5. Integration method for Hamiltonian system. In many of formulas (e.g. the classical RK4), the errors in conserved quantities (energy, angular momentum)

Slides:



Advertisements
Similar presentations
Quantum Harmonic Oscillator
Advertisements

Geometric Integration of Differential Equations 1. Introduction and ODEs Chris Budd.
Geometric Integration of Differential Equations 2. Adaptivity, scaling and PDEs Chris Budd.
Formal Computational Skills
Molecular dynamics in different ensembles
LINCS: A Linear Constraint Solver for Molecular Simulations Berk Hess, Hemk Bekker, Herman J.C.Berendsen, Johannes G.E.M.Fraaije Journal of Computational.
Integration Techniques
Computational Methods in Physics PHYS 3437
Ordinary Differential Equations
1cs542g-term Notes. 2 Solving Nonlinear Systems  Most thoroughly explored in the context of optimization  For systems arising in implicit time.
1cs542g-term Notes  Notes for last part of Oct 11 and all of Oct 12 lecture online now  Another extra class this Friday 1-2pm.
MAT 594CM S10Fundamentals of Spatial ComputingAngus Forbes Week 2 : Dynamics & Numerical Methods Goal : To write a simple physics simulation Topics: Intro.
Total Recall Math, Part 2 Ordinary diff. equations First order ODE, one boundary/initial condition: Second order ODE.
CSE245: Computer-Aided Circuit Simulation and Verification Lecture Note 5 Numerical Integration Spring 2010 Prof. Chung-Kuan Cheng 1.
1 EE 616 Computer Aided Analysis of Electronic Networks Lecture 12 Instructor: Dr. J. A. Starzyk, Professor School of EECS Ohio University Athens, OH,
Computer-Aided Analysis on Energy and Thermofluid Sciences Y.C. Shih Fall 2011 Chapter 6: Basics of Finite Difference Chapter 6 Basics of Finite Difference.
Initial-Value Problems
1 EE 616 Computer Aided Analysis of Electronic Networks Lecture 12 Instructor: Dr. J. A. Starzyk, Professor School of EECS Ohio University Athens, OH,
Harvard University - Boston University - University of Maryland Numerical Micromagnetics Xiaobo TanJohn S. Baras P. S. Krishnaprasad University of Maryland.
Chapter 16 Integration of Ordinary Differential Equations.
CISE301_Topic8L31 SE301: Numerical Methods Topic 8 Ordinary Differential Equations (ODEs) Lecture KFUPM (Term 101) Section 04 Read , 26-2,
Numerical Methods for Partial Differential Equations CAAM 452 Spring 2005 Lecture 2 Instructor: Tim Warburton.
Numerical Solution of Ordinary Differential Equation
MATH 685/ CSI 700/ OR 682 Lecture Notes Lecture 10. Ordinary differential equations. Initial value problems.
1 Chapter 6 Numerical Methods for Ordinary Differential Equations.
Vibrational Spectroscopy
Boyce/DiPrima 9th ed, Ch 8.4: Multistep Methods Elementary Differential Equations and Boundary Value Problems, 9th edition, by William E. Boyce and Richard.
Numerical Integration Methods
CHAPTER 6 Quantum Mechanics II
Numerical Computations in Linear Algebra. Mathematically posed problems that are to be solved, or whose solution is to be confirmed on a digital computer.
Erin Catto Blizzard Entertainment Numerical Integration.
Chang-Kui Duan, Institute of Modern Physics, CUPT 1 Harmonic oscillator and coherent states Reading materials: 1.Chapter 7 of Shankar’s PQM.
EE3561_Unit 8Al-Dhaifallah14351 EE 3561 : Computational Methods Unit 8 Solution of Ordinary Differential Equations Lesson 3: Midpoint and Heun’s Predictor.
Javier Junquera Molecular dynamics in the microcanonical (NVE) ensemble: the Verlet algorithm.
Modeling and simulation of systems Numerical methods for solving of differential equations Slovak University of Technology Faculty of Material Science.
Increasing asymptotic stability of Crank-Nicolson method Alexei A. Medovikov Vyacheslav I. Lebedev.
Modelling & Simulation of Chemical Engineering Systems Department of Chemical Engineering King Saud University 501 هعم : تمثيل الأنظمة الهندسية على الحاسب.
Integration of 3-body encounter. Figure taken from
6. Introduction to Spectral method. Finite difference method – approximate a function locally using lower order interpolating polynomials. Spectral method.
Programming assignment #2 Solving a parabolic PDE using finite differences Numerical Methods for PDEs Spring 2007 Jim E. Jones.
7. Introduction to the numerical integration of PDE. As an example, we consider the following PDE with one variable; Finite difference method is one of.
(1) Experimental evidence shows the particles of microscopic systems moves according to the laws of wave motion, and not according to the Newton laws of.
Serge Andrianov Theory of Symplectic Formalism for Spin-Orbit Tracking Institute for Nuclear Physics Forschungszentrum Juelich Saint-Petersburg State University,
Rieben IMA Poster, 05/11/ UC Davis /LLNL/ ISCR High Order Symplectic Integration Methods for Finite Element Solutions to Time Dependent Maxwell Equations.
PHYS 773: Quantum Mechanics February 6th, 2012
Numerical Analysis – Differential Equation
1 EE 616 Computer Aided Analysis of Electronic Networks Lecture 12 Instructor: Dr. J. A. Starzyk, Professor School of EECS Ohio University Athens, OH,
Announcements Read Chapters 11 and 12 (sections 12.1 to 12.3)
Please remember: When you me, do it to Please type “numerical-15” at the beginning of the subject line Do not reply to my gmail,
Lecture 40 Numerical Analysis. Chapter 7 Ordinary Differential Equations.
ECE 576 – Power System Dynamics and Stability Prof. Tom Overbye Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign.
Ordinary Differential Equations
CHAPTER 6 Quantum Mechanics II
Lecture 39 Numerical Analysis. Chapter 7 Ordinary Differential Equations.
MODULE 13 Time-independent Perturbation Theory Let us suppose that we have a system of interest for which the Schrödinger equation is We know that we can.
Effective Hamiltonian Operations Condensing Physics to Conserve Over Time Joseph Knips.
Higher Order Runge-Kutta Methods for Fluid Mechanics Problems Abhishek Mishra Graduate Student, Aerospace Engineering Course Presentation MATH 6646.
Chapter 30.
Integrators of higher order
ECE 576 – Power System Dynamics and Stability
Perturbation Methods Jeffrey Eldred
CSE245: Computer-Aided Circuit Simulation and Verification
Class Notes 19: Numerical Methods (2/2)
CSE 245: Computer Aided Circuit Simulation and Verification
Try Lam 25 April 2007 Aerospace and Mechanical Engineering
CSE245: Computer-Aided Circuit Simulation and Verification
Boundary value problems:
Physics 319 Classical Mechanics
Stationary State Approximate Methods
Presentation transcript:

5. Integration method for Hamiltonian system. In many of formulas (e.g. the classical RK4), the errors in conserved quantities (energy, angular momentum) accumulate in time. A numerical integration scheme that conserves the energy may be suitable for solving particular problems. ex) A long-term stability of the planetary system. Symplectic integration method and Symmetric integration method are known to have this property. Comparison of 2 nd order symplectic method and Runge-Kutta method Consider the integration of Hamiltonian system in which the energy is conserved.

Hamiltonian system has pure imaginary eigenvalue, When a stable numerical method is applied, an oscillatory solution often tends to be dumped or diverges. If the region of stability of the method includes the imaginary axis, the numerical solution oscillates correctly. Cf.) Some methods suitable for 2 nd order ODEs. Stormer-Cowell method. Extremely high precision formulas O(h 14 ), O(h 16 ) are used in the celestial mechanics. Amount of floating operations, memory, are about a half of Adams methods. Ex) Verlet Method : Runge-Kutta-Nystroem method. Better accuracy for the same level RK formula, less memory. Exc 5-1) Show that the Verlet method and leap flog method are the same.

Hamiltonian system. Hamilton’s equation. Rewriting Hamilton’s equation, a formal solution is written The operator exp[tD H ] is well defined in the following sense;

Symplectic formula.

Exponential law for the non-commutative operators. Symplectic integration formula approximate this infinite products by finite products as The number of product, k, is taken large enough to have a desirable order truncation error O(h n+1 ). (For this formula, the local truncation error is  = O(h n ).) Exc 5-3) Check if the symplectic formulas generated by the symplectic maps are the same. Exc 5-2) Show that the 2 nd order symplectic formula is the same as the Verlet method.

Why the symplectic formula conserves energy? Exc 5-4) Integrate harmonic oscillator using some symplectic formulas, as well as the other non-symplectic formula of the same order. Then compare the conservation of the energy in time. This means that the symplectic formula is associated with the Hamiltonian of the different dynamical system.

Some systematic decomposition method for the exponential products. (1) (2) (3) Formulas (2) and (3) are symmetric, S n (h) S n (-h) = 1

Symplectic formula with symmetric decomposition. Formulas (2) and (3) becomes (2) (3)

A few drawback of the symplectic formula – Difficult to change the time step size h. Once change the step size, the formula is no more symplectic. – floating operation is way more than the multistep method of comparable order. Symmetric integration formulas Symmetric formula – the error in the energy is bounded similar to symplectic formula. – No difficulty in changing the time step size h. Ex) Trapezoidal formula

Symmetric integration formulas (continue) – An implicit formula. Symmetric. – Direct iteration can be used. – relatively simple coding and decent accuracy. Exc 5-5) Derive the above 2 nd order Hermite formula – Method for changing step size in symmetric formula. – Stability of symmetric formula – linear stability and P-stability.