Nearby Initial Conditions Research Articles

Hidden Strange Nonchaotic Attractors

In this paper, it is found numerically that the previously found hidden chaotic attractors of the Rabinovich–Fabrikant system actually present the characteristics of strange nonchaotic attractors. For a range of the bifurcation parameter, the hidden attractor is manifestly fractal with aperiodic dynamics, and even the finite-time largest Lyapunov exponent, a measure of trajectory separation with nearby initial conditions, is negative. To verify these characteristics numerically, the finite-time Lyapunov exponents, ‘0-1’ test, power spectra density, and recurrence plot are used. Beside the considered hidden strange nonchaotic attractor, a self-excited chaotic attractor and a quasiperiodic attractor of the Rabinovich–Fabrikant system are comparatively analyzed.

Stochastic stability of a piezoelectric vibration energy harvester under a parametric excitation and noise-induced stabilization

Vibration energy harvesters seek to convert the energy of ambient, random vibrations into electrical power, often using piezoelectric transduction. The stochastic dynamics of a piezoelectric harvester subjected to a parametric (state-dependent) excitation has not been comprehensively investigated in the nonequilibrium regime. Motivated by mathematical results that establish the stabilization of dynamic response using noise, we investigate the stochastic stability of a generic harvester in the linear and the monostable nonlinear regimes excited by a multiplicative noise process characterized by both Brownian and Lévy distributions. Stability is characterized in each case by studying the approach of the harvester response towards equilibrium in the time domain, longer term proximity (or divergence) of two solutions starting with nearby initial conditions in the phase plane as well as the Lyapunov exponent. In the linear case, we analytically obtain a lower bound on the magnitude of the noise intensity that guarantees stability. The bound is derived as an inequality in terms of the system parameters. This analytic result is validated numerically using the Euler-Maruyama scheme by: (1) computing the harvester response and its approach to equilibrium in terms of its displacement, velocity and voltage, (2) computing the trajectories of two solutions with nearby initial conditions in the phase plane and (3) the sign of the maximal Lyapunov exponent in terms of energy. We find that noise-induced stabilization occurs consistently for the noise intensities greater than the lower bound in linear and weakly nonlinear harvesters, for both Brownian and Lévy excitation. Instabilities emerge for the noise intensities lower than the bound. The results lead to the interesting conclusion that noise of appropriate strength can induce stabilization and are expected to be useful in the design of energy harvesters. In addition, the results are expected to be significant in the study of phenomena such as noise-induced transport in Brownian rotors where stability is an important aspect of the stochastic dynamics.

Are long-term N-body simulations reliable?

ABSTRACT N-body integrations are used to model a wide range of astrophysical dynamics, but they suffer from errors which make their orbits diverge exponentially in time from the correct orbits. Over long time-scales, their reliability needs to be established. We address this reliability by running a three-body planetary system over about 200 e-folding times. Using nearby initial conditions, we can construct statistics of the long-term phase-space structure and compare to rough estimates of resonant widths of the system. We compared statistics for a wide range of numerical methods, including a Runge–Kutta method, Wisdom–Holman method, symplectic corrector methods, and a method by Laskar and Robutel. ‘Improving’ an integrator did not increase the phase-space accuracy, but simply increasing the number of initial conditions did. In fact, the statistics of a higher order symplectic corrector method were inconsistent with the other methods in one test.

On the graphical stability of hybrid solutions with non-matching jump times

We investigate stability of a solution of a hybrid system in the sense that the graphs of solutions from nearby initial conditions remain close and tend towards the graph of the given solution. In this manner, a small continuous-time mismatch is allowed between the jump times of neighbouring solutions and the ‘peaking phenomenon’ is avoided. We provide conditions such that this stability notion is implied by stability with respect to a specifically designed distance-like function. Hence, stability of solutions in the graphical sense can be analysed with existing Lyapunov techniques.

Extending the hybrid methodology for orbit propagation by fitting techniques

The hybrid methodology for orbit propagation is a technique that allows improving the accuracy of any propagator for predicting the future trajectory of a satellite or space-debris object in orbit around the Earth. It is based on modeling the error of the base propagator to be enhanced. Both statistical time-series forecasting methods and machine-learning techniques can be used for that purpose. The standard procedure for developing a hybrid orbit propagator requires some initial control data, that is, a set of precise ephemerides corresponding to either real observations or accurately computed pseudo-observations, from which to model the base-propagator error dynamics. It also needs tuning the time-series forecaster from those control data. We propose an improvement to the hybrid methodology for orbit propagation, based on fitting new hybrid propagators from others previously developed for nearby initial conditions, which avoids the need for both the control data and the tuning process, and achieves comparable results.

The Mid-Pleistocene Transition induced by delayed feedback and bistability

The Mid-Pleistocene Transition, the shift from 41 kyr to 100 kyr glacial-interglacial cycles that occurred roughly 1 Myr ago, is often considered as a change in internal climate dynamics. Here we revisit the model of Quaternary climate dynamics that was proposed by Saltzman and Maasch (1988). We show that it is quantitatively similar to a scalar equation for the ice dynamics only when combining the remaining components into a single delayed feedback term. The delay is the sum of the internal times scales of ocean transport and ice sheet dynamics, which is on the order of 10 kyr. We find that, in the absence of astronomical forcing, the delayed feedback leads to bistable behaviour, where stable large-amplitude oscillations of ice volume and an equilibrium coexist over a large range of values for the delay. We then apply astronomical forcing. We perform a systematic study to show how the system response depends on the forcing amplitude. We find that over a wide range of forcing amplitudes the forcing leads to a switch from small-scale oscillations of 41 kyr to large-amplitude oscillations of roughly 100 kyr without any change of other parameters. The transition in the forced model consistently occurs near the time of the Mid-Pleistocene Transition as observed in data records. This provides evidence that the MPT could have been primarily a forcing-induced switch between attractors of the internal dynamics. Small additional random disturbances make the forcing-induced transition near 800 kyr BP even more robust. We also find that the forced system forgets its initial history during the small-scale oscillations, in particular, nearby initial conditions converge prior to transitioning. In contrast to this, in the regime of large-amplitude oscillations, the oscillation phase is very sensitive to random perturbations, which has a strong effect on the timing of the deglaciation events.

Intrinsic mode functions locate implicit turbulent attractors in time in frontal lobe MEG recordings

In seeking evidence for the presence and characteristic range of coupled time scale(s) of putative implicit turbulent attractors of dorsal frontal lobe magnetic fields, the recorded nonstationary, nonlinear MEG signals were non-orthogonally decomposed using Huang’s Empirical Mode Decomposition, EMD, (Huang and Attoh-Okine, 2005) into 16 Intrinsic Mode Functions, EMD→IMFi, i=1…16. Measures known to be invariant in non-uniformly hyperbolic (turbulent) dynamical systems, topological entropy, hT, metric entropy, hM, non-uniform entropy, hU and power spectral scaling exponent, α, were imposed on each of the IMFi which evidenced most clearly an invariant temporal scale zone of IMFi, i=6…11, for hT, which we have found to be the most robust of invariant measures of MEG’s magnetic field turbulent attractors (Mandell et al., 2011a,b; Mandell, 2013). The ergodic theory of dynamical systems (Walters, 1982; Pollicott and Yuri, 1998) allows the inference that an implicit attractor with consistently hT>0 will also evidence at least one positive Lyapounov exponent indicating the presence of a turbulent attractor with exponential separation of nearby initial conditions, exponential convergence of distant points and disordering, mixing, of orbital sequences. It appears that this approach permits the inference of the presence of chaotic, turbulent attractor and its characteristic time scales without the invocation of arbitrary n-dimensional embedding, phase space reconstructions or (inappropriate) orthogonal decompositions.

Discontinuity-induced bifurcation cascades in flows and maps with application to models of the yeast cell cycle

This paper applies methods of numerical continuation analysis to document characteristic bifurcation cascades of limit cycles in piecewise-smooth, hybrid-dynamical-system models of the eukaryotic cell cycle, and associated period-adding cascades in piecewise-defined maps with gaps. A general theory is formulated for the occurrence of such cascades, for example given the existence of a period-two orbit with one point on the system discontinuity and with appropriate constraints on the forward trajectory for nearby initial conditions. In this case, it is found that the bifurcation cascade for nearby parameter values exhibits a scaling relationship governed by the largest-in-magnitude Floquet multiplier, here required to be positive and real, in complete agreement with the characteristic scaling observed in the numerical study. A similar cascade is predicted and observed in the case of a saddle–node bifurcation of a period-two orbit, away from the discontinuity, provided that the associated center manifold is found to intersect the discontinuity transversally.

Quantitative Universality for a Class of Weakly Chaotic Systems

We consider a general class of intermittent maps designed to be weakly chaotic, i.e., for which the separation of trajectories of nearby initial conditions is weaker than exponential. We show that all its spatio and temporal properties, hitherto regarded independently in the literature, can be represented by a single characteristic function ϕ. A universal criterion for the choice of ϕ is obtained within the Feigenbaum’s renormalization-group approach. We find a general expression for the dispersion rate ζ(t) of initially nearby trajectories and we show that the instability scenario for weakly chaotic systems is more general than that originally proposed by Gaspard and Wang (Proc. Natl. Acad. Sci. USA 85:4591, 1988). We also consider a spatially extended version of such class of maps, which leads to anomalous diffusion, and we show that the mean squared displacement satisfies σ 2(t)∼ζ(t). To illustrate our results, some examples are discussed in detail.

Modal Spectra Extracted from Nonequilibrium Fluid Patterns in Laboratory Experiments on Rayleigh-Bénard Convection

We describe a method to extract from experimental data the important dynamical modes in spatiotemporal patterns in a system driven out of thermodynamic equilibrium. Using a novel optical technique for controlling fluid flow, we create an experimental ensemble of Rayleigh-Bénard convection patterns with nearby initial conditions close to the onset of secondary instability. An analysis of the ensemble evolution reveals the spatial structure of the dominant modes of the system as well as the corresponding growth rates. The extracted modes are related to localized versions of instabilities found in the ideal unbounded system. The approach may prove useful in describing instability in experimental systems as a step toward prediction and control.

Noise-induced switching near a depth two heteroclinic network and an application to Boussinesq convection

We investigate the robust heteroclinic dynamics arising in a system of ordinary differential equations in R(4) with symmetry [Formula in text]. This system arises from the normal form reduction of a 1: squate root of 2 mode interaction for Boussinesq convection. We investigate the structure of a particular robust heteroclinic attractor with "depth two connections" from equilibria to subcycles as well as connections between equilibria. The "subcycle" is not asymptotically stable, due to nearby trajectories undertaking an "excursion," but it is a Milnor attractor, meaning that a positive measure set of nearby initial conditions converges to the subcycle. We investigate the dynamics in the presence of noise and find a number of interesting properties. We confirm that typical trajectories wind around the subcycle with very occasional excursions near a depth two connection. The frequency of excursions depends on noise intensity in a subtle manner; in particular, for anisotropic noise, the depth two connection may be visited much more often than for isotropic noise, and more generally the long term statistics of the system depends not only on the noise strength but also on the anisotropy of the noise. Similar properties are confirmed in simulations of Boussinesq convection for parameters giving an attractor with depth two connections.

Meta-chaos: Reconstructing chaotic attractors from the separation of nearby initial conditions on hyperhelices

Examples of reconstruction of chaotic attractors from the measure of exponential separation of nearby initial conditions on curves generated by iteratively coiling a helix around the result of the previous step, so called hyperhelices, are shown.

Motion planning and trajectory tracking for three-dimensional Poiseuille flow

We present the first solution to a boundary motion planning problem for the Navier–Stokes equations, linearized around the parabolic equilibrium in a three-dimensional channel flow. The pressure and skin friction at one wall are chosen as the reference outputs as they are the most readily measurable ‘wall-restricted’ quantities in experimental fluid dynamics and also because they play a special role as performance metrics in aerodynamics. The reference velocity input is applied at the opposite wall. We find the exact (method independent) solution to the motion planning problem using the PDE (partial differential equation) backstepping theory. The motion planning solution results in open-loop controls, which produce the reference output trajectories only under special initial conditions for the flow velocity field. To achieve convergence to the reference trajectory from other (nearby) initial conditions, we design a feedback controller. We also present a detailed examination of the closed-form solutions for gains and the behaviour of the motion planning solution as the wavenumbers grow or the Reynolds number grows. Numerical results are shown for the motion planning problem.

Anti-deterministic behaviour of discrete systems that are less predictable than noise

We present a new type of deterministic dynamical behaviour that is less predictable than white noise. We call it anti-deterministic (AD) because time series corresponding to the dynamics of such systems do not generate deterministic lines in recurrence plots for small thresholds. We show that although the dynamics is chaotic in the sense of exponential divergence of nearby initial conditions and although some properties of AD data are similar to white noise, the AD dynamics is in fact, less predictable than noise and hence is different from pseudo-random number generators.

The predictability of large-scale wind-driven flows

Abstract. The singular values associated with optimally growing perturbations to stationary and time-dependent solutions for the general circulation in an ocean basin provide a measure of the rate at which solutions with nearby initial conditions begin to diverge, and hence, a measure of the predictability of the flow. In this paper, the singular vectors and singular values of stationary and evolving examples of wind-driven, double-gyre circulations in different flow regimes are explored. By changing the Reynolds number in simple quasi-geostrophic models of the wind-driven circulation, steady, weakly aperiodic and chaotic states may be examined. The singular vectors of the steady state reveal some of the physical mechanisms responsible for optimally growing perturbations. In time-dependent cases, the dominant singular values show significant variability in time, indicating strong variations in the predictability of the flow. When the underlying flow is weakly aperiodic, the dominant singular values co-vary with integral measures of the large-scale flow, such as the basin-integrated upper ocean kinetic energy and the transport in the western boundary current extension. Furthermore, in a reduced gravity quasi-geostrophic model of a weakly aperiodic, double-gyre flow, the behaviour of the dominant singular values may be used to predict a change in the large-scale flow, a feature not shared by an analogous two-layer model. When the circulation is in a strongly aperiodic state, the dominant singular values no longer vary coherently with integral measures of the flow. Instead, they fluctuate in a very aperiodic fashion on mesoscale time scales. The dominant singular vectors then depend strongly on the arrangement of mesoscale features in the flow and the evolved forms of the associated singular vectors have relatively short spatial scales. These results have several implications. In weakly aperiodic, periodic, and stationary regimes, the mesoscale energy content is usually relatively low and the predictability of the wind-driven circulation is determined by the large-scale structure of the flow. In the more realistic, strongly chaotic regime, in which energetic mesoscale eddies are produced by the meandering of the separated western boundary current extension, the predictability of the flow locally tends to be a stronger function of the local mesoscale eddy structure than of the larger scale structure of the circulation. This has a broader implication for the effectiveness of different approaches to forecasting the ocean with models which sequentially assimilate new observations.

Model error in weather forecasting

Abstract. Operational forecasting is hampered both by the rapid divergence of nearby initial conditions and by error in the underlying model. Interest in chaos has fuelled much work on the first of these two issues; this paper focuses on the second. A new approach to quantifying state-dependent model error, the local model drift, is derived and deployed both in examples and in operational numerical weather prediction models. A simple law is derived to relate model error to likely shadowing performance (how long the model can stay close to the observations). Imperfect model experiments are used to contrast the performance of truncated models relative to a high resolution run, and the operational model relative to the analysis. In both cases the component of forecast error due to state-dependent model error tends to grow as the square-root of forecast time, and provides a major source of error out to three days. These initial results suggest that model error plays a major role and calls for further research in quantifying both the local model drift and expected shadowing times.

Aperiodic Chaotic Orbits

1. INTRODUCTION. Two common formalizations of the popular notion of unpredictability in the presence of chaos are sensitive dependence on initial conditions and expansiveness. Sensitive dependence on initial conditions suggests that orbits of chaotic systems corresponding to even very nearby initial conditions may separate as time grows. Expansiveness occurs when all initial conditions yield orbits which must, for some time value, be separated by some minimum distance 8 > 0. This note sharpens the distinction between these concepts. The definition of a discrete time, dynamical system acting on a compact set, J, of the real line involves a function, say f, which maps J into itself. The function is applied iteratively. Specifically, the value of the system at time n is xn+1 = f(x) = fn+I(x), where x E J and fn( ) denotes the n-fold composition of f. An orbit of the dynamical system is denoted by {xn}. For ease of exposition, the presentation here is specialized to a familiar example for J = [0, 1], namely, the tent map defined by the function

Numerical, experimental, and analytical studies of the dissipative toda lattice: I. The behavior of a single solitary wave

The time evolution of solitons in a dissipative Toda lattice has been studied numerically, and results have been compared with experimental data measured on a nonlinear electrical transmission line. In the absence of dissipation the Toda lattice is an integrable soliton system, but when dissipation is present the traveling solitary wave decreases and a tail is formed behind it. Nevertheless, some solitonic properties persist even with strong dissipation: There is some decreasing traveling wave solution which attracts all nearby initial conditions, furthermore the scattering of these solitary waves remains elastic, as will be shown in part II. For strong dissipation, and also for large times, the process is nonadiabatic and the perturbative methods used on the inverse scattering method do not seem to work. However, we have found a simple linear method for the construction of a good approximate solution for the dissipative tail.