Using Eigenvalues and Eigenvectors to solve Differential Equations

In summary, the system of differential equations can be solved by finding the eigenvalues and eigenvectors of the matrix and using them to solve for the constants in the solution. By setting up a matrix and finding its inverse, the differential equations can be reduced to a simple form that is easy to solve.
  • #1
beckiey
1
0

Homework Statement



x1(t) and x2(t) are functions of t which are solutions of the system of differential equations

x(dot)1 = 4x1 + 3x2
x(dot)2 = -6x1 - 5x2

Express x1(t) and x2(t) in terms of the exponential function, given that x1(0) = 1 and x2(0) = 0

The Attempt at a Solution



I've already put this into matrix form,

4...3
-6 -5

and then

(4-λ) 3
-6 (-5-λ)

To find that the eigenvalues are -2 and 1, and then that the eigenvectors are

(a
-2a)

and

(b
-b)

but after that I'm completely stuck. I know you get into constants and such but I just can't remember how to continue.
 
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  • #2
beckiey said:

Homework Statement



x1(t) and x2(t) are functions of t which are solutions of the system of differential equations

x(dot)1 = 4x1 + 3x2
x(dot)2 = -6x1 - 5x2

Express x1(t) and x2(t) in terms of the exponential function, given that x1(0) = 1 and x2(0) = 0

The Attempt at a Solution



I've already put this into matrix form,

4...3
-6 -5

and then

(4-λ) 3
-6 (-5-λ)

To find that the eigenvalues are -2 and 1, and then that the eigenvectors are

(a
-2a)

and

(b
-b)

but after that I'm completely stuck. I know you get into constants and such but I just can't remember how to continue.
You can write (a, -2a)= a(1, -2) and (b, -b) as b(1, -1). Use those vectors as columns in a matrix:
[tex]A= \begin{bmatrix}1 & 1\\ -2 & -1\end{bmatrix}[/tex]
and write [begin]A^{-1}[/itex] as its inverse matrix.
Then
[tex]A^{-1}\begin{bmatrix}1 & 1 \\ -2 & -1\end{bmatrix}A= \begin{bmatrix}-2 & 0\\ 0 & 1\end{bmatrix}[/tex]

Writing your differential equation as differential equation as dY/dt= BY, We can multiply on both sides by [itex]A^{-1}[/itex] and write Y as [itex]Y= AX[/itex] so that \(\displaystyle X= A^{-1}Y\) and the differential equation becomes [itex]d(A^{-1}Y)/dt= dX/dt= A^{-1}BY= (A^{-1}BA)[/itex] which is just
[tex]\frac{dX}{dt}= \begin{bmatrix}-2 & 0 \\ 0 & 1\end{bmatrix}X[/tex]
which is easy to solve. Once you have X, then, of course, Y= AX.
 

FAQ: Using Eigenvalues and Eigenvectors to solve Differential Equations

How are eigenvalues and eigenvectors used to solve differential equations?

Eigenvalues and eigenvectors are used to find a set of solutions to a system of differential equations. By finding the eigenvalues and eigenvectors of the coefficient matrix of the system, we can express the solutions in terms of these values, making it easier to solve the equations.

What is the significance of eigenvalues and eigenvectors in solving differential equations?

Eigenvalues and eigenvectors provide a way to simplify the solutions of a system of differential equations. They allow us to express the solutions in terms of a few key values, making it easier to understand and analyze the behavior of the system.

Can eigenvalues and eigenvectors be used to solve all types of differential equations?

No, eigenvalues and eigenvectors can only be used to solve linear differential equations. Nonlinear differential equations require different methods of solution.

How do I find the eigenvalues and eigenvectors of a coefficient matrix?

To find the eigenvalues and eigenvectors, we first need to find the characteristic polynomial of the coefficient matrix. This is done by taking the determinant of the matrix minus a variable times the identity matrix. Then, we solve for the values of the variable that make the determinant equal to zero. These values are the eigenvalues. To find the eigenvectors, we substitute each eigenvalue back into the original matrix and solve for the corresponding eigenvector.

Are there any real-world applications of using eigenvalues and eigenvectors to solve differential equations?

Yes, there are many real-world applications where eigenvalues and eigenvectors are used to solve differential equations. Some examples include modeling population growth, analyzing electrical circuits, and predicting weather patterns.

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