Autonomous Ordinary Differential Equations Research Articles

Dynamic survival analysis: Modelling the hazard function via ordinary differential equations.

The hazard function represents one of the main quantities of interest in the analysis of survival data. We propose a general approach for parametrically modelling the dynamics of the hazard function using systems of autonomous ordinary differential equations (ODEs). This modelling approach can be used to provide qualitative and quantitative analyses of the evolution of the hazard function over time. Our proposal capitalises on the extensive literature on ODEs which, in particular, allows for establishing basic rules or laws on the dynamics of the hazard function via the use of autonomous ODEs. We show how to implement the proposed modelling framework in cases where there is an analytic solution to the system of ODEs or where an ODE solver is required to obtain a numerical solution. We focus on the use of a Bayesian modelling approach, but the proposed methodology can also be coupled with maximum likelihood estimation. A simulation study is presented to illustrate the performance of these models and the interplay of sample size and censoring. Two case studies using real data are presented to illustrate the use of the proposed approach and to highlight the interpretability of the corresponding models. We conclude with a discussion on potential extensions of our work and strategies to include covariates into our framework. Although we focus on examples of Medical Statistics, the proposed framework is applicable in any context where the interest lies in estimating and interpreting the dynamics of the hazard function.

Koopman Spectral Linearization vs. Carleman Linearization: A Computational Comparison Study

Nonlinearity presents a significant challenge in developing quantum algorithms involving differential equations, prompting the exploration of various linearization techniques, including the well-known Carleman Linearization. Instead, this paper introduces the Koopman Spectral Linearization method tailored for nonlinear autonomous ordinary differential equations. This innovative linearization approach harnesses the interpolation methods and the Koopman Operator Theory to yield a lifted linear system. It promises to serve as an alternative approach that can be employed in scenarios where Carleman Linearization is traditionally applied. Numerical experiments demonstrate the effectiveness of this linearization approach for several commonly used nonlinear ordinary differential equations.

A Study of Movable Singularities in Non-Algebraic First-Order Autonomous Ordinary Differential Equations

We studied the movable singularities of solutions of autonomous non-algebraic first-order ordinary differential equations in the form of y′=I(y(t)) and y′=I1(y(t))+I2(y(t))+⋯+In(y(t)), aiming to prove that all movable singularities of all complex solutions of these equations are at most algebraic branch points. This study explores the use of the constructing triangle method to analyze complex solutions of autonomous non-algebraic first-order ordinary differential equations. For complex solutions in the form of y=w+iv, we treat the constructing triangle method as a way to construct a right-angled triangle in the complex plane, with the lengths of the adjacent sides being w and v. We use the definitions of the trigonometric functions sin and cos (the ratio of the adjacent side to the hypotenuse) to represent the trigonometric functions of complex solutions y=w+iv. Since the movable singularities of the inverse functions of trigonometric functions are easy to analyze, the properties of the movable singularities of the complex solutions are then easy to deal with.

НЕЙРОННА МЕРЕЖА ТИПУ АВТОКОДУВАЛЬНИК ДЛЯ ВКЛАДЕННЯ ОДНОВИМІРНИХ ЧАСОВИХ РЯДІВ

The problem of time series embedding is a universal one. It is the main prerequisite when it comes to modeling of dynamical processes using systems of autonomous ordinary differential equations (ODEs) because they have hard requirements for the dimensionality of the problem. One-dimensional ODE can only exhibit 3 types of behavior while two-dimensional ODE can exhibit 9. This is why it is important to increase the dimensionality of the problem before starting the modeling to allow for wider range of possible behaviors in the final model. One way to increase the dimensionality is to delay-embed the time series data but this approach can be extended to allow the use of an autoencoder neural network that would associate a higher-dimensional vector to each point in the time series and will allow the modeling to be performed in higher dimension.

Integrable geodesic flows and metrisable second-order ordinary differential equations

It is well known that the system of ordinary differential equations (ODEs) describing geodesic flows of some Riemannian metrics on 2-surfaces admits a projection on a special class of second-order ODEs. In this paper we study in detail this special class of ODEs. We classify all such autonomous ODEs possessing autonomous first integrals that are fractional-quadratic in the first derivative. We construct all the families of integrable geodesic flows related to the ODEs under study. These families are parameterized by two arbitrary functions and contain metrics with superintegrable geodesic flows. We also study the inverse problem and find novel families of second-order ODEs that are related to integrable geodesic flows. We explicitly present first integrals of such ODEs. We find the general structure of metrisable second-order ODEs related to conformal metrics.

Machine learning methods for autonomous ordinary differential equations

Machine learning methods for autonomous ordinary differential equations

Periodic Center Manifolds for Nonhyperbolic Limit Cycles in ODEs

In this paper, we deal with a classical object, namely, a nonhyperbolic limit cycle in a system of smooth autonomous ordinary differential equations. While the existence of a center manifold near such a cycle was assumed in several studies on cycle bifurcations based on periodic normal forms, no proofs were available in the literature until recently. The main goal of this paper is to give an elementary proof of the existence of a periodic smooth locally invariant center manifold near a nonhyperbolic cycle in finite-dimensional ordinary differential equations by using the Lyapunov–Perron method. In addition, we provide several explicit examples of analytic vector fields admitting (non)-unique, (non)-[Formula: see text]-smooth and (non)-analytic periodic center manifolds.

Dynamics of a Leslie-Gower type predation model with non-monotonic functional response and weak Allee effect on prey

This research concerns with analysis of a class of modified predator- prey type Leslie-Gower models. The model is described by an autonomous nonlinear ordinary differential equation system. The functional response of predators is Holling IV type or non-monotone, and the growth of prey is affected by the Allee effect. An important aspect is the study of the point (0, 0) since it has a strong influence on the behavior of the system being essential for the existence and extinction of both species, although the proposed system is not define there.

Combined Newton-Gradient Method for Constrained Root-Finding in Chemical Reaction Networks

In this work, we present a fast, globally convergent, iterative algorithm for computing the asymptotically stable states of nonlinear large-scale systems of quadratic autonomous ordinary differential equations (ODE) modeling, e.g., the dynamic of complex chemical reaction networks. Toward this aim, we reformulate the problem as a box-constrained optimization problem where the roots of a set of nonlinear equations need to be determined. Then, we propose to use a projected Newton’s approach combined with a gradient descent algorithm so that every limit point of the sequence generated by the overall algorithm is a stationary point. More importantly, we suggest replacing the standard orthogonal projector with a novel operator that ensures the final solution to satisfy the box constraints while lowering the probability that the intermediate points reached at each iteration belong to the boundary of the box where the Jacobian of the objective function may be singular. The effectiveness of the proposed approach is shown in a practical scenario concerning a chemical reaction network modeling the signaling network of colorectal cancer cells. Specifically, in this scenario the proposed algorithm is proved to be faster and more accurate than a classical dynamical approach where the asymptotically stable states are computed as the limit points of the flux of the Cauchy problem associated with the ODE system.

Modifying an existing SIMIODE project to create an in-depth project requiring a written report

This article considers starting with an existing SIMIODE modeling scenario [Winkel, B. (2015). 1-031-CoolIt-ModelingScenario. SIMIODE (Version 2.0). QUBES Educational Resources. https://doi.org/10.25334/3WG8-EC31] that develops Newton's law of cooling by considering data on the cooling of a beaker of water in a room, and expanding upon it to create a longer project modeling the temperature of a building with an internal heat pump that is also subject to a sinusoidal varying outside temperature. The proposed project was undertaken early on in the course, since little background was required, and a longer project format was utilised so that students could return to the project and see direct applications of new concepts, such as autonomous vs. nonautonomous ordinary differential equations, slope fields, and Euler's method as they were introduced. The project prompt is provided as well as a detailed discussion of the motivation behind the questions. Finally, the pros and cons of requiring the students to submit a written lab report for the project are reflected upon and a sample rubric is provided.

Nonlinear Singularly Perturbed Cauchy Problem With Inner Layer

In the article, the asymptotics of the solution of the Cauchy problem for a nonlinear autonomous ordinary differential equation of the first order, which is a simple mathematical model with an inner layer, is constructed. For all theoretical calculations, evidence-based calculations in the Maple system are given.

Exact Solutions of Nonlinear Second-Order Autonomous Ordinary Differential Equations: Application to Mechanical Systems

Many physical processes can be described via nonlinear second-order ordinary differential equations and so, exact solutions to these equations are of interest as, aside from their accuracy, they may reveal beforehand key properties of the system’s response. This work presents a method for computing exact solutions of second-order nonlinear autonomous undamped ordinary differential equations. The solutions are divided into nine cases, each depending on the initial conditions and the system’s first integral. The exact solutions are constructed via a suitable parametrization of the unknown function into a class of functions capable of representing its behavior. The solution is shown to exist and be well-defined in all cases for a general nonlinear form of the differential equation. Practical properties of the solution, such as its period, time to reach an extreme value or long-term behavior, are obtained without the need of computing the solution in advance. Illustrative examples considering different types of nonlinearity present in classical physical systems are used to further validate the obtained exact solutions.

Energy translation symmetries and dynamics of separable autonomous two-dimensional ODEs

We study symmetries in the phase plane for separable, autonomous two-state systems of ordinary differential equations (ODEs). We prove two main theoretical results concerning the existence and non-triviality of two orthogonal symmetries for such systems. In particular, we show that these symmetries correspond to translations in the internal energy of the system, and describe their action on solution trajectories in the phase plane. In addition, we apply recent results establishing how phase plane symmetries can be extended to incorporate temporal dynamics to these energy translation symmetries. Subsequently, we apply our theoretical results to the analysis of three models from the field of mathematical biology: a canonical biological oscillator model, the Lotka–Volterra (LV) model describing predator–prey dynamics, and the SIR model describing the spread of a disease in a population. We describe the energy translation symmetries in detail, including their action on biological observables of the models, derive analytic expressions for the extensions to the time domain, and discuss their action on solution trajectories.

Second‐order modified positive and elementary stable nonstandard numerical methods for n$$ n $$‐dimensional autonomous differential equations

A novel technique is presented to construct and analyze second‐order modified positive and elementary stable nonstandard (SOPESN) numerical methods for solving two general classes of ‐dimensional autonomous ordinary differential equations. The new SOPESN methods are second‐order generalizations of the explicit Euler's method, thereby improving the order of accuracy of the underlying numerical method. Numerical simulations are presented to validate the theoretical results and highlight the advantages of the proposed new modified nonstandard methods over existing standard and nonstandard numerical methods.

Self-similar gravitational dynamics, singularities and criticality in 2D

We initiate a systematic study of continuously self-similar (CSS) gravitational dynamics in two dimensions, motivated by critical phenomena observed in higher dimensional gravitational theories. We consider CSS spacetimes admitting a homothetic Killing vector (HKV) field. For a general two-dimensional gravitational theory coupled to a dilaton field and Maxwell field, we find that the assumption of continuous self-similarity determines the form of the dilaton coupling to the curvature. Certain limits produce two important classes of models, one of which is closely related to two-dimensional target space string theory and the other being Liouville gravity. The gauge field is shown to produce a shift in the dilaton potential strength. We consider static black hole solutions and find spacetimes with uncommon asymptotic behaviour. We show the vacuum self-similar spacetimes to be special limits of the static solutions. We add matter fields consistent with self-similarity (including a certain model of semi-classical gravity) and write down the autonomous ordinary differential equations governing the gravitational dynamics. Based on the phenomenon of finite-time blow-up in ODEs, we argue that spacetime singularities are generic in our models. We present qualitatively diverse results from analytical and numerical investigations regarding matter field collapse and singularities. We find interesting hints of a Choptuik-like scaling law.

Saddle-Type Blow-Up Solutions with Computer-Assisted Proofs: Validation and Extraction of Global Nature

In this paper, blow-up solutions of autonomous ordinary differential equations (ODEs) which are unstable under perturbations of initial points, referred to as saddle-type blow-up solutions, are studied. Combining dynamical systems machinery (e.g., compactifications, timescale desingularizations of vector fields) with tools from computer-assisted proofs (e.g., rigorous integrators, the parameterization method for invariant manifolds), these blow-up solutions are obtained as trajectories on local stable manifolds of hyperbolic saddle equilibria at infinity. With the help of computer-assisted proofs, global trajectories on stable manifolds, inducing blow-up solutions, provide a global picture organized by global-in-time solutions and blow-up solutions simultaneously. Using the proposed methodology, intrinsic features of saddle-type blow-ups are observed: locally smooth dependence of blow-up times on initial points, level set distribution of blow-up times and decomposition of the phase space playing a role as separatrixes among solutions, where the magnitude of initial points near those blow-ups does not matter for asymptotic behavior. Finally, singular behavior of blow-up times on initial points belonging to different family of blow-up solutions is addressed.

Low-rank kernel approximation of Lyapunov functions using neural networks

<p style='text-indent:20px;'>We study the use of single hidden layer neural networks for the approximation of Lyapunov functions in autonomous ordinary differential equations. In particular, we focus on the connection between this approach and that of the meshless collocation method using reproducing kernel Hilbert spaces. It is shown that under certain conditions, an optimised neural network is functionally equivalent to the RKHS generalised interpolant solution corresponding to a kernel function that is implicitly defined by the neural network. We demonstrate convergence of the neural network approximation using several numerical examples, and compare with approximations obtained by the meshless collocation method. Finally, motivated by our theoretical and numerical findings, we propose a new iterative algorithm for the approximation of Lyapunov functions using single hidden layer neural networks.</p>

Persistence of the heteroclinic loop under periodic perturbation

<abstract><p>We consider an autonomous ordinary differential equation that admits a heteroclinic loop. The unperturbed heteroclinic loop consists of two degenerate heteroclinic orbits $ \gamma_1 $ and $ \gamma_2 $. We assume the variational equation along the degenerate heteroclinic orbit $ \gamma_i $ has $ {d_i}\left({{d_i} > 1, i = 1, 2} \right) $ linearly independent bounded solutions. Moreover, the splitting indices of the unperturbed heteroclinic orbits are $ s $ and $ -s $ $ (s\geq 0) $, respectively. In this paper, we study the persistence of the heteroclinic loop under periodic perturbation. Using the method of Lyapunov-Schmidt reduction and exponential dichotomies, we obtained the bifurcation function, which is defined from $ \mathbb{R}^{d_1+d_2+2} $ to $ \mathbb{R}^{d_1+d_2} $. Under some conditions, the perturbed system can have a heteroclinic loop near the unperturbed heteroclinic loop.</p></abstract>

Dynamics of a Mechanical System with Curve of Equilibria: Cosymmetry and Multistability

We analyze the effects of extreme multistability in a mechanical system which describes the movement of an idealized ball over a surface like a Mexican hat. The mathematical model is given by a system of autonomous ordinary differential equations with parameters. In particular cases of rotational symmetry and cosymmetry, the system has a curve of asymptotically stable equilibria. The symmetry gives a circle of equilibria with identical stability spectra, whereas the cosymmetry produces an ellipse of equilibria with nonidentical properties. The destruction of both symmetry and cosymmetry leads to a finite number of equilibria (multistability). We study the dynamics for conservative (without dissipation) and dissipative (linear damping) cases using analytical methods and computer simulation. We found interesting effects caused by extreme multistability: nontrivial selection of equilibria of the family, high sensitivity to initial data because of memory about conservative chaos, and essential difference in dynamics in rotational symmetry and cosymmetry cases.

Chaotic Cattaneo-LTNE porous convection

The chaotic convection in a porous medium has been studied with a local thermal nonequilibrium (LTNE) model and hyperbolic-type heat transport equation in the solid arising due to Cattaneo heat flux law. The Brinkman-extended Darcy model is considered to describe the flow in a porous medium. A system of autonomous nonlinear ordinary differential equations is derived by using a truncated double Fourier series expansion such that the linear stability theory results are the same as those for the full two-dimensional problem. The stability of equilibrium points of the system is discussed in detail for the governing parameters involved therein. The transition to chaos in different phase planes and the transient behavior of heat transfer are analyzed by solving the model equations numerically using the Runge-Kutta-Fehlberg technique. The effect of increasing scaled solid thermal relaxation time parameter is to speed up the transition to chaos and to decrease the heat transfer.