated from the triangle map of Casati-Prosen. For the case in which the map is both ergodic and mixing the resulting probability density function quickly concurs with the Normal distribution. However, when the map is weakly chaotic, and fuzzily not mixing, the resulting probability density functions are described by power-laws. Moreover, contrarily to what it would be expected, as the number of added variables N increases the distance to Gaussian distribution increases. This behaviour goes against standard central limit theorem. By extrapolation of our finite size results we preview that in the limit of N going to infinity the distribution has the same asymptotic decay as a Lorentzian (or a q=2-Gaussian).     

Detailed description of a two-state non-Markov system

A two-state system in which transitions between the states are made randomly, is often used as a model of different phenomena in several fields. Both the probability density for the cumulative dwell-time in one of the states during a fixed observation time T, and the distribution of the number of transitions made during that time are known. We calculate the joint distribution of these two correlated random variables, showing that at long times it approaches a two-dimensional Gaussian form.     

Chaos and limit cycles in the Lorenz model

The Lorenz model is interpreted as a damping motion under a time-dependent force. The range of the Rayleigh number r in which limit cycles exist is studied by numerical simulation. The shape of the limit cycle is given.     

Dynamical phases of the Hindmarsh-Rose neuronal model: studies of the transition from bursting to spiking chaos

The dynamical phases of the Hindmarsh-Rose neuronal model are analyzed in detail by varying the external current I. For increasing current values, the model exhibits a peculiar cascade of nonchaotic and chaotic period-adding bifurcations leading the system from the silent regime to a chaotic state dominated by bursting events. At higher I-values, this phase is substituted by a regime of continuous chaotic spiking and finally via an inverse period doubling cascade the system returns to silence. The analysis is focused on the transition between the two chaotic phases displayed by the model: one dominated by spiking dynamics and the other by bursts. At the transition an abrupt shrinking of the attractor size associated with a sharp peak in the maximal Lyapunov exponent is observable. However, the transition appears to be continuous and smoothed out over a finite current interval, where bursts and spikes coexist. The beginning of the transition (from the bursting side) is signaled from a structural modification in the interspike interval return map. This change in the map shape is associated with the disappearance of the family of solutions responsible for the onset of the bursting chaos. The successive passage from bursting to spiking chaos is associated with a progressive pruning of unstable long-lasting bursts.     

Nonlinear dynamos: A complex generalization of the Lorenz equations

Plane nonlinear dynamo waves can be described by a sixth order system of nonlinear ordinary differential equations which is a complex generalization of the Lorenz system. In the regime of interest for modelling magnetic activity in stars there is a sequence of bifurcations, ending in chaos, as a stability parameter D (the dynamo number) is increased. We show that solutions undergo three successive Hopf bifurcations, followed by a transition to chaos. The system possesses a symmetry and can therefore be reduced to a fifth order system, with trajectories that lie on a 2-torus after the third bifurcation. As D is then increased, frequency locking occurs, followed by a sequence of period-doubling bifurcations that leads to chaos. This behaviour is probably caused by the Shil'nikov mechanism, with a (conjectured) homoclinic orbit when D is infinite.     

Monte Carlo study of phase transitions in the bond-diluted 3D 4-state Potts model

Large-scale Monte Carlo simulations of the bond-diluted three-dimensional 4-state Potts model are performed. The phase diagram and the physical properties at the phase transitions are studied using finite-size scaling techniques. Evidences are given for the existence of a tricritical point dividing the phase diagram into a regime where the transitions remain of first order and a second regime where the transitions are softened to continuous ones by the influence of disorder. In the former regime, the nature of the transition is essentially clarified through an analysis of the energy probability distribution. In the latter regime critical exponents are estimated. Rare and typical events are identified and their role is qualitatively discussed in both regimes.     

Different ways to turbulence in dissipative dynamical systems

The Lorenz model is studied in details for σ = 10, $\text{b =}\text{8}\text{3}$ and 145 < r < 170. Between r = 145 and r = 148.4 the Lore nz attractor disaggregates itself into a limit cycle through a cascade of bifurcation with successive undoubling of periods. At r = 166.07 this limit cycle looses its stability through “intermittency”, giving rise to a second aperiodic attractor. We give a semi-quantitative interpretation of these processes and discuss their relation with the different transitions to turbulence observed experimentally.     

What makes a phase transition? Analysis of the random satisfiability problem

In the last 30 years it was found that many combinatorial systems undergo phase transitions. One of the most important examples of these can be found among the random k-satisfiability problems (often referred to as k-SAT), asking whether there exists an assignment of Boolean values satisfying a Boolean formula composed of clauses with k random variables each. The random 3-SAT problem is reported to show various phase transitions at different critical values of the ratio of the number of clauses to the number of variables. The most famous of these occurs when the probability of finding a satisfiable instance suddenly drops from 1 to 0. This transition is associated with a rise in the hardness of the problem, but until now the correlation between any of the proposed phase transitions and the hardness is not totally clear. In this paper we will first show numerically that the number of solutions universally follows a lognormal distribution, thereby explaining the puzzling question of why the number of solutions is still exponential at the critical point. Moreover we provide evidence that the hardness of the closely related problem of counting the total number of solutions does not show any phase transition-like behavior. This raises the question of whether the probability of finding a satisfiable instance is really an order parameter of a phase transition or whether it is more likely to just show a simple sharp threshold phenomenon. More generally, this paper aims at starting a discussion where a simple sharp threshold phenomenon turns into a genuine phase transition.     

Angular distribution effect on the integrated cross section for radiative capture of 14 MeV neutrons

In the past, many reported integrated cross sections for the 14 MeV neutron radiative capture were measured at 90° relative to the neutron beam direction and multiplied by 4π, so as to obtain a measure of the angle-integrated cross sections.In such a procedure, an isotropic angular distribution of γ-rays is assumed. We calculated this distribution using the consistent direct-semi-direct model, in which the need for the model-free parameters has been eliminated. The result is that the a₁ Legendre polynomial, averaged over the bound state transitions, is practically zero (distribution is forward-backward symmetric) and that the a₂ coefficient is a smooth function of the mass number with the values between −0.4 and −0.6, indicating anisotropy of the distribution. Reported integrated cross sections are therefore for about 20% to 30% too high relative to the properly angle integrated cross sections.     

Limit cycles and chaos in realistic models of the Belousov-Zhabotinskii reaction system

Effects of spatial variation in the Belousov-Zhabotinskii reaction is studied numerically by adopting the Field-Noyes kinetics (Oregonator) and the Zhabotinskii-Zaikin-Korzukhin-Kreitser kinetics. This is carried out for a spatially-discrete model composed ofN equivalent cells interacting through gradient coupling. When the system is near the boundary at which a uniform steady state bifurcates into a limit cycle, it is found with the aid of a perturbation expansion that the above models withN=3 exhibit various types of oscillations depending on the interaction strength between cells. Chaotic characteristics are also observed for a certain region of parameters. It is shown that the ZZKK model withN=2 exhibits a different kind of chaos when the size of the limit cycle becomes sensitive to external parameters, e.g., the concentrations of bromate ion or bromomalonic acid. Although each cell is equivalent, symmetry about cell numbers usually breaks down in a periodic state. It is found, however, that symmetry is recovered for the former kind of chaos, while the latter kind of chaos, there exists an asymmetric chaos as well as symmetric chaos. This has been examined by the time evolution of a certain concentration variable and by its Lorenz plot. In the asymmetric chaos, the Lorenz plot constitutes approximately a one-dimensional map. Furthermore, possible connections of the present limit cycles and chaos with the experiments of Zhabotinskii and Vavilin-Zhabotinskii-Zaikin are suggested.     

Stochastic analysis of explosive behaviour: A qualitative approach

In many instances, the evolution of physico-chemical systems involves a long slow induction period followed by an abrupt switching to a final stable attractor. In the present paper the properties of fluctuations during this explosive stage of evolution are analyzed. Qualitative arguments, confirmed by an exactly soluble model, establish that this regime is characterized by the development of long tails and multiple humps in the probability distribution. The implications of this phenomenon of transient bimodality are discussed.     

Resonances in a Chaotic Attractor Crisis of the Lorenz Flow

Local bifurcations of stationary points and limit cycles have successfully been characterized in terms of the critical exponents of these solutions. Lyapunov exponents and their associated covariant Lyapunov vectors have been proposed as tools for supporting the understanding of critical transitions in chaotic dynamical systems. However, it is in general not clear how the statistical properties of dynamical systems change across a boundary crisis during which a chaotic attractor collides with a saddle. This behavior is investigated here for a boundary crisis in the Lorenz flow, for which neither the Lyapunov exponents nor the covariant Lyapunov vectors provide a criterion for the crisis. Instead, the convergence of the time evolution of probability densities to the invariant measure, governed by the semigroup of transfer operators, is expected to slow down at the approach of the crisis. Such convergence is described by the eigenvalues of the generator of this semigroup, which can be divided into two families, referred to as the stable and unstable Ruelle–Pollicott resonances, respectively. The former describes the convergence of densities to the attractor (or escape from a repeller) and is estimated from many short time series sampling the state space. The latter is responsible for the decay of correlations, or mixing, and can be estimated from a long times series, invoking ergodicity. It is found numerically for the Lorenz flow that the stable resonances do approach the imaginary axis during the crisis, as is indicative of the loss of global stability of the attractor. On the other hand, the unstable resonances, and a fortiori the decay of correlations, do not flag the proximity of the crisis, thus questioning the usual design of early warning indicators of boundary crises of chaotic attractors and the applicability of response theory close to such crises.