Symplectic partitioned Runge-Kutta method based onthe eighth-order nearly analytic discrete operator and its wavefield simulations

We propose a symplectic partitioned Runge-Kutta （SPRK） method with eighth-order spatial accuracy based on the extended Hamiltonian system of the acoustic waveequation. Known as the eighth-order NSPRK method, this technique uses an eighth-orderaccurate nearly analytic discrete （NAD） operator to discretize high-order spatial differentialoperators and employs a second-order SPRK method to discretize temporal derivatives.The stability criteria and numerical dispersion relations of the eighth-order NSPRK methodare given by a semi-analytical method and are tested by numerical experiments. We alsoshow the differences of the numerical dispersions between the eighth-order NSPRK methodand conventional numerical methods such as the fourth-order NSPRK method, the eighth-order Lax-Wendroff correction （LWC） method and the eighth-order staggered-grid （SG）method. The result shows that the ability of the eighth-order NSPRK method to suppress thenumerical dispersion is obviously superior to that of the conventional numerical methods. Inthe same computational environment, to eliminate visible numerical dispersions, the eighth-order NSPRK is approximately 2.5 times faster than the fourth-order NSPRK and 3.4 timesfaster than the fourth-order SPRK, and the memory requirement is only approximately47.17% of the fourth-order NSPRK method and 49.41% of the fourth-order SPRK method,which indicates the highest computational efficiency. Modeling examples for the two-layermodels such as the heterogeneous and Marmousi models show that the wavefields generatedby the eighth-order NSPRK method are very clear with no visible numerical dispersion.These numerical experiments illustrate that the eighth-order NSPRK method can effectivelysuppress numerical dispersion when coarse grids are adopted. Therefore, this methodcan greatly decrease computer memory requirement and accelerate the forward modelingproductivity. In general, the eighth-order NSPRK method has tremendous potential value forseismic exploration and seismology research.

Numerical Dispersion Relation of Multi-symplectic Runge-Kutta Methods for Hamiltonian PDEs

Numerical dispersion relation of the multi-symplectic Runge-Kutta （MSRK） method for linear Hamiltonian PDEs is derived in the present paper, which is shown to be a discrete counterpart to that possessed by the differential equation. This provides further understanding of MSRK methods. However, much still remains to be investigated further.

Runge-Kutta method, finite element method, and regular algorithms for Hamiltonian system

The symplectic algorithm and the energy conservation algorithm are two important kinds of algorithms to solve Hamiltonian systems. The symplectic Runge- Kutta （RK） method is an important part of the former, and the continuous finite element method （CFEM） belongs to the later. We find and prove the equivalence of one kind of the implicit RK method and the CFEM, give the coefficient table of the CFEM to simplify its computation, propose a new standard to measure algorithms for Hamiltonian systems, and define another class of algorithms --the regular method. Finally, numerical experiments are given to verify the theoretical results.

A SIMPLE WAY CONSTRUCTING SYMPLECTICRUNGE-KUTTA METHODS

Presents a study which derived a way of constructing symplectic methods with the help of symplecticity conditions of partitioned Runge-Kutta methods. Classes of symplectic Runge-Kutta methods; Relationship between Runge-Kutta methods.

Algebraic dynamics algorithm:Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Based on the exact analytical solution of ordinary differential equations, a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm. A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models. The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision, and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

Construction of Symplectic Runge-Kutta Methods for Stochastic Hamiltonian Systems

We study the construction of symplectic Runge-Kutta methods for stochastic Hamiltonian systems(SHS).Three types of systems,SHS with multiplicative noise,special separable Hamiltonians and multiple additive noise,respectively,are considered in this paper.Stochastic Runge-Kutta(SRK)methods for these systems are investigated,and the corresponding conditions for SRK methods to preserve the symplectic property are given.Based on the weak/strong order and symplectic conditions,some effective schemes are derived.In particular,using the algebraic computation,we obtained two classes of high weak order symplectic Runge-Kutta methods for SHS with a single multiplicative noise,and two classes of high strong order symplectic Runge-Kutta methods for SHS with multiple multiplicative and additive noise,respectively.The numerical case studies confirm that the symplectic methods are efficient computational tools for long-term simulations.

Symmetric-Adjoint and Symplectic-Adjoint Runge-Kutta Methods and Their Applications

Symmetric and symplectic methods are classical notions in the theory of numerical methods for solving ordinary differential equations.They can generate numerical flows that respectively preserve the symmetry and symplecticity of the continuous flows in the phase space.This article is mainly concerned with the symmetric-adjoint and symplectic-adjoint Runge-Kutta methods as well as their applications.It is a continuation and an extension of the study in[14],where the authors introduced the notion of symplectic-adjoint method of a Runge-Kutta method and provided a simple way to construct symplectic partitioned Runge-Kutta methods via the symplectic-adjoint method.In this paper,we provide a more comprehensive and systematic study on the properties of the symmetric-adjoint and symplecticadjoint Runge-Kutta methods.These properties reveal some intrinsic connections among some classical Runge-Kutta methods.Moreover,those properties can be used to significantly simplify the order conditions and hence can be applied to the construction of high-order Runge-Kutta methods.As a specific and illustrating application,we construct a novel class of explicit Runge-Kutta methods of stage 6 and order 5.Finally,with the help of symplectic-adjoint method,we thereby obtain a new simple proof of the nonexistence of explicit Runge-Kutta method with stage 5 and order 5.

ORDER PROPERTIES AND CONSTRUCTION OF SYMPLECTIC RUNGE-KUTTA METHODS

The main results of this paper are as follows: (1) Suppose an s stage Runge-Kutta method is consistent, irreducible, non-confluent and symplectic. Then this method is of order at least 2p + l(1 less than or equal to p less than or equal to s - 1) provided that the simplifying conditions C(p) (or D(p) with non-zero weights) and B(2p + l) hold, where 1 0, 1, 2. (2) Suppose an s stage Runge-Kutta method is consistent, irreducible and non-confluent, and satisfies the simplifying conditions C(p) and D(p) with 0 < p <less than or equal to> s. Then this method is symplectic if and only if either p = s or the nonlinear stability matrix M of the method has an (s - p) x (s - p) chief submatrix (M) over cap = 0. (3) Using the results (1) and (2) as bases, we present a general approach for the construction of symplectic Runge-Kutta methods, and a software has been designed, by means of which, the coefficients of s stage symplectic Runge-Kutta methods satisfying C(p),D(p) and B(2p + l) can be easily computed, where 1 I P less than or equal to s, 0 less than or equal to l less than or equal to 2, s less than or equal to 2p + l less than or equal to 2s.

基于复频移完全匹配层的辛龙格库塔算法探地雷达正演

为了消除探地雷达(ground penetrating radar,GPR)正演模拟的截断边界处的非物理反射,需要对模拟区域边界进行特殊处理。目前应用效果较好的边界处理方法为加载完全匹配层吸收边界条件。而复频移完全匹配层(complex frequency shift perfectly matched layer,CFS-PML)可以加强对低频区凋落波、倏失波的吸收效果,还可以压制信号的虚假反射,被引入到GPR正演边界条件处理中。将CFS-PML应用于辛龙格库塔求解二维GPR波动方程的数值模拟中,利用辛算法可以实现对时间坐标和空间坐标的保辛计算,从而实现GPR高精度正演模拟。首先,以横磁(transverse magnetic,TM)波为例,推导了基于CFS-PML的辛龙格库塔GPR波动方程求解公式。其次,利用狭长模型开展了CFS-PML吸收边界条件中的关键参数的选取试验,通过对比反射误差的大小确定了最优参数。此外,通过CFS-PML吸收边界条件与透射边界条件的对比实验,说明大角度掠射下CFS-PML边界条件较透射边界具有更好的吸收效果。最后,为了进一步验证该算法的效果,应用加载CFS-PML边界的辛龙格库塔算法对一个具有起伏地形的地电模型进行了正演。通过剖面法和宽角法得到的正演剖面图,证明该算法具有较好的GPR正演精度。

辛算法数值求解一维薛定谔方程特征值

将一维薛定谔方程利用Legendre变换转化为等价哈密顿正则方程,采取辛格式数值求解莫尔斯势场和谐振子势场下一维薛定谔方程特征值的数值解,并做了数值比较,最后给出了特征值对应的波函数图像.

基于辛RKN技术的FDTD方法

高阶辛时域有限差分法(S-FDTD)的稳定度及计算精度都较传统的时域有限差分法(FDTD)更为优越,在长时间数值仿真中的优势更加明显。本文从电磁场方程的Hamilton函数出发,提出了一种基于辛Runge-Kutta-Nystr m(SRKN)算法的S-FDTD方法,对该方法的稳定性和数值色散性进行了系统的探讨。计算结果表明与传统的高阶S-FDTD方法——辛Partitioned-Runge-Kutta(SPRK)比较,该方法计算速度和计算精度都有较大的提高。

Symmetric and symplectic methods for gyrocenter dynamics in time-independent magnetic fields

We apply a second-order symmetric Runge–Kutta method and a second-order symplectic Runge–Kutta method directly to the gyrocenter dynamics which can be expressed as a noncanonical Hamiltonian system.The numerical simulation results show the overwhelming superiorities of the two methods over a higher order nonsymmetric nonsymplectic Runge–Kutta method in long-term numerical accuracy and near energy conservation.Furthermore,they are much faster than the midpoint rule applied to the canonicalized system to reach given precision.

Symplectic Analysis on Coupling Behaviors of Spatial Fiexible Damping Beam

Although the complex structure-preserving method presented in our previous studies can be used to investigate the orbit–attitude–vibration coupled dynamic behaviors of the spatial flexible damping beam,the simulation speed still needs to be improved.In this paper,the infinite-dimensional dynamic model describing the orbit–attitude–vibration coupled dynamic problem of the spatial flexible damping beam is pretreated by the method of separation of variables,and the second-level fourth-order symplectic Runge–Kutta scheme is constructed to investigate the coupling dynamic behaviors of the spatial flexible damping beam quickly.Compared with the simulation speed of the complex structure-preserving method,the simulation speed of the symplectic Runge–Kutta method is faster,which benefits from the pretreatment step.The effect of the initial radial velocity on the transverse vibration as well as on the attitude evolution of the spatial flexible damping beam is presented in the numerical examples.From the numerical results about the effect of the initial radial velocity,it can be found that the appearance of the initial radial velocity can decrease the vibration frequency of the spatial beam and shorten the evolution interval for the attitude angle to tend towards a stable value significantly.In addition,the validity of the numerical results reported in this paper is verified by comparing with some numerical results presented in our previous studies.

Explicit Multi-Symplectic Methods for Hamiltonian Wave Equations

In this paper,based on the multi-symplecticity of concatenating symplectic Runge-Kutta-Nystrom(SRKN)methods and symplectic Runge-Kutta-type methods for numerically solving Hamiltonian PDEs,explicit multi-symplectic schemes are constructed and investigated,where the nonlinear wave equation is taken as a model problem.Numerical comparisons are made to illustrate the effectiveness of our newly derived explicit multi-symplectic integrators.

MSPRK Methods for the Korteweg-de Vries Equation

We consider the Korteweg-de Vries （KdV） equation in the form ut＋uux＋uxxx=0,（1） which is a nonlinear hyperbolic equation and has smooth solutions for all the time. There are a vast of results can be found in the literature for this equation, both theoretical and numerical. However, several good reasons account for needs of another numerical study of this equation are listed in [1].

Predictive Mathematical and Statistical Modeling of the Dynamic Poverty Problem in Burundi: Case of an Innovative Economic Optimization System

The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dynamic of the poverty in Burundi. The Burundian economy shows an inflation rate of -1.5% in 2018 for the Gross Domestic Product growth real rate of 2.8% in 2016. In this research, the aim is to find a model that contributes to solving the problem of poverty in Burundi. The results of this research fill the knowledge gap in the modeling and optimization of the Burundian economic system. The aim of this model is to solve an optimization problem combining the variables of production, consumption, budget, human resources and available raw materials. Scientific modeling and optimal solving of the poverty problem show the tools for measuring poverty rate and determining various countries’ poverty levels when considering advanced knowledge. In addition, investigating the aspects of poverty will properly orient development aid to developing countries and thus, achieve their objectives of growth and the fight against poverty. This paper provides a new and innovative framework for global scientific research regarding the multiple facets of this problem. An estimate of the poverty rate allows good progress with the theory and optimization methods in measuring the poverty rate and achieving sustainable development goals. By comparing the annual food production and the required annual consumption, there is an imbalance between different types of food. Proteins, minerals and vitamins produced in Burundi are sufficient when considering their consumption as required by the entire Burundian population. This positive contribution for the latter comes from the fact that some cows, goats, fishes, ···, slaughtered in Burundi come from neighboring countries. Real production remains in deficit. The lipids, acids, calcium, fibers and carbohydrates produced in Burundi are insufficient for consumption. This negative contribution proves a Burundian food deficit. It is a decision-making indicator for the design and updating of agricultural policy and implementation programs as well as projects. Investment and economic growth are only possible when food security is mastered. The capital allocated to food investment must be revised upwards. Demographic control is also a relevant indicator to push forward Burundi among the emerging countries in 2040. Meanwhile, better understanding of the determinants of poverty by taking cultural and organizational aspects into account guides managers for poverty reduction projects and programs.

基于高精度NAD算子的SPRK方法及二维弹性波场模拟

针对具有哈密尔顿系统的二维弹性波方程,使用具有八阶精度的近似解析离散算子离散空间高阶偏导数,利用有着二阶精度的辛分部Runge-Kutta方法离散时间导数,得到了八阶NAD-SPRK方法。利用该方法模拟二维弹性波分别在均匀横向各向同性介质、双层均匀各向同性介质、双层非均匀介质和含起伏间断面的三层介质中的传播。波场模拟结果表明,八阶NAD-SPRK方法能有效地压制粗网格和强间断介质条件下引起的数值频散,PML吸收边界条件同八阶NAD-SPRK方法有机结合能有效地衰减来自人工边界的反射波。

A Novel Class of Energy-Preserving Runge-Kutta Methods for the Korteweg-de Vries Equation

In this paper,we present a quadratic auxiliary variable approach to develop a new class of energy-preserving Runge-Kutta methods for the Korteweg-de Vries equation.The quadratic auxiliary variable approach is first proposed to reformulate the original model into an equivalent system,which transforms the energy conservation law of the Korteweg-de Vries equation into two quadratic invariants of the reformulated system.Then the symplectic Runge-Kutta methods are directly employed for the reformulated model to arrive at a new kind of time semi-discrete schemes for the original problem.Under consistent initial conditions,the proposed methods are rigorously proved to maintain the original energy conservation law of the Korteweg-de Vries equation.In addition,the Fourier pseudo-spectral method is used for spatial discretization,resulting in fully discrete energy-preserving schemes.To implement the proposed methods effectively,we present a very efficient iterative technique,which not only greatly saves the calculation cost,but also achieves the purpose of practically preserving structure.Ample numerical results are addressed to confirm the expected order of accuracy,conservative property and efficiency of the proposed algorithms.

ENERGY AND QUADRATIC INVARIANTS PRESERVING METHODS FOR HAMILTONIAN SYSTEMS WITH HOLONOMIC CONSTRAINTS

We introduce a new class of parametrized structure–preserving partitioned RungeKutta(α-PRK)methods for Hamiltonian systems with holonomic constraints.The methods are symplectic for any fixed scalar parameterα,and are reduced to the usual symplectic PRK methods like Shake-Rattle method or PRK schemes based on Lobatto IIIA-IIIB pairs whenα=0.We provide a new variational formulation for symplectic PRK schemes and use it to prove that theα-PRK methods can preserve the quadratic invariants for Hamiltonian systems subject to holonomic constraints.Meanwhile,for any given consistent initial values(p0,q0)and small step size h>0,it is proved that there existsα∗=α(h,p0,q0)such that the Hamiltonian energy can also be exactly preserved at each step.Based on this,we propose some energy and quadratic invariants preservingα-PRK methods.Theseα-PRK methods are shown to have the same convergence rate as the usual PRK methods and perform very well in various numerical experiments.

Arbitrarily High-Order Energy-Preserving Schemes for the Camassa-Holm Equation Based on the Quadratic Auxiliary Variable Approach

In this paper,we present a quadratic auxiliary variable(QAV)technique to develop a novel class of arbitrarily high-order energy-preserving algorithms for the Camassa-Holm equation.The QAV approach is first utilized to transform the original equation into a reformulated QAV system with a consistent initial condition.Then the reformulated QAV system is discretized by applying the Fourier pseudo-spectral method in space and the symplectic Runge-Kutta methods in time,which arrives at a class of fully discrete schemes.Under the consistent initial condition,they can be rewritten as a new fully discrete system by eliminating the introduced auxiliary variable,which is rigorously proved to be energy-preserving and symmetric.Ample numerical experiments are conducted to confirm the expected order of accuracy,conservative property and efficiency of the proposed methods.The presented numerical strategy makes it possible to directly apply a special class of Runge-Kutta methods to develop energy-preserving algorithms for a general conservative system with any polynomial energy.