Symplectic runge kutta for hamiltonian system

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Discussion Overview

The discussion revolves around the implementation of symplectic Runge-Kutta methods for solving the restricted three-body problem in a Hamiltonian framework. Participants explore the advantages of symplectic integrators in preserving invariants over long time integrations compared to traditional methods.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant describes their attempt to solve the restricted three-body problem using a Hamiltonian that is time-independent, expressing uncertainty about symplectic methods and their implementation.
  • Another participant confirms that symplectic algorithms respect invariants and suggests that standard Runge-Kutta methods may suffice for short time integrations but may not be suitable for long periods.
  • Resources for symplectic integration in MATLAB are mentioned, including a specific toolbox and a tutorial, indicating that such tools can aid in understanding and applying these methods.
  • A participant highlights the importance of symplectic integrators in maintaining stability in Hamiltonian systems, noting that they represent exact solutions of some Hamiltonians, albeit not necessarily the user's specific Hamiltonian.
  • Visual evidence of the differences in results from various integration methods is referenced, with a link to an image showing variations in the Jacobi constant over time.

Areas of Agreement / Disagreement

Participants generally agree on the benefits of symplectic integrators for long-term stability in Hamiltonian systems, but there is no consensus on the specifics of implementation or the best approach for the user's particular Hamiltonian.

Contextual Notes

Participants express varying levels of familiarity with symplectic methods, indicating a potential gap in understanding the underlying concepts and practical applications. The discussion includes references to specific algorithms and tools, but no detailed mathematical derivations or proofs are provided.

Who May Find This Useful

This discussion may be useful for students and researchers interested in numerical methods for Hamiltonian systems, particularly those exploring symplectic integration techniques and their applications in celestial mechanics.

Heimdall
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Hi !


I'm trying to solve the restricted problem of three bodies, where a negligeable mass particule is moving in the gravitationnal field of two heavy objects which are in circular orbit around their common center of mass. this is a plane problem...

I describe the mouvment in the mobile referential in order to have an time independent hamiltonian, which is the following :



[tex]H = \frac{1}{2} ( P^2_1+P^2_2 ) + P_1Q_2-P_2Q_1 - (\frac{1-\mu}{R_1} + \frac{\mu}{R_2})[/tex]

where Q1,2 and P1,2 are the position and momenta of the object one and two respectively.

I found out that, since the energy is an invariant of this problem, there was a numerical algorithm which was better to use : symplectic method.

I don't know much about it, I just know it is better than classical RK4 (even with variable time step) because it preserves invariants and 'symplectic form' (I don't really know what it is...)


I'm french student in 2nd cycle physics studies, I learned hamiltonian formalism this year, but not the "symplectic" notion... therefore, I don't really know how to code a symplectic integrator.

I didn't see a lot of web sites which could help me, just things like "Candy-Rozmus algorithm" which I don't really understand.

I found an exemple of a symplectic runge kutta function on the web
"http://aristote.obspm.fr/phynum/libphynum/lib1.html"

the code is here in this package : http://aristote.obspm.fr/phynum/libphynum/libphn.tar.gz


I'm looking for some help to understand this...

Thank you
 
Last edited:
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hum, sorry nobody knows something ?
 
hi heimdall, as u rightly pointed out, symplecting algorithms respect the 'invariants' in the problem.
following the std RG methods will give you reasonable results unless u want to integrate for very long periods .
there are many symplecting integration toolboxes available for matlab.
one of them is
http://www.ii.uib.no/diffman.

it also comes with a decent tutorial(or try 'symplectinc integration' on google's scholar)

to see the difference...look at this image where i have shown the variation the jacobi constant with time(this ofcourse is an artifact of the integration)
I used the integrator available in matlab.
look at
http://www.ae.iitm.ac.in/~ae03b005/jacobi.png
 
Last edited by a moderator:
oops..i forgot to add a point..the hill curve in the third curve is for cj=3.02 ..the max that is reached in the integration...the initial conditions actually corresspond to a cj=2.9998
 
Heimdall said:
hum, sorry nobody knows something ?

I can tell you a little bit. A symplectic integrator will represent the exact solution of some Hamiltonian. It won't be YOUR Hamiltonian, however. As you take smaller and smaller time steps, the symplectic integrator will solve a problem that's closer and closer to the actual problem you are intersted in.

The fact that the solution will actually be the exact solution of some Hamiltonian is useful for avoiding some types of obnoxious behaviors.

Symplectic integrators are especially useful where one is interested in the stability of a system.
 

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