What are the eigenvalues and eigenvectors of matrix A = [2 2; 3 1]?

In summary, the eigenvalues and eigenvectors of matrix A are -1, 4. When lambda = 4, I get -2x + 2y = 4x and 3x - 3y = 4y. I get the eigenvector corresponding to eigenvalue 4 when x = 3.
  • #1
fuzzyorama
13
0
Eigenvalues & Eigenvectors !SOLVED!

Homework Statement


Find the eigenvalues and eigenvectors of matrix
[tex] A = \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right) [/tex]

Homework Equations


[tex] Ax = \lambda x [/tex]

The Attempt at a Solution


Solving
[tex] \left\vert \begin{array}{cc} 2 - \lambda & 2 \\ 3 & 1 - \lambda \end{array} \right\vert [/tex]
I get the eigenvalues [tex] \lambda = -1, 4[/tex]

When [tex] \lambda = 4[/tex]

[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

Then I get these equations [tex] -2x + 2y = 4x \mbox{~and~} 3x -3y = 4y [/tex]
From the first equation, [tex] y = 3x [/tex]. So is

[tex] x\left( \begin{array}{c} 4 \\ 12 \end{array} \right) [/tex] the eigenvector?
 
Last edited:
Physics news on Phys.org
  • #2
fuzzyorama said:

Homework Statement


Find the eigenvalues and eigenvectors of matrix
[tex] A = \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right) [/tex]

Homework Equations


[tex] Ax = \lambda x [/tex]

The Attempt at a Solution


Solving
[tex] \left\vert \begin{array}{cc} 2 - \lambda & 2 \\ 3 & 1 - \lambda \end{array} \right\vert [/tex]
I get the eigenvalues [tex] \lambda = -1, 4[/tex]

When [tex] \lambda = 4[/tex]

[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

Then I get these equations [tex] -2x + 2y = 4x \mbox{~and~} 3x -3y = 4y [/tex]
From the first equation, [tex] y = 3x [/tex]. So is

[tex] x\left( \begin{array}{c} 4 \\ 12 \end{array} \right) [/tex] the eigenvector?
That will certainly work. But remember that the set of all eigenvectors, corresponding to a given eigenvalue, form a subspace- there is no such thing as the eigenvector, there are an infinite number of them. Any multiple of an eigenvector is also an eigenvector. Here you got y= 3x. Any reason for then taking x= 4? The fact that the eigenvalue is 4 (if that's where you got the "4") does not imply that x must be 4. I might be inclined to take x= 1 so that y= 3(1) and the eigenvector is
[tex]\left(\begin{array}{c}1 \\ 3\end{array}\right)[/tex]
or you might divide that by its length, [itex]\sqrt{10}[/itex] to get a unit length eigenvector,
[tex]\left(\begin{array}{c}\frac{1}{\sqrt{10}}\\ \frac{3}{\sqrt{10}}\end{array}\right)[/tex]
Any of those are eigenvectors corresponding to eigenvalue 4. Now, what are the eigenvectors corresponding to eigenvalue -1?
 
  • #3
Here you got y= 3x. Any reason for then taking x= 4? The fact that the eigenvalue is 4 (if that's where you got the "4") does not imply that x must be 4. I might be inclined to take x= 1 so that y= 3(1) and the eigenvector is
[tex] \left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex]

I thought that just by replacing the y in
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

with 3x would give me the eigenvector. I then multiplied it with the eigenvalue 4 and took the x out. So the eigenvector can also be
[tex] \left(\begin{array}{c}2 \\ 6\end{array}\right) \left(\begin{array}{c}3 \\ 9\end{array}\right) \left(\begin{array}{c}5 \\ 15\end{array}\right) [/tex] ?
Now, what are the eigenvectors corresponding to eigenvalue -1?

When [tex] \lambda = -1 [/tex], I get
[tex] \left( \begin{array}{cc} 3 & 2 \\ 3 & 2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = -\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

and the equations 3x + 2y = -x and 3x +2y = -y. From these two equations I get y = x so the eigenvector is [tex] -\left(\begin{array}{c}1 \\ 1\end{array}\right) [/tex] ?
 
  • #4
Your work is easy enough to check, and you should do this. If [itex]\lambda[/itex] is an eigenvalue with associated eigenvector x, then Ax better be equal to [itex]\lambda[/itex]x. If not, then you have a mistake.
 
  • #5
OMG I got a typo. a22 should be -3. Apologies.

[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -3 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]
If [tex] \lambda [/tex] is an eigenvalue with associated eigenvector x, then Ax better be equal to [tex] \lambda x [/tex]. If not, then you have a mistake.

From what I understand, by that you mean from the equation
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -3 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

where the eigenvector is
[tex] \left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex]
I can replace the x with 1 and y with 3:
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -3 \end{array} \right)\left( \begin{array}{c} 1 \\ 3 \end{array} \right) = 4\left( \begin{array}{c} 1 \\ 3 \end{array} \right) [/tex]
Solving the [tex] Ax [/tex] part, I get
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -3 \end{array} \right)\left( \begin{array}{c} 1 \\ 3 \end{array} \right) = \left( \begin{array}{c} -2(1) + 2(3) \\ 3(1) + (-3)(3) \end{array} \right) = \left( \begin{array}{c} 4 \\ -6 \end{array} \right) [/tex]
but it doesn't equal to
[tex] \lambda x = \left( \begin{array}{c} 4(1) \\ 4(3) \end{array} \right) = \left( \begin{array}{c} 4 \\ 12 \end{array} \right)[/tex]

Does this mean I got it wrong?
 
  • #6
No, you're looking at [tex]Ax = \lambda x[/tex] where x is your eigenvector and lambda is your eigenvalue and A is still your original [tex] A = \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right) [/tex]. You plug in your eigenvector at this point and verify you get the vector back multiplied by its respective eigenvalue.

The reason you don't have simply 1 eigenvector is that you can start as [tex]Ax = \lambda x[/tex] and say, let your new eigenvector be 3x where x is what you call "the eigenvector", that is [tex]A(3x) = \lambda (3x)[/tex] which gives you [tex] 3Ax = 3\lambda x[/tex] which is simply [tex]Ax = \lambda x[/tex] still, thus any multiple of the eigenvector you found is another eigenvector.
 
  • #7
Ahh.. so I don't actually need to multiply the eigenvector with the eigenvalue to see if they are equal?
 
  • #8
fuzzyorama said:
Ahh.. so I don't actually need to multiply the eigenvector with the eigenvalue to see if they are equal?

Yes you still need to. Remember, the idea here is finding a vector that when acted upon by your matrix A, you return the vector multiplied by the eigenvalue. No matter what constant you multiply your eigenvector by, that is x -> cx where c is a constant, when you multiply from the left with A you still must return that eigenvalue multiplied by cx.
 
  • #9
Oh wait!
No, you're looking at [tex] Ax = \lambda x [/tex] where x is your eigenvector and lambda is your eigenvalue and A is still your original [tex] A = \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right) [/tex]

[tex] \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right)\left(\begin{array}{c}1 \\ 3\end{array}\right) = 4\left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex]
[tex] \left(\begin{array}{c}8 \\ 6\end{array}\right) = \left(\begin{array}{c} 4 \\ 12 \end{array}\right) [/tex]

But it doesn't matter because both are multiples of [tex] \left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex] ?
 
  • #10
fuzzyorama said:
Oh wait!


[tex] \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right)\left(\begin{array}{c}1 \\ 3\end{array}\right) = 4\left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex]
[tex] \left(\begin{array}{c}8 \\ 6\end{array}\right) = \left(\begin{array}{c} 4 \\ 12 \end{array}\right) [/tex]

But it doesn't matter because both are multiples of [tex] \left(\begin{array}{c}1 \\ 3\end{array}\right) [/tex] ?

No, they must be exact. You're still using the wrong eigenvectors, I thought you realized that earlier when you mentioned the typo you made. When you found your eigenvector for lambda = 4, you found 2 equations that were inconsistent [tex] -2x + 2y = 4x \mbox{~and~} 3x -3y = 4y[/tex] . This should have immediately told you that something was wrong.

Basically, at this point: [tex]
\left( \begin{array}{cc} -2 & 2 \\ 3 & -2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right)
[/tex] you should know that somethings wrong since the rows have to be linearly dependent (that is, rows are a multiple of each other) to solve for eigenvectors.
 
  • #11
fuzzyorama said:
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 4\left( \begin{array}{c} x \\ y \end{array} \right) [/tex]

This is the wrong equation to use. The matrix on the right has to be A, and not the modified one with the subtracted eigenvalues.

If you want to use the modified matrix as you are, you need to set the right hand side equal to 0.

Basically you're making the mistake of this:

y=x Original equation

and then:
y-x=x WRONG

y-x=0 CORRECT

but in matrix form.

I make this mistake myself quite often.
 
  • #12
This is the wrong equation to use. The matrix on the right has to be A, and not the modified one with the subtracted eigenvalues.

If you want to use the modified matrix as you are, you need to set the right hand side equal to 0.
Thanks for pointing that out:smile: Now I will redo everything.
[tex] A = \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right) [/tex]
[tex] \left\vert \begin{array}{cc} 2 - \lambda & 2 \\ 3 & 1 - \lambda \end{array} \right\vert = 0 [/tex]

[tex] (2 - \lambda )(1 - \lambda) - (3)(2) = 0 [/tex]
[tex] 2 - 2\lambda - \lambda + \lambda^2 - 6 = 0 [/tex]
[tex] \lambda^2 -3\lambda - 4 = 0 [/tex]

[tex] \therefore \lambda = -1, 4 [/tex]

When [tex] \lambda = -1 [/tex],
[tex] \left( \begin{array}{cc} 2 - (-1) & 2 \\ 3 & 1 - (-1) \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 0 [/tex]
[tex] \left( \begin{array}{cc} 3 & 2 \\ 3 & 2 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 0 [/tex]

[tex] 3x + 2y = 0 [/tex]
[tex] 2y = -3x [/tex]
[tex] \therefore y = -\frac{3}{2}x [/tex]

Now I put this in my original matrix A ([tex] Ax = \lambda x [/tex])
[tex] \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right)\left( \begin{array}{c} x \\ -\frac{3}{2}x \end{array} \right) = -\left( \begin{array}{c} x \\ -\frac{3}{2}x \end{array} \right) [/tex]
[tex] \therefore -x\left( \begin{array}{c} 1 \\ -\frac{3}{2} \end{array} \right) [/tex]

Next, when [tex] \lambda = 4 [/tex],
[tex] \left( \begin{array}{cc} 2 - 4 & 2 \\ 3 & 1 - 4 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 0 [/tex]
[tex] \left( \begin{array}{cc} -2 & 2 \\ 3 & -3 \end{array} \right)\left( \begin{array}{c} x \\ y \end{array} \right) = 0 [/tex]

[tex] -2x + 2y = 0 [/tex]
[tex] 3x - 3y = 0 [/tex]
[tex] \therefore x = y [/tex]

[tex] \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right)\left( \begin{array}{c} x \\ x \end{array} \right) = 4 \left( \begin{array}{c} x \\ x \end{array} \right)
[/tex]
[tex] \therefore x\left( \begin{array}{c} 1 \\ 1 \end{array} \right) [/tex]

Dayum this took quite a while heh.
 
Last edited:
  • #13
At [tex] \therefore y = -\frac{3}{2}x [/tex], what this is telling you is that the solution to your system of equation is ANY matrix such that the y-entry is -3/2 of the x-entry. For example, you can try [tex]\left( {\begin{array}{*{20}c} 2 \\ { - 3} \\\end{array}}\right)[/tex] for example. Any constant multiple of that eigenvector is an eigenvector as well! You can normalize it and use [tex]
\left( {\begin{array}{*{20}c}
{\frac{2}{{\sqrt {13} }}} \\
{\frac{{ - 3}}{{\sqrt {13} }}} \\
\end{array}} \right)[/tex] for example! Plug it into your original equation and you'll see both work.

Also, having the x multiplying your eigenvector is kinda confusing as it look slike you're multiplying your eigenvector by another matrix x.
 
  • #14
Pengwuino said:
At [tex] \therefore y = -\frac{3}{2}x [/tex], what this is telling you is that the solution to your system of equation is ANY matrix such that the y-entry is -3/2 of the x-entry. For example, you can try [tex]\left( {\begin{array}{*{20}c} 2 \\ { - 3} \\\end{array}}\right)[/tex] for example. Any constant multiple of that eigenvector is an eigenvector as well! You can normalize it and use [tex]
\left( {\begin{array}{*{20}c}
{\frac{2}{{\sqrt {13} }}} \\
{\frac{{ - 3}}{{\sqrt {13} }}} \\
\end{array}} \right)[/tex] for example! Plug it into your original equation and you'll see both work.

I got it right?

Understood! So it can also be
[tex] \left( {\begin{array}{*{20}c} 4 \\ { - 6} \\\end{array}}\right) [/tex] ?
 
  • #15
Yes, it can be any constant multiple. Simply plug it in and see what pops out to make sure you have an eigenvector.
 
  • #16
[tex] \left( \begin{array}{cc} 2 & 2 \\ 3 & 1 \end{array} \right)\left( \begin{array}{c} 2 \\ -3 \end{array} \right) = -\left( \begin{array}{c} 2 \\ -3 \end{array} \right) [/tex]

[tex] 2(2) + 2(-3) = -2 [/tex]
[tex] 3(2) + 1(-3) = 3 [/tex]

I GOT IT RIGHT! YOU GUYS ARE THE AWESOMEST! THANKS :!) :!) :!)
 

1. What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are mathematical concepts that are used to understand and analyze linear transformations. Eigenvalues represent the scaling factor by which an eigenvector is stretched or compressed by a transformation.

2. How do eigenvalues and eigenvectors relate to matrices?

Eigenvalues and eigenvectors are calculated from square matrices. Eigenvalues are the solutions to the characteristic equation of a matrix, while eigenvectors are the corresponding vectors that are transformed by the eigenvalues.

3. What is the significance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in various fields such as physics, engineering, and computer science. They help to simplify and understand complex systems and can be used for tasks such as image compression, data analysis, and simulation.

4. How are eigenvalues and eigenvectors calculated?

To calculate eigenvalues and eigenvectors, we first find the characteristic polynomial of a matrix and then solve for its roots, which are the eigenvalues. The corresponding eigenvectors can then be found by solving a system of equations.

5. What is the difference between eigenvalues and eigenvectors?

The main difference between eigenvalues and eigenvectors is that eigenvalues are numbers that represent the scaling factor of an eigenvector, while eigenvectors are vectors that are transformed by the eigenvalues. Eigenvalues are also scalar values, while eigenvectors are typically represented as column vectors.

Similar threads

  • Advanced Physics Homework Help
Replies
6
Views
873
  • Linear and Abstract Algebra
Replies
14
Views
1K
  • Differential Equations
Replies
2
Views
685
  • Linear and Abstract Algebra
Replies
1
Views
674
  • Precalculus Mathematics Homework Help
Replies
14
Views
2K
  • Precalculus Mathematics Homework Help
Replies
1
Views
724
  • Advanced Physics Homework Help
Replies
19
Views
827
  • Precalculus Mathematics Homework Help
Replies
13
Views
784
  • MATLAB, Maple, Mathematica, LaTeX
Replies
3
Views
479
  • Precalculus Mathematics Homework Help
Replies
7
Views
1K
Back
Top