Finding a vector associated with an eigenvalue

In summary, the conversation discusses finding a general solution to a system using the method (A - \lambdaI)V2 = V1. This involves finding the characteristic equation and using it to solve for the eigenvalues. The method is then used to find a and b in the system, which can be used to find the general solution for x_1 and x_2. The conversation also briefly touches on vector spaces and fields, which are concepts from Linear Algebra.
  • #1
Zem
33
0
Find a general solution of the given system using the method (A - [tex]\lambda[/tex]I)V2 = V1.

[tex]x'_1 = 2x_1 - 5x_2, x'_2 = 4x_1 - 2x_2[/tex]
[tex]x' =
\left(\begin{array}{cc}2&-5\\4&-2\end{array}\right)[/tex]

characteristic equation:
(2 - [tex]\lambda[/tex])((-2) - [tex]\lambda[/tex]) + 20 = 0
[tex]\lambda[/tex]^2 + 16 = 0
[tex]\lambda[/tex] = 4i

Using this method:
(A - 4i[tex]\lambda[/tex])V_2 = V_1
[tex]\left(\begin{array}{cc}2-4i&-5\\4&-2-4i\end{array}\right) *[/tex] [tex]\left(\begin{array}{cc}a\\b\end{array}\right) = [/tex] [tex]\left(\begin{array}{cc}0\\0\end{array}\right) [/tex]

(2 - 4i)a - 5b = 0
4a - (-2 - 4i)b = 0

When there are no complex roots, I can set a or b = 1 to find the value of the other. And when I row reduce this in my ti89, I get

[tex]\left(\begin{array}{cc}1&i 0\\0&0 0\end{array}\right) [/tex] with a space between the i and 0 in the top row, and the two 0's in the 2nd row.

How do I find a and b in this problem? When I find their values I will have V_1.
 
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  • #2
What is your vector space [itex]V[/itex], and what field [itex]F[/itex] is it over? For the moment I'm going to assume [itex]V = \mathbb{C}^2[/itex] and [itex]F= \mathbb{C}[/itex].

Also, it is not stated but you must mean that [itex]x_1', x_2'[/itex] are the coordinates of the image of [itex](x_1,x_2)[/itex] under the linear operator [itex]T[/itex] defined by the equations you have for [itex]x_1', x_2'[/itex]. ie:

[tex] T(x_1,x_2) = (x_1', x_2') [/tex]

(By the way, have you verified that [itex]T[/itex] is in fact linear?)

Zem said:
Using this method:
(A - 4i[tex]\lambda[/tex])V_2 = V_1
[tex]\left(\begin{array}{cc}2-4i&-5\\4&-2-4i\end{array}\right) *[/tex] [tex]\left(\begin{array}{cc}a\\b\end{array}\right) = [/tex] [tex]\left(\begin{array}{cc}0\\0\end{array}\right) [/tex]

(2 - 4i)a - 5b = 0
4a - (-2 - 4i)b = 0
There is a sign error here, this should be:

(2 - 4i)a - 5b = 0
4a + (-2 - 4i)b = 0

When there are no complex roots, I can set a or b = 1 to find the value of the other. And when I row reduce this in my ti89, I get

How do I find a and b in this problem? When I find their values I will have V_1.
You don't need a calculator to do this. Simply choose one of the above two equations and solve for one of the variables in terms of the other. As a check, plug that value into the other equation (you should get an identity). You'll end up with an equation for a in terms of b (or vice versa). Choose a value for a or b that makes (a, b) non-zero, and voila, you have an eigenvector for your linear operator corresponding to the eigenvalue [itex]\lambda = 4i[/itex].

edit: Re-reading your question, it asks for a *general* solution, so you can leave your answer in terms of a or b, just be sure to include the proper restrictions on a or b so that your answer gives only the non-zero solutions.
 
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  • #3
Originally Posted by nocturnal
You don't need a calculator to do this. Simply choose one of the above two equations and solve for one of the variables in terms of the other. As a check, plug that value into the other equation (you should get an identity). You'll end up with an equation for a in terms of b (or vice versa). Choose a value for a or b that makes (a, b) non-zero, and voila, you have an eigenvector for your linear operator corresponding to the eigenvalue .
My problem was that I was stuck on assigning b = 1, but it appears much better to make b = a's coefficient.
When I set [tex]b = (2-4i), a = 5[/tex], so
[tex]V_1 = \left(\begin{array}{cc}5\\2-4i\end{array}\right)[/tex]
:cool:
 
  • #4
Did you see the edit at the bottom of my post? The problem states that its looking for the *general* solution, so you wanto to find the set of all such vectors that satisfy this equation.
 
  • #5
Yes, I was just stuck in the middle of the problem. Now all I have to do is put the real and complex parts of the solutions together to get the general solutions of x_1 and x_2. Piece of cake.

I am curious, though, what you were saying about [tex]T[/tex] and [tex]F[/tex]. Is that stuff for linear algebra? We did not cover anything regarding vectors over fields or [tex]T[/tex]. Perhaps I should have mentioned that this was an ODE homework problem.
Thanks!
 
  • #6
Zem said:
I am curious, though, what you were saying about [tex]T[/tex] and [tex]F[/tex]. Is that stuff for linear algebra? We did not cover anything regarding vectors over fields or [tex]T[/tex]. Perhaps I should have mentioned that this was an ODE homework problem.
Thanks!
Yes, those are terms from Linear Algebra. Essentially a vector space is a set of "vectors" satisfying certain properties. The vectors can be acted on by "scalars" (elements of a field - another set satisfying certain properties). A Linear Operator is a function satisfying certain properties that maps a vector space into itself. It is in the context of Linear Operators that we talk about eigenvectors and eigenvalues. If you take Linear Algebra they will go into great detail about these concepts.
 
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What is an eigenvalue?

An eigenvalue is a special number associated with a square matrix. It represents the scalar by which a particular vector is scaled when multiplied by the matrix.

What is a vector associated with an eigenvalue?

A vector associated with an eigenvalue is a non-zero vector that, when multiplied by a square matrix, gives a scalar multiple of itself. This vector is also known as an eigenvector.

How do you find a vector associated with an eigenvalue?

To find a vector associated with an eigenvalue, you can use the eigenvalue-eigenvector equation: Av = λv, where A is the square matrix, v is the eigenvector, and λ is the eigenvalue. You can also use methods such as the characteristic polynomial or Gaussian elimination to find the eigenvectors.

Why is it important to find a vector associated with an eigenvalue?

Finding a vector associated with an eigenvalue is important because it allows us to understand the behavior of a given matrix. Eigenvectors are used in many mathematical and scientific fields, such as physics, engineering, and data analysis, to solve complex problems and make predictions.

Can a matrix have multiple vectors associated with the same eigenvalue?

Yes, a matrix can have multiple vectors associated with the same eigenvalue. This is because the eigenvalue-eigenvector equation has infinitely many solutions, and any scalar multiple of an eigenvector is also an eigenvector.

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