Numerical methods for systems of differential equations

In summary, the conversation discusses an implicit method for solving equations, specifically the equation xj+1=xj+h/2(f(tj,xj)+f(tj+h,xj+1)). The main questions addressed are finding an appropriate Runge-Kutta scheme for this method, determining the method's rank when used with the equation x'=ax, and calculating its stability area. The conversation also includes a request for help in preparing for a test.
  • #1
mkerikss
18
0

Homework Statement


Consider the implicit (not actually sure wether that's the correct english word, my material is in Finnish and I'm Swedish-speaking :smile:) method
xj+1=xj+h/2(f(tj,xj)+f(tj+h,xj+1))

a)Write an appropriate Runge-Kutta scheme
b) What is the methods rank when we use the equation x'=ax ? I have absolutely no clue if rank is the correct word but it is a number that describes some kind of order. Unfortunately I can't describe it better than that because I don't really know what it is and that is one of my questions.
c)What is the methods stability area?

The Attempt at a Solution



In a), I'm not sure if the different numerical methods have different schemes, but one I've used in an earlier exercise is

__t____________t1_____t2_______tn
x1
x2
:
:
xn

Is this correct?

In b), I'm really lost. I've figured out that x'=f(x)=ax. The one previous time I've done an exercise about "rank" the solution was to use Taylor expansions, and then all x, x', x'' eventually disappeared, which if I recall correctly implies that the rank is 2. But I have no idea how to do that in this particular exercise.

I've also seen one example of calculating stability areas. Just to check that I have understood correctly, does this mean that I can write an equation where xj+1=Anx0, solve A:s eigenvalues and their absolute values have to be <1. Then I can solve h. Or is this a different situation?

Thanks for your help!
 
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  • #2
Anyone? I'm preparing for a test tomorrow and would appreciate your help :smile:
 

1. What are numerical methods for systems of differential equations?

Numerical methods for systems of differential equations are techniques used to solve systems of equations that describe the rate of change of a system over time. These methods involve breaking down the system into smaller, simpler equations that can be solved using numerical techniques.

2. Why are numerical methods necessary for solving systems of differential equations?

Systems of differential equations can be very complex and difficult to solve analytically. Numerical methods provide a way to approximate the solutions to these equations, making it possible to solve even the most complex systems.

3. What are some common numerical methods used for solving systems of differential equations?

Some common numerical methods include Euler's method, Runge-Kutta methods, and multistep methods. These methods use a combination of approximation and iteration to find solutions to the system of equations.

4. How accurate are numerical methods for solving systems of differential equations?

The accuracy of numerical methods depends on the complexity of the system and the specific method used. Generally, the more steps and iterations that are used, the more accurate the solution will be. However, numerical methods can never provide exact solutions, only approximations.

5. Are there any limitations to using numerical methods for systems of differential equations?

Yes, there are limitations to using numerical methods. These methods can only provide approximations, and the accuracy of these approximations can be affected by the initial conditions, step size, and other variables. Additionally, some systems may be too complex for numerical methods to accurately approximate.

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