Eigenvalue method for solving system of differential equations

In summary: I didn't know that either. I guess I was just assuming that since the real part was just a number it would be easy to just take it.
  • #1
theBEAST
364
0

Homework Statement


Here is the question along with my work. I attempted to solve for the actual solution using both eigenvectors. From what I have been taught it should yield the same answer... But as you can see (circled in red) the solutions are clearly different. Is this normal or maybe because I am making an algebra mistake?

I know for sure the solution in attempt 1 is correct because that is what wolfram alpha gives me. But attempt 2 for some reason has a different answer.
WRwEq.jpg
 
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  • #2
I really don't understand what you mean by "solving with V1" and "solving with V2". The general solution, from which you get the solution with the given initial values, must be a linear combination of V1 and[ V2. You cannot get a solution from either one alone.
 
  • #3
HallsofIvy said:
I really don't understand what you mean by "solving with V1" and "solving with V2". The general solution, from which you get the solution with the given initial values, must be a linear combination of V1 and[ V2. You cannot get a solution from either one alone.

This is not true. You can retrieve a real valued solution from either [itex]x^{(1)}[/itex] or [itex]x^{(2)}[/itex] by taking the real parts of either one by using Euler's formula.
 
  • #4
Zondrina said:
This is not true. You can retrieve a real valued solution from either [itex]x^{(1)}[/itex] or [itex]x^{(2)}[/itex] by taking the real parts of either one by using Euler's formula.

Yup, take a look at the first example from Pauls notes. They said you only need one eigenvector:

http://tutorial.math.lamar.edu/Classes/DE/ComplexEigenvalues.aspx

So am I doung something wrong or am I suppose to get a slightly different answer?
 
  • #5
In your solution with [itex]v_2[/itex], you should have substituted [itex]\mu = -3\sqrt 3[/itex] into the your formula. Since [itex]\sin(-3\sqrt3 t) = - \sin(3 \sqrt 3 t)[/itex], the result is that every term multiplied by [itex]\sin (3 \sqrt3 t)[/itex] has the wrong sign.

Make that correction and you should get the same result as with [itex]v_1[/itex].
 
Last edited:
  • #6
Zondrina said:
This is not true. You can retrieve a real valued solution from either [itex]x^{(1)}[/itex] or [itex]x^{(2)}[/itex] by taking the real parts of either one by using Euler's formula.

Wow! After doing these for such a long time I did not know that. I always thought you just took the magnitude of the eigenvalue... At least that's what it looked like in the generic formula I wrote and copied from the professor.

Thanks!
 

1. What is the eigenvalue method for solving systems of differential equations?

The eigenvalue method is a mathematical technique used to solve systems of differential equations. It involves finding the eigenvalues and eigenvectors of a matrix associated with the system of equations, and using these values to determine a general solution.

2. When is the eigenvalue method used?

The eigenvalue method is commonly used when solving systems of linear differential equations, particularly in the field of mathematics and engineering. It is also used in physics and other scientific disciplines.

3. How does the eigenvalue method work?

The eigenvalue method involves setting up a matrix of coefficients for the system of differential equations. The eigenvalues and eigenvectors of this matrix are then calculated, and these values are used to form a general solution to the system of equations.

4. What are the advantages of using the eigenvalue method?

One advantage of the eigenvalue method is that it can be used to find a general solution to a system of differential equations, rather than just a specific solution for a given set of initial conditions. It is also a useful tool for solving systems of linear equations in a more efficient and organized way.

5. Are there any limitations to the eigenvalue method?

The eigenvalue method is not applicable to all types of differential equations. It is specifically designed for linear systems, and may not be effective for nonlinear systems. Additionally, the method may become more complex and difficult to use for larger systems with many variables and equations.

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