Journal of Nonlinear Science最新文献

Localised patterns are often observed in models for dryland vegetation, both as peaks of vegetation in a desert state and as gaps within a vegetated state, known as ‘fairy circles’. Recent results from radial spatial dynamics show that approximations of localised patterns with dihedral symmetry emerge from a Turing instability in general reaction–diffusion systems, which we apply to several vegetation models. We present a systematic guide for finding such patterns in a given reaction–diffusion model, during which we obtain four key quantities that allow us to predict the qualitative properties of our solutions with minimal analysis. We consider four well-established vegetation models and compute their key predictive quantities, observing that models which possess similar values exhibit qualitatively similar localised patterns; we then complement our results with numerical simulations of various localised states in each model. Here, localised vegetation patches emerge generically from Turing instabilities and act as transient states between uniform and patterned environments, displaying complex dynamics as they evolve over time.

We study a system describing the dynamics of a two-phase flow of incompressible viscous fluids influenced by the convective heat transfer of Caginalp-type. The separation of the fluids is expressed by the order parameter which is of diffuse interface and is known as the Cahn–Hilliard model. We shall consider a nonlocal version of the Cahn–Hilliard model which replaces the gradient term in the free energy functional into a spatial convolution operator acting on the order parameter and incorporate with it a potential that is assumed to satisfy an arbitrary polynomial growth. The order parameter is influenced by the fluid velocity by means of convection; the temperature affects the interface via a modification of the Landau–Ginzburg free energy. The fluid is governed by the Navier–Stokes equations which is affected by the order parameter and the temperature by virtue of the capillarity between the two fluids. The temperature on the other hand satisfies a parabolic equation that considers latent heat due to phase transition and is influenced by the fluid via convection. The goal of this paper is to prove the global existence of weak solutions and show that, for an appropriate choice of sequence of convolutional kernels, the solutions of the nonlocal system converge to its local version.

In this paper, we are concerned with the minimal regularity of weak solutions implying the law of balance for both energy and helicity in the incompressible Euler equations. In the spirit of recent works due to Berselli (J Differ Equ 368:350–375, 2023) and Berselli and Georgiadis (Nonlinear Differ Equ Appl 31(33):1–14, 2024), it is shown that the energy of weak solutions is invariant if the velocity (vin L^{p}(0,T;B^{frac{1}{p}}_{frac{2p}{p-1},c(mathbb {N})} )) with (1<ple 3) and the helicity is conserved if (vin L^{p}(0,T;B^{frac{2}{p}}_{frac{2p}{p-1},c(mathbb {N})} )) with (2<ple 3 ) for both the periodic domain and the whole space, which generalizes the classical work of Cheskidov et al. (Nonlinearity 21:1233–1252, 2008). As an application, we deduce the upper bound of energy dissipation rate of the form (o(mu ^{frac{palpha -1}{palpha -2alpha +1}})) of Leray–Hopf weak solutions in (L^{p}( 0,T;underline{B}^{alpha }_{frac{2p}{p-1},VMO}(mathbb {T}^{d}))) in the Navier–Stokes equations, which extends recent corresponding result obtained by Drivas and Eyink (Nonlinearity 32:4465–4482, 2019).

We consider a system of interacting particles governed by the generalized Langevin equation (GLE) in the presence of external confining potentials, singular repulsive forces, as well as memory kernels. Using a Mori–Zwanzig approach, we represent the system by a class of Markovian dynamics. Under a general set of conditions on the nonlinearities, we study the large-time asymptotics of the multi-particle Markovian GLEs. We show that the system is always exponentially attractive toward the unique invariant Gibbs probability measure. The proof relies on a novel construction of Lyapunov functions. We then establish the validity of the small-mass approximation for the solutions by an appropriate equation on any finite-time window. Important examples of singular potentials in our results include the Lennard–Jones and Coulomb functions.

This work introduces a parametric model order reduction (PMOR) approach that enhances an existing widely used technique based on proper orthogonal decomposition (POD) and discrete empirical interpolation method (DEIM) for parametrized nonlinear dynamical systems by employing machine learning procedures performed on a Grassmann manifold. In particular, distances between parameters are first computed based on a metric defined on the Grassmann manifold of solution spaces. Then, the distance information is utilized in the K-medoids clustering algorithm to partition parameters into classes with corresponding local solution spaces, which are further used to form a dictionary of local bases. The artificial neural network (ANN) is next used to build a classifier that can automatically identify the most suitable local basis from the dictionary for a given input parameter to construct a parametrized reduced-order model by the POD–DEIM approach. This work numerically demonstrates the significance of using distance on the Grassmann manifold of the solution spaces, instead of directly using the Euclidean distance on the parameter space. To validate the proposed method, numerical studies are performed on a parametrized 1D Burger’s equation and a viscous fingering in a horizontal flow through a 2D porous media domain. The proposed method is shown to have advantage in terms of accuracy when compared to the traditional global basis approach, as well as the local reduced-order basis approach based on the Euclidean metric.

Understanding efficient modifications to improve network functionality is a fundamental problem of scientific and industrial interest. We study the response of network dynamics against link modifications on a weakly connected directed graph consisting of two strongly connected components: an undirected star and an undirected cycle. We assume that there are directed edges starting from the cycle and ending at the star (master–slave formalism). We modify the graph by adding directed edges of arbitrarily large weights starting from the star and ending at the cycle (opposite direction of the cutset). We provide criteria (based on the sizes of the star and cycle, the coupling structure, and the weights of cutset and modification edges) that determine how the modification affects the spectral gap of the Laplacian matrix. We apply our approach to understand the modifications that either enhance or hinder synchronization in networks of chaotic Lorenz systems as well as Rössler. Our results show that the hindrance of collective dynamics due to link additions is not atypical as previously anticipated by modification analysis and thus allows for better control of collective properties.

This paper is dedicated to investigating the chaos of a initial-boundary value (IBV) problem of a multi-dimensional weakly hyperbolic equation subject to two general nonlinear boundary conditions (NBCs). The existence and uniqueness of solution for the IBV problem are established. By employing the snap-back repeller and heteroclinic cycle theories, it has been proven that the IBV problem with a linear and a general NBCs exhibits chaos in the sense of both Devaney and Li–Yorke. Furthermore, these chaotic results are extended to the IBV problem with two general NBCs. Two stability criteria of the IBV problem are established, respectively, for the corresponding two cases of boundary conditions. Finally, numerical simulations are presented to illustrate the theoretical results.

We study the stochastic Camassa–Holm equation with pure jump noise. We prove that if the initial condition of the solution is a solitary wave solution of the unperturbed equation, the solution decomposes into the sum of a randomly modulated solitary wave and a small remainder. Moreover, we derive the equations for the modulation parameters and show that the remainder converges to the solution of a stochastic linear equation as amplitude of the jump noise tends to zero.

A main goal in the field of statistical shape analysis is to define computable and informative metrics on spaces of immersed manifolds, such as the space of curves in a Euclidean space. The approach taken in the elastic shape analysis framework is to define such a metric by starting with a reparametrization-invariant Riemannian metric on the space of parametrized shapes and inducing a metric on the quotient by the group of diffeomorphisms. This quotient metric is computed, in practice, by finding a registration of two shapes over the diffeomorphism group. For spaces of Euclidean curves, the initial Riemannian metric is frequently chosen from a two-parameter family of Sobolev metrics, called elastic metrics. Elastic metrics are especially convenient because, for several parameter choices, they are known to be locally isometric to Riemannian metrics for which one is able to solve the geodesic boundary problem explicitly—well-known examples of these local isometries include the complex square root transform of Younes, Michor, Mumford and Shah and square root velocity (SRV) transform of Srivastava, Klassen, Joshi and Jermyn. In this paper, we show that the SRV transform extends to elastic metrics for all choices of parameters, for curves in any dimension, thereby fully generalizing the work of many authors over the past two decades. We give a unified treatment of the elastic metrics: we extend results of Trouvé and Younes, Bruveris as well as Lahiri, Robinson and Klassen on the existence of solutions to the registration problem, we develop algorithms for computing distances and geodesics, and we apply these algorithms to metric learning problems, where we learn optimal elastic metric parameters for statistical shape analysis tasks.

In this paper, we propose fully discrete analogues of a generalized sine-Gordon (gsG) equation (u_{t x}=left( 1+nu partial _x^2right) sin u). The key points of the construction are based on the bilinear discrete KP hierarchy and appropriate definition of discrete reciprocal transformations. We derive semi-discrete analogues of the gsG equation from the fully discrete gsG equation by taking the temporal parameter limit (brightarrow 0). In particular, one fully discrete gsG equation is reduced to a semi-discrete gsG equation in the case of (nu =-1) (Feng et al. in Numer Algorithms 94:351–370, 2023). Furthermore, N-soliton solutions to the semi- and fully discrete analogues of the gsG equation in the determinant form are presented. Dynamics of one- and two-soliton solutions for the discrete gsG equations are analyzed. By introducing a parameter c, we demonstrate that the gsG equation can reduce to the sine-Gordon equation and the short pulse at the levels of continuous, semi-discrete and fully discrete cases. The limiting forms of the N-soliton solutions to the gsG equation in each level also correspond to those of the sine-Gordon equation and the short pulse equation.