Lyapunov Time Research Articles

On the dynamics of Comet 1P/Halley: Lyapunov and power spectra

Using a purely Newtonian model for the Solar System, we investigate the dynamics of comet 1P/Halley considering in particular the Lyapunov and power spectra of its orbit, using the nominal initial conditions of JPL's Horizons system. We carry out precise numerical integrations of the $(N+1)$-restricted problem and the first variational equations, considering a time span of $2\times10^5$~yr. The power spectra are dominated by a broadband component, with peaks located at the current planetary frequencies, including contributions from Jupiter, Venus, the Earth and Saturn, as well as the $1:6$ resonance among Halley and Jupiter and higher harmonics. From the average value of the maximum Lyapunov exponent we estimate the Lyapunov time of the comet's nominal orbit, obtaining $\tau_L \simeq 562$~yr; the remaining independent Lyapunov exponents (not related by time-reversal symmetry) tend asymptotically to zero as $t^{-1/2}$. Yet, our results do not display convergence of the maximum Lyapunov exponent. We argue that the lack of convergence of the maximum Lyapunov exponent is a signature of transient chaos which will lead to an eventual ejection of the comet from the Solar System.

Analysis of daily streamflow complexity by Kolmogorov measures and Lyapunov exponent

Analysis of daily streamflow variability in space and time is important for water resources planning, development, and management. The natural variability of streamflow is being complicated by anthropogenic influences and climate change, which may introduce additional complexity into streamflow records. To address the complexity in streamflow, daily discharge data recorded during the period 1989–2016 at twelve gauging stations on Brazos River in Texas (USA) were used to derive a set of novel quantitative tools: Kolmogorov complexity (KC) and its derivative-associated measures to assess complexity, and Lyapunov time (LT) to assess predictability. It was found that all daily discharge series exhibited long memory with an increasing down-flow tendency, while the randomness of the series at individual sites could not be definitively concluded. All Kolmogorov complexity measures had relatively small values with the exception of the USGS (United States Geological Survey) 08088610 station at Graford, Texas, which exhibited the highest values of the complexity measures. This finding may be attributed to the elevated effect of human activities at Graford, and proportionally lesser effect at other stations. In addition, complexity tended to decrease downflow, meaning that larger catchments were generally less influenced by anthropogenic activities. The correction on randomness of Lyapunov time (quantifying predictability) was found to be inversely proportional to the Kolmogorov complexity, which strengthened our conclusion regarding the effect of anthropogenic activities, considering that KC and LT were distinct measures, based on rather different techniques.

Characteristic times in the standard map.

We study and compare three characteristic times of the standard map: the Lyapunov time t_{L}, the Poincaré recurrence time t_{r}, and the stickiness (or escape) time t_{st}. The Lyapunov time is the inverse of the Lyapunov characteristic number (L) and in general is quite small. We find empirical relations for the L as a function of the nonlinearity parameter K and of the chaotic area A. We also find empirical relations for the Poincaré recurrence time t_{r} as a function of the nonlinearity parameter K, of the chaotic area A, and of the size of the box of initial conditions ε. As a consequence, we find relations between t_{r} and L. We compare the distributions of the stickiness time and the Poincaré recurrence time. The stickiness time inside the sticky regions at the boundary of the islands of stability is orders of magnitude smaller than the Poincaré recurrence time t_{r} and this affects the diffusion exponent μ, which converges always to the value μ=1. This is shown in an extreme stickiness case. The diffusion is anomalous (ballistic motion) inside the accelerator mode islands of stability with μ=2 but it is normal everywhere outside the islands with μ=1. In a particular case of extreme stickiness, we find the hierarchy of islands around islands.

The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures.

The purpose of this paper was to choose an appropriate information dissimilarity measure for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations on the Brazos River in Texas (USA), for the period 1989–2016. For that purpose, we selected and compared the average-linkage clustering hierarchical algorithm based on the compression-based dissimilarity measure (NCD), permutation distribution dissimilarity measure (PDDM), and Kolmogorov distance (KD). The algorithm was also compared with K-means clustering based on Kolmogorov complexity (KC), the highest value of Kolmogorov complexity spectrum (KCM), and the largest Lyapunov exponent (LLE). Using a dissimilarity matrix based on NCD, PDDM, and KD for daily streamflow, the agglomerative average-linkage hierarchical algorithm was applied. The key findings of this study are that: (i) The KD clustering algorithm is the most suitable among others; (ii) ANOVA analysis shows that there exist highly significant differences between mean values of four clusters, confirming that the choice of the number of clusters was suitably done; and (iii) from the clustering we found that the predictability of streamflow data of the Brazos River given by the Lyapunov time (LT), corrected for randomness by Kolmogorov time (KT) in days, lies in the interval from two to five days.

Dynamical Glass and Ergodization Times in Classical Josephson Junction Chains.

Models of classical Josephson junction chains turn integrable in the limit of large energy densities or small Josephson energies. Close to these limits the Josephson coupling between the superconducting grains induces a short-range nonintegrable network. We compute distributions of finite-time averages of grain charges and extract the ergodization time T_{E} which controls their convergence to ergodic δ distributions. We relate T_{E} to the statistics of fluctuation times of the charges, which are dominated by fat tails. T_{E} is growing anomalously fast upon approaching the integrable limit, as compared to the Lyapunov time T_{Λ}-the inverse of the largest Lyapunov exponent-reaching astonishing ratios T_{E}/T_{Λ}≥10^{8}. The microscopic reason for the observed dynamical glass is rooted in a growing number of grains evolving over long times in a regular almost integrable fashion due to the low probability of resonant interactions with the nearest neighbors. We conjecture that the observed dynamical glass is a generic property of Josephson junction networks irrespective of their space dimensionality.

A novel memristive 6D hyperchaotic autonomous system with hidden extreme multistability

Abstract This paper presents a 6D autonomous system, obtained by introducing a flux-controlled memristor model into an existing 5D hyperchaotic autonomous system. The dynamics of the novel system are investigated in terms of equilibrium points, bifurcation diagrams, Lyapunov exponent spectra, phase portraits, time series and attraction basins. Moreover, its circuit implementation is also proposed. The system is hyperchaotic under a line or a plan of equilibria. Other attractive dynamics observed are: hidden extreme multistability, transient chaos, bursting and offset boosting phenomenon. Interestingly, for a particular set of parameters, an unusual metastability showing transition from chaotic to periodic bursting dynamics is found. Dynamical systems capable of producing the above complexity are not common in the literature; thus, this novel memristive 6D hyperchaotic autonomous system deserves particular attention. PSpice based simulations are in good agreement with numerical computations. To the best of our knowledge, this system is the first with higher order presenting all those phenomena.

The potentially hazardous NEA 2001 BB16

Abstract We computed the impact solutions of the potentially dangerous Near Earth Asteroid (NEA) 2001 BB16 based on 47 optical observations from January 20.08316 UTC, 2001, through February 09.15740 UTC, 2016, and one radar observation from January 19.90347 UTC, 2016. We used two methods to sample the starting Line of Variation (LOV). First method, called thereafter LOV1, with the uniform sampling of the LOV parameter, out to LOV = 5 computing 3000 virtual asteroids (VAs) on both sides of the LOV, which gives 6001 VAs and propagated their orbits to JD2525000.5 TDT=February 12, 2201. We computed the non-gravitational parameter A2=(34.55±7.38)·10–14 au/d2 for nominal orbit of 2001 BB16 and possible impacts with the Earth until 2201. For potential impact in 2195 we find A2=20.0·10−14 au/d2. With a positive value of A2, 2001 BB16 can be prograde rotator. Moreover, we computed Lyapunov Time (LT) for 2001 BB16, which for all VAs, has a mean value of about 25 y. We showed that impact solutions, including the calculated probability of a possible collision of a 2001 BB16 asteroid with the Earth depends on how to calculate and take into account the appropriate gravitational model, including the number of perturbing massive asteroids. In some complicated cases, it may depend also on the number of clones calculated for a given sigma LOV1. The second method of computing the impact solutions, called thereafter LOV2, is based on a non-uniformly sampling of the LOV. We showed that different methods of sampling the LOV can give different impact solutions, but all computed dates of possible impacts of the asteroid 2001 BB16 with the Earth occur in accordance at the end of the 22nd century.

Research on Dynamic Game Model and Application of China’s Imported Soybean Price in the Context of China‐US Economic and Trade Friction

China’s soybean price fluctuates due to the current economic and trade frictions between China and the United States. Brazil and the United States are regarded as two oligarchs in China’s soybean import market. A dynamic price game model is established, and price elasticity parameters are estimated by using statistical data and Rotterdam model. The stability of Nash equilibrium point is discussed through bifurcation diagram, maximum Lyapunov exponent, evolutionary trajectory, and time series diagram. The influence of price adjustment speed on equilibrium price is analyzed. The numerical simulation of price adjustment speed is carried out, which is compared with the actual situation of imported soybean price before and after the trade friction. The results show that the model constructed in this paper can reflect the changing trend of price and demand and predict the short‐term import soybean prices of Brazil and the United States. The forecast accuracy of price fluctuation is high. The results provide model and theoretical reference for price game under trade disputes and provide methodological reference for forecasting the price of imported goods.

Chaos in Non-Linear Planar Oscillation of a Satellite in an Elliptic Orbit under the Influence of Aerodynamic Torque

This article deals with the non-linear oscillation of a satellite in an elliptic orbit around the Earth under the influence of aerodynamic torque. It is assumed that the orbital plane of the satellite coincides with the equatorial plane of the Earth. The half width of the chaotic separatrix has been estimated by Chirikov criterion. Through surface of section method, it has been observed that the aerodynamic torque parameter (e), the eccentricity of the orbit (e) and the mass ratio (ω0) play an important role in changing the regular motion into the chaotic one. We studied the behaviour of trajectories due to change in parameters with Lyapunov exponents and time series plots. The theory is applied to Resourcesat1 an artiflcial satellite of the Earth.

Celestial chaos: The new logics of theory-testing in orbital dynamics

I explore how the nature, scope, and limits of the knowledge obtained in orbital dynamics has changed in recent years. Innovations in the design of spacecraft trajectories, as well as in astronomy, have led to new logics of theory-testing—that is, new research methodologies—in orbital dynamics. These methodologies—which combine resonance overlap theories, numerical experiments, and the implementation of space missions—were developed in response to the discovery of chaotic dynamical systems in our solar system. In the past few decades, they have replaced the methodology that dominated orbital research in the centuries following Newton's Principia. As a result, the kind of knowledge achieved by orbital research has changed: we can know how orbiting bodies in chaotic systems behave, but only over sufficiently short time scales; and we can reliably measure those temporal limitations, using Lyapunov time.

A multi-arc approach for chaotic orbit determination problems

Chaotic dynamical systems are characterized by the existence of a predictability horizon, connected to the notion of Lyapunov time, beyond which predictions of the state of the system are meaningless. In order to study the main features of orbit determination in the presence of chaos, Spoto and Milani (Celest Mech Dyn Astron 124:295–309, 2016) applied the classical least-squares fit and differential correction algorithm to determine a chaotic orbit and a dynamical parameter of a simple discrete system—Chirikov standard map (cf. Chirikov in Phys Rep 52:263, 1979)—with observations distributed beyond the predictability horizon. They found a time limit beyond which numerical calculations are affected by numerical instability: the computability horizon. In this article, we aim at pushing forward such inherent obstacle to numerical calculations in chaotic orbit determination by applying the classical and the constrained multi-arc method (cf. Alessi et al. in Mon Not R Astron Soc 423:2270–2278, 2012) to the same dynamical system. These strategies entail the determination of an orbit when observations are grouped in separate observed arcs. For each arc, a set of initial conditions is determined and, in the case of the constrained multi-arc method, all subsequent arcs are constrained to belong to the same trajectory. We show that the use of these techniques in place of the standard least-squares method has significant advantages: Not only can we perform accurate numerical calculations well beyond the computability horizon, in particular, the constrained multi-arc strategy improves considerably the determination of the dynamical parameter.

Numerical Instruments for the Analysis of Secular Dynamics of Exoplanetary Systems

A review is given of modern numerical methods for the analysis of resonant and chaotic dynamics: calculation of the Lyapunov characteristic exponents, the MEGNO method, and the maximum eccentricity method. These methods are used to construct stability diagrams for the planetary systems γ Cep, HD 196885, and HD 41004. The diagrams are analyzed to determine the most probable values taken by the orbital parameters of the exoplanets and obtain estimates for the Lyapunov time of their orbital dynamics. The stability diagrams constructed using the different methods are compared to analyze their effectiveness in the study of secular dynamics of exoplanetary systems.

Research on Supply Chain Stability Driven by Consumer’s Channel Preference Based on Complexity Theory

At present, most of the manufacturers are increasingly laying emphasis on dual-channel selling. The level of consumer’s preference is diverse with different channels. This study discusses a supply chain where one common manufacturer uses two different channels to sell product. The bounded rationality expectation has been applied to explore the decision-making mechanism in finalizing the wholesale prices and sales commissions for the manufacturer and retailers. In addition, the dynamic features of the system are simulated by 2D bifurcation diagram, the largest Lyapunov exponent, attractor variation, and time series. The simulation results suggest that if the adjustment speeds of the wholesale prices and sales commissions change drastically, the system would fall into a chaotic state. If the consumers prefer the online channel, the wholesale prices and sales commissions may be raised and vice versa. However, too strong preference of each channel will make the system appear to have a considerably periodic fluctuation, even chaos. In the meantime, the parameter adjustment method can help make the periodic or chaotic system go back to stability. Therefore, the significance of this study is with a practical meaning to make better pricing strategy for players in dual-channel selling supply chain system.

Sparse identification of nonlinear dynamics for rapid model recovery.

Big data have become a critically enabling component of emerging mathematical methods aimed at the automated discovery of dynamical systems, where first principles modeling may be intractable. However, in many engineering systems, abrupt changes must be rapidly characterized based on limited, incomplete, and noisy data. Many leading automated learning techniques rely on unrealistically large data sets, and it is unclear how to leverage prior knowledge effectively to re-identify a model after an abrupt change. In this work, we propose a conceptual framework to recover parsimonious models of a system in response to abrupt changes in the low-data limit. First, the abrupt change is detected by comparing the estimated Lyapunov time of the data with the model prediction. Next, we apply the sparse identification of nonlinear dynamics (SINDy) regression to update a previously identified model with the fewest changes, either by addition, deletion, or modification of existing model terms. We demonstrate this sparse model recovery on several examples for abrupt system change detection in periodic and chaotic dynamical systems. Our examples show that sparse updates to a previously identified model perform better with less data, have lower runtime complexity, and are less sensitive to noise than identifying an entirely new model. The proposed abrupt-SINDy architecture provides a new paradigm for the rapid and efficient recovery of a system model after abrupt changes.

Is type 1 diabetes a chaotic phenomenon?

A database of ten type 1 diabetes patients wearing a continuous glucose monitoring device has enabled to record their blood glucose continuous variations every minute all day long during fourteen consecutive days. These recordings represent, for each patient, a time series consisting of 1 value of glycaemia per minute during 24 h and 14 days, i.e., 20,160 data points. Thus, while using numerical methods, these time series have been anonymously analyzed. Nevertheless, because of the stochastic inputs induced by daily activities of any human being, it has not been possible to discriminate chaos from noise. So, we have decided to keep only the 14 nights of these ten patients. Then, the determination of the time delay and embedding dimension according to the delay coordinate embedding method has allowed us to estimate for each patient the correlation dimension and the maximal Lyapunov exponent. This has led us to show that type 1 diabetes could indeed be a chaotic phenomenon. Once this result has been confirmed by the determinism test, we have computed the Lyapunov time and found that the limit of predictability of this phenomenon is nearly equal to half the 90 min sleep-dream cycle. We hope that our results will prove to be useful to characterize and predict blood glucose variations.

Thermal diffusivity and butterfly velocity in anisotropic Q-lattice models

We study a relation between the thermal diffusivity (DT ) and two quantum chaotic properties, Lyapunov time (τL) and butterfly velocity (vB ) in strongly correlated systems by using a holographic method. Recently, it was shown that {mathbb{E}}_i:={D}_{T,i}/left({v}_{{}^{B,i}}^2{tau}_Lright)left(i=x,yright) is universal in the sense that it is determined only by some scaling exponents of the IR metric in the low temperature limit regardless of the matter fields and ultraviolet data. Inspired by this observation, by analyzing the anisotropic IR scaling geometry carefully, we find the concrete expressions for {mathbb{E}}_i in terms of the critical dynamical exponents zi in each direction, {mathbb{E}}_i={z}_i/2left({z}_i-1right) . Furthermore, we find the lower bound of {mathbb{E}}_i is always 1/2, which is not affected by anisotropy, contrary to the η/s case. However, there may be an upper bound determined by given fixed anisotropy.

Nonlinear Dynamics of Imperfect FGM Conical Panel

Structures composed of functionally graded materials (FGM) can satisfy many rigorous requisitions in engineering application. In this paper, the nonlinear dynamics of a simply supported FGM conical panel with different forms of initial imperfections are investigated. The conical panel is subjected to the simple harmonic excitation along the radial direction and the parametric excitation in the meridian direction. The small initial geometric imperfection of the conical panel is expressed by the form of the Cosine functions. According to a power‐law distribution, the effective material properties are assumed to be graded along the thickness direction. Based on the first‐order shear deformation theory and von Karman type nonlinear geometric relationship, the nonlinear equations of motion are established by using the Hamilton principle. The nonlinear partial differential governing equations are truncated by Galerkin method to obtain the ordinary differential equations along the radial displacement. The effects of imperfection types, half‐wave numbers of the imperfection, amplitudes of the imperfection, and damping on the dynamic behaviors are studied by numerical simulation. Maximum Lyapunov exponents, bifurcation diagrams, time histories, phase portraits, and Poincare maps are obtained to show the dynamic responses of the system.

Thermal diffusivity and chaos in metals without quasiparticles

We study the thermal diffusivity $D_T$ in models of metals without quasiparticle excitations (`strange metals'). The many-body quantum chaos and transport properties of such metals can be efficiently described by a holographic representation in a gravitational theory in an emergent curved spacetime with an additional spatial dimension. We find that at generic infra-red fixed points $D_T$ is always related to parameters characterizing many-body quantum chaos: the butterfly velocity $v_B$, and Lyapunov time $\tau_L$ through $D_T \sim v_B^2 \tau_L$. The relationship holds independently of the charge density, periodic potential strength or magnetic field at the fixed point. The generality of this result follows from the observation that the thermal conductivity of strange metals depends only on the metric near the horizon of a black hole in the emergent spacetime, and is otherwise insensitive to the profile of any matter fields.

Long-term influence of asteroids on planet longitudes and chaotic dynamics of the solar system

Over timescales much longer than an orbital period, the solar system exhibits large-scale chaotic behavior and can thus be viewed as a stochastic dynamical system. The aim of the present paper is to compare different sources of stochasticity in the solar system. More precisely we studied the importance of the long term influence of asteroids on the chaotic dynamics of the solar system. We show that the effects of asteroids on planets is similar to a white noise process, when those effects are considered on a timescale much larger than the correlation time τϕ ≃ 104 yr of asteroid trajectories. We computed the timescale τe after which the effects of the stochastic evolution of the asteroids lead to a loss of information for the initial conditions of the perturbed Laplace–Lagrange secular dynamics. The order of magnitude of this timescale is precisely determined by theoretical argument, and we find that τe ≃ 104 Myr. Although comparable to the full main-sequence lifetime of the sun, this timescale is considerably longer than the Lyapunov time τi ≃ 10 Myr of the solar system without asteroids. This shows that the external sources of chaos arise as a small perturbation in the stochastic secular behavior of the solar system, rather due to intrinsic chaos.

Association between meteor showers and asteroids using multivariate criteria

Context. Meteoroid streams are fragments of matter produced by comets or asteroids which intersects the orbit of Earth. Meteor showers are produced when Earth intersects these streams of matter. The discoveries of active asteroids and extinct comets open a new view of the relation between these objects as possible parent bodies at the origin of meteor showers. Aims. The aim of this work is to identify the asteroids that can produce or re-populate meteoroid streams by determining the similarity of their orbits and orbital evolution over 10 000 yr.Methods. The identification was carried out by evaluating several well known D -criteria metrics, the orbits being taken from the IAU Meteor Data Center database and from IAU Minor Planet Center. Finally, we analyzed the physical properties and the orbital stability (in the Lyapunov time sense) of the candidates as well as their possible relationship with meteorites.Results. 206 near-Earth asteroids (NEAs) were associated as possible parent bodies with 28 meteor showers, according to at least two of the criterion used. 50 of them satisfied all the criteria. Notable finds are: binary asteroid 2000UG11 associated with Andromedids (AND), while the tumbling asteroid (4179)Toutatis could be associated with October Capricornids (OCC). Other possible good candidates are 2004TG10, 2008EY5, 2010CF55, 2010TU149 and 2014OY1. These objects have low albedo, therefore can be primitive objects. Asteroid 2007LW19 which is a fast rotator and most probably has monolithic structure and so its physical characteristic does not support the association found based on the dynamical criteria.