Numerical Approximation of a 4D System of ODE's

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Discussion Overview

The discussion centers on methods for numerically approximating a system of ordinary differential equations (ODEs) with four variables (x, y, z, t). The focus is on finding general methods that meet specific conditions regarding the explicit definition of differentials and the treatment of time as linear.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant outlines the requirements for the ODEs, emphasizing the need for explicit definitions of differentials and a linear treatment of time.
  • Another participant suggests that a 4-stage Runge-Kutta method is effective for explicit coupled ODEs that are not too stiff, but indicates that stiff equations may require specialized solvers.
  • A request for recommendations on implicit methods is made, highlighting a preference for generality and a willingness to accept more complex algorithms.
  • One participant proposes the backward Euler method as a starting point, noting its unconditional stability and classification as an implicit method.

Areas of Agreement / Disagreement

Participants express differing views on the appropriateness of explicit versus implicit methods, with some advocating for explicit methods while others explore implicit options. The discussion remains unresolved regarding the best approach for the given conditions.

Contextual Notes

Participants have not fully defined the limitations of their proposed methods, and there is an acknowledgment of the complexity involved in implicit methods versus the simplicity of explicit methods.

Who May Find This Useful

This discussion may be useful for researchers or practitioners interested in numerical methods for solving systems of ODEs, particularly those dealing with higher-dimensional systems and the trade-offs between explicit and implicit approaches.

TylerH
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What is the most general method of approximating arbitrary systems of ODEs of 4 variables(x,y,z,t) that fit these conditions? The conditions that are assumed true of the ODEs are:
1) that I require differentials to be explicitly defined (but they can be defined in terms of other differentials).
2) that time is assumed linear (ei, it's a 3 variable system described in terms of 4, but the 4th is known)

That is:
dx=y^2+sin(x)
dy=-dz+y*t
dz=t*z

would be valid, because dx,dy, and dz are explicitly defined and alone on one side.

dx=f(dx)

would be invalid, because I don't want to solve implicit equations.

f(dx,x,y,z,t) = g(x,y,z,t)

would be invalid, because I don't want to have to move all the junk to the other side to get an explicit definition of dx.
 
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A (4-stage) Runge-Kutta method usually works pretty well for systems of explicit coupled ode's that are not too stiff. If your equation becomes very stiff, you probably need to switch to specialized stiff solvers, which are usually (semi-)implicit.
 
What are some implicit methods that you would recommend? With generality being the most favored quality. I'm okay with the algorithm being harder and slower, it's all going to be precomputed anyway.

When I said I didn't want to solve implicit equations, I was only really talking about avoiding symbolic math.

Thanks for the response.
 
You could start with the backward Euler method, it is unconditionally stable and the easiest of a large class of implicit methods (adams-moulton)
 

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