Bifurcation, Chaos, Multistability, Sensitivity, and Dynamic Properties to the Third Fractional WBBM Equation

This study investigates the dynamics of dust acoustic periodic waves in a three-component, unmagnetized dusty plasma system using generalized (r⋆,q⋆) distributions. First, boundary conditions are applied to reduce the model to a second-order nonlinear ordinary differential equation. The Galilean transformation is subsequently applied to reformulate the second-order ordinary differential equation into an unperturbed dynamical system. Next, phase portraits of the system are examined under all possible conditions of the discriminant of the associated cubic polynomial, identifying regions of stability and instability. The Runge–Kutta method is employed to construct the phase portraits of the system. The Hamiltonian function of the unperturbed system is subsequently derived and used to analyze energy levels and verify the phase portraits. Under the influence of an external periodic perturbation, the quasi-periodic and chaotic dynamics of dust ion acoustic waves are explored. Chaos detection tools confirm the presence of quasi-periodic and chaotic patterns using Basin of attraction, Lyapunov exponents, Fractal Dimension, Bifurcation diagram, Poincaré map, Time analysis, Multi-stability analysis, Chaotic attractor, Return map, Power spectrum, and 3D and 2D phase portraits. In addition, the model’s response to different initial conditions was examined through sensitivity analysis.

Bifurcation, chaos, modulation instability, and solitons are important phenomena in nonlinear dynamical structures that help us understand complex physical processes. This work employs the Schrödinger equation with cubic nonlinearity (SECN), rising in superconductivity, quantum mechanics, optics, and plasma physics. We developed an ordinary differential arrangement using a traveling wave alteration and found the soliton outcome to the mentioned problem utilizing the unified solver technique. Then we obtain different categories of wave designs, including bright and dark solitons, with periodic, quasiperiodic, and chaotic behaviors. We examined the system’s planar dynamics to observe sensitivity, chaos, and bifurcation. The chaotic state involves various procedures such as multistability, recurrence diagrams, bifurcation shapes, fractal dimensions, return maps, Poincaré graphics, Lyapunov exponents, phase portraits, and strange attractors. These properties help us understand complicated behaviors like how waves become chaotic patterns. Our outcomes demonstrate a clear understanding of wave propagation and how energy is absorbed. These findings develop our knowledge of nonlinear problems and guide us in wave circulation in real-life situations. Therefore, our procedures are useful and operative offering a simple technique for studying nonlinear problems, which progresses our understanding of these equations’ sensitivity, waveform pattern, and propagation strategy.

This paper investigates the explicit, accurate soliton and dynamic strategies in the resolution of the Wazwaz–Benjamin–Bona–Mahony (WBBM) equations. By exploiting the ensuing wave events, these equations find applications in fluid dynamics, ocean engineering, water wave mechanics, and scientific inquiry. The two main goals of the study are as follows: Firstly, using the dynamic perspective, examine the chaos, bifurcation, Lyapunov spectrum, Poincaré section, return map, power spectrum, sensitivity, fractal dimension, and other properties of the governing equation. Secondly, we use a generalized rational exponential function (GREF) technique to provide a large number of analytical solutions to nonlinear partial differential equations (NLPDEs) that have periodic, trigonometric, and hyperbolic properties. We examining the wave phenomena using 2D and 3D diagrams along with a projection of contour plots. Through the use of the computational program Mathematica, the research confirms the computed solutions to the WBBM equations.

This paper uses the unified solver process to acquire soliton outcomes for the fractional Phi-4 model. The dynamic characteristic of the governing model is investigated for its planar dynamical system by applying the bifurcation method. Under the given parameters, 2D and 3D phase portraits, time series, return map, Lyapunov exponent, recurrence plot, strange attractor, bifurcation diagram, and fractal dimension plot are provided. These plots show the periodic, quasi-periodic, and chaotic nature of the suggested nonlinear problem. Moreover, the sensitivity and multistability assessments of the stated model are studied for a clear understanding of chaotic behavior. To understand the system’s long-term behavior, we also test the stability of our results. Our results agree with previous results and may help researchers better understand the behavior of nonlinear systems. Furthermore, other fields such as biology, economics, and engineering can apply our results.

The existence of strange nonchaotic attractors (SNAs) is verified in a simple quasiperiodically-forced piecewise smooth system with Farey tree. It can be seen that more and more jumping discontinuities appear on the smooth torus and the torus becomes extremely fragmented with the change of control parameter. Finally, the torus becomes an SNA with fractal property. In order to confirm the existence of SNAs in this system, we preliminarily use the estimation of the phase sensitivity exponent, estimation of the largest Lyapunov exponent and rational approximation. SNAs are further characterized by power spectra, recurrence plots, the largest Lyapunov exponents and their variance, the distribution of the finite-time Lyapunov exponents, the spectral distribution function and scaling laws.

Parallel-pumping experiments in two ferromagnets, YIG and (CH3NH3)2CuCl4 (abbreviated as MACC) have been performed at a pumping frequency of 9 GHz band at liquid-helium temperatures. Above the spin-wave instability threshold, auto-oscillations of magnon number which include period-doubling and period-halving bifurcations, chaos, and periodic windows are observed. From experimental time-series data, return maps, fractal dimensions, positive Lyapunov exponents, phase space portraits of strange attractors, and two-dimensional Poincare sections are obtained. A Lyapunov exponent is one of the quantitative measures of a strange attractor. Lyapunov exponents are obtained by analyzing experimental return maps as 0.34 for YIG and 0.21 for MACC. Phase space trajectories, i.e., strange attractors, are constructed by the conventional time-delay method. The successive Poincare sections of the strange attractors exhibit the stretching and folding effects of sheets of trajectories which confirms the fractal characteristics of the strange attractors. The fractal dimensions of the attractors are obtained by the correlation integral method to be 2.0 for YIG and 2.3 for MACC.

Preface. Introduction. Fractals: A cantor set. The Koch triadic island. Fractal dimensions. The logistic map: The linear map. The fixed points and their stability. Period two. The period doubling route to chaos. Feigenbaum's constants. Chaos and strange attractors. The critical point and its iterates. Self similarity, scaling and univerality. Reversed bifurcations. Crisis. Lyapunov exponents. Dimensions of attractors. Tangent bifurcations and intermittency. Exact results at ^D*l = 1. Poincar^D'e maps and return maps. The circle map: The fixed points. Circle maps near K = 0. Arnol'd tongues. The critical value K = 1. Period two, bimodality, superstability and swallow tails. Where can there be chaos? Higher dimensional maps: Linear maps in higher dimensions. Manifolds. Homoclinic and hetroclinic points. Lyapunov exponents in higher dimensional maps. The Kaplan-Yorke conjecture. The Hopf bifurcation. Dissipative maps in higher dimensions: The Henon map. The complex logistic map. Two dimensional coupled logistic map. Conservative maps: The twist map. The KAM theorem. The rings of Saturn. Cellular automata. Ordinary differential equations: Fixed points. Linear stability analysis. Homoclinic and hetroclinic orbits. Lyapunov exponents for flows. Hopf bifurcations for flows. The Lorenz model. Time series analysis: Fractal dimension from a time series. Autoregressive models. Rescaled range analysis. The global temperature - an example. Appendices. Further reading. Index.

This study sought to deepen our understanding of the dynamical properties of the newly extended (3+1)-dimensional integrable Kadomtsev–Petviashvili (KP) equation, which models the behavior of ion acoustic waves in plasmas and nonlinear optics. This paper aimed to perform Lie symmetry analysis and derive lump, breather, and soliton solutions using the extended hyperbolic function method and the generalized logistic equation method. It also analyzed the dynamical system using chaos detection techniques such as the Lyapunov exponent, return maps, and the fractal dimension. Initially, we focused on constructing lump and breather soliton solutions by employing Hirota’s bilinear method. Secondly, employing Lie symmetry analysis, symmetry generators were utilized to satisfy the Lie invariance conditions. This approach revealed a seven-dimensional Lie algebra for the extended (3+1)-dimensional integrable KP equation, incorporating translational symmetry (including dilation or scaling) as well as translations in space and time, which were linked to the conservation of energy. The analysis demonstrated that this formed an optimal sub-algebraic system via similarity reductions. Subsequently, a wave transformation method was applied to reduce the governing system to ordinary differential equations, yielding a wide array of exact solitary wave solutions. The extended hyperbolic function method and the generalized logistic equation method were employed to solve the ordinary differential equations and explore closed-form analytical solitary wave solutions for the diffusive system under consideration. Among the results obtained were various soliton solutions. When plotting the results of all the solutions, we obtained bright, dark, kink, anti-kink, peak, and periodic wave structures. The outcomes are illustrated using 2D, 3D, and contour plots. Finally, upon introducing the perturbation term, the system’s behavior was analyzed using chaos detection techniques such as the Lyapunov exponent, return maps, and the fractal dimension. The results contribute to a deeper understanding of the dynamic properties of the extended KP equation in fluid mechanics.

The Gross–Pitaevskii equation is widely known for its applications in fields such as Bose–Einstein condensates and optical fibres. This study investigates the dynamical behaviour of various wave solutions to the M-fractional nonlinear Gross–Pitaevskii equation. Soliton solutions are derived using the GREFM, and the results are illustrated through 3D surface and contour plots. Furthermore, we apply the Galilean transformation to convert the second-order ordinary differential equation into a dynamical system and conduct bifurcation and sensitivity analyses. A perturbation term is introduced into the system to investigate the chaotic behaviour, Poincaré and time series analysis. The presence of chaos is further confirmed by using fractal dimension, return maps, power spectra and Lyapunov exponents. Additionally, we investigate multistability by analyzing the system’s response to various initial conditions. These contributions support the development of robust simulation tools for analyzing fractional dynamical systems in nonlinear optics and quantum mechanics.

This study explores the novel dynamics of the (3+1)-dimensional generalized Korteweg–de Vries–Zakharov–Kuznetsov (KdV-ZK) equation. A Galilean transformation is employed to derive the associated system of equations. Perturbing this system allows us to investigate the presence and characteristics of chaotic behavior, including return maps, fractal dimension, power spectrum, recurrence plots, and strange attractors, supported by 2D and time-dependent phase portraits. A sensitivity analysis is demonstrated to show how the system behaves when there are small changes in initial values. Finally, the planar dynamical system method is used to derive anti-kink, dark soliton, and kink soliton solutions, advancing our understanding of the range of solutions admitted by the model.

Chaotic dynamics of a behavior-based miniature mobile robot: effects of environment and control structure

This work finds new exact soliton solutions to the fractional space-time higher-order nonlinear Schrödinger equation, describing how tiny pulses move through a nonlinear system. First, we transform this nonlinear fractional differential equation into an ordinary differential framework using the beta derivative and a traveling wave transformation. Then, we find analytical solutions using the unified solver method. Along with this, a thorough stability analysis is done using the Hamiltonian technique. Afterward, we study the chaotic analysis of the stated model using planner dynamics and show two- and three-dimensional phase illustrations, Lyapunov exponents, Poincaré maps, bifurcation figures, fractal dimensions, strange attractors, recurrence plots, and return maps as graphical representations regarding this chaotic analysis. Finally, we ensure that these precise solitons provide the internal complex image of wave travel.

Science, engineering, medicine, biology, and many other areas deal with signals acquired in the form of time series from different dynamical systems for the purpose of analysis, diagnosis, and control of the systems. The signals are often mixed with noise. Separating the noise from the signal may be very difficult if both the signal and the noise are broadband. The problem becomes inherently difficult when the signal is chaotic because its power spectrum is indistinguishable from broadband noise. This paper describes how to measure and analyze chaos using Lyapunov metrics. The principle of characterizing strange attractors by the divergence and folding of trajectories is studied. A practical approach to evaluating the largest local and global Lyapunov exponents by rescaling and renormalization leads to calculating the m Lyapunov exponents for m-dimensional strange attractors either modeled explicitly (analytically) or reconstructed from experimental time-series data. Several practical algorithms for calculating Lyapunov exponents are summarized. Extensions of the Lyapunov exponent approach to studying chaos are also described briefly as they are capable of dealing with the multiscale nature of chaotic signals. The extensions include the Lyapunov fractal dimension, the Kolmogorov--Sinai and Re/spl acute/nyi entropies, as well as the Re/spl acute/nyi fractal dimension spectrum and the Mandelbrot fractal singularity spectrum.

In this paper we investigate numerically the possibility of conversion of a chaotic attractor into a nonchaotic but strange attractor in both a discrete system (an one dimensional map) and in a continuous dynamical system — Bonhoeffer—van der Pol oscillator. In these systems we show suppression of chaotic property, namely, the sensitive dependence on initial states, by adding appropriate i) chaotic signal and ii) Gaussian white noise. The controlled orbit is found to be strange but nonchaotic with largest Lyapunov exponent negative and noninteger correlation dimension. Return map and power spectrum are also used to characterize the strange nonchaotic attractor.

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.