Calculating Eigenvectors for a 3x3 Matrix: Understanding the Process

In summary, we are trying to find the eigenvectors for a 3x3 matrix with eigenvalues of λ1=13.8196, λ2=36.18, and λ3=40. The next step is to calculate the eigenvectors for each eigenvalue, starting with λ1. The solution manual provides an example of how to calculate the eigenvector for λ1, which involves reducing the matrix and solving for the variables. However, there seems to be a discrepancy between the calculated and given eigenvectors.
  • #1
M Sally
3
0
Member advised that the homework template must be used.
Hi,
I am trying to find the eigenvectors for the following 3x3 matrix and are having trouble with it. The matrix is
(I have a ; since I can't have a space between each column. Sorry):
[20 ; -10 ; 0]
[-10 ; 30 ; 0]
[0 ; 0 ; 40]

I’ve already calculated the eigenvalues, which are: λ1=13.8196, λ2=36.18 , λ3= 40
The next step is to calculate the eigenvectors for every eigenvalue λ and it’s now I keep getting the wrong answer. Let us take λ1 for instance. We'll get:

[20-13.8192 ; -10 ; 0]
[-10 ; 30-13.8196 ; 0]
[0 ; 0 ; 40-13.8196]

According to the solution manual, we get the following eigenvector for the eigenvalue λ1 :

[ 0.85066 ]
[ 0.527 ]
[ 0 ]

I tried to reduce the matrix by following these steps:
[20-13.8192 ; -10 ; 0] [6.1808 ; -10 ; 0] [1 ; -1.6179 ; 0]
[-10 ;30-13.8196 ; 0] ~ [-10 ; -16.1808 ; 0] ~ [-1 ; 1.6181 ; 0]
[0 ; 0 ; 40-13.8196] [0 ; 0 ; 1] [0 ; 0 ; 0]

I don’t get anywhere after this since, as can be seen, I won't get the same eigenvectors. How did they get 0.85066 and 0.527 ?! If you can explain it for λ1 then I'll probably solve it for λ2 and λ3 as well.

Thanks!
 
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  • #2
M Sally said:
Hi,
I am trying to find the eigenvectors for the following 3x3 matrix and are having trouble with it. The matrix is
(I have a ; since I can't have a space between each column. Sorry):
[20 ; -10 ; 0]
[-10 ; 30 ; 0]
[0 ; 0 ; 40]

I’ve already calculated the eigenvalues, which are: λ1=13.8196, λ2=36.18 , λ3= 40
The next step is to calculate the eigenvectors for every eigenvalue λ and it’s now I keep getting the wrong answer. Let us take λ1 for instance. We'll get:

[20-13.8192 ; -10 ; 0]
[-10 ; 30-13.8196 ; 0]
[0 ; 0 ; 40-13.8196]

According to the solution manual, we get the following eigenvector for the eigenvalue λ1 :

[ 0.85066 ]
[ 0.527 ]
[ 0 ]

I tried to reduce the matrix by following these steps:
[20-13.8192 ; -10 ; 0] [6.1808 ; -10 ; 0] [1 ; -1.6179 ; 0]
[-10 ;30-13.8196 ; 0] ~ [-10 ; -16.1808 ; 0] ~ [-1 ; 1.6181 ; 0]
[0 ; 0 ; 40-13.8196] [0 ; 0 ; 1] [0 ; 0 ; 0]

I don’t get anywhere after this since, as can be seen, I won't get the same eigenvectors. How did they get 0.85066 and 0.527 ?! If you can explain it for λ1 then I'll probably solve it for λ2 and λ3 as well.

Thanks!

For nice formatting (not much more work than what you already did), use the LaTeX commands "\pmatrix}{ ...your matrix... } " or "begin{bmatrix} ...your matrix... end{bmatrix}". Put the whole thing between two $signs (to start the equation) and two more $signs to end the equation.

Individual elements are entered as "a11 & a12 & a13 \\ a21 & a22 & a23 \\ ... " so "&" is a column-separator, while "\\" is an end-of-row and/or start a new-row command.

In the "pmatrix" version the matrix elements are all placed within a pair of curly brackets "{..}". In the second option the words "begin" and "end" must be preceded by a backslash, so they read as "\begin " and "\end"; however, I avoided writing that pair so as to not confuse the typesetter for this message.

The first option gives you
$$A = \pmatrix{20 & -10 & 0 \\-10 & 30 & 0 \\ 0 & 0 & -40}$$
while the second one gives you
$$A = \begin{bmatrix} 20 & -10 & 0 \\-10 & 30 & 0 \\ 0 & 0 & -40 \end{bmatrix}$$

Just right-click on the formula and select "show math as Tex commands" to see the details.
 
Last edited:
  • #3
You have ##\lambda_1= 25 -\sqrt{125}\; , \;\lambda_2= 25 +\sqrt{125}\; , \;\lambda_3=-40##. Have you tried to solve the three equation systems ##A \cdot \begin{bmatrix}x\\y\\z\end{bmatrix} = \lambda_i \cdot \begin{bmatrix}x\\y\\z\end{bmatrix}## by hand?
 
  • #4
M Sally said:
Hi,
I am trying to find the eigenvectors for the following 3x3 matrix and are having trouble with it. The matrix is
(I have a ; since I can't have a space between each column. Sorry):
[20 ; -10 ; 0]
[-10 ; 30 ; 0]
[0 ; 0 ; 40]

I’ve already calculated the eigenvalues, which are: λ1=13.8196, λ2=36.18 , λ3= 40
The next step is to calculate the eigenvectors for every eigenvalue λ and it’s now I keep getting the wrong answer. Let us take λ1 for instance. We'll get:

[20-13.8192 ; -10 ; 0]
[-10 ; 30-13.8196 ; 0]
[0 ; 0 ; 40-13.8196]

According to the solution manual, we get the following eigenvector for the eigenvalue λ1 :

[ 0.85066 ]
[ 0.527 ]
[ 0 ]

I tried to reduce the matrix by following these steps:
[20-13.8192 ; -10 ; 0] [6.1808 ; -10 ; 0] [1 ; -1.6179 ; 0]
[-10 ;30-13.8196 ; 0] ~ [-10 ; -16.1808 ; 0] ~ [-1 ; 1.6181 ; 0]
[0 ; 0 ; 40-13.8196] [0 ; 0 ; 1] [0 ; 0 ; 0]

I don’t get anywhere after this since, as can be seen, I won't get the same eigenvectors. How did they get 0.85066 and 0.527 ?! If you can explain it for λ1 then I'll probably solve it for λ2 and λ3 as well.

Thanks!
For ##\lambda_1 = 25 - 5 \sqrt{5} \doteq 18.8196## the equations ##(\mathbf{A} - \lambda_1 \mathbf{I}) \mathbf{x} = \mathbf{0}## read as
$$
\begin{array}{rcl}
(-5 + 5 \sqrt{5}) x_1 -10 x_2 =0 \\
-10 x_1 + (5+5 \sqrt{5}) x_2 = 0\\
(15 + 5 \sqrt{5}) x_3 = 0
\end{array}
$$
The first two equations are equivalent, so keeping only the first one we get the general solution as
$$x_2 = \frac{1}{2}(\sqrt{5}-1) x_1, \: x_3 = 0,$$
where ##x_1## is ab arbitrary nonzero real number.

The ratio of ##x_2## to ##x_1## is ##x_2: x_1 = (1/2)(\sqrt{5}-1) \doteq 0.6180339880##. For the book's solution this ratio is .6180658176, which could be made closer to the true result by including more precision in the printed vales of the components. The norm of the book's as-printed eigenvector is 1.002376215, which is nearly equal to 1, so the book is choosing ##x_1## to make ##\sqrt{x_1^2 + x_2^2 + x_3^2} = 1,## which is one of the standard normalizations for eigenvectors.
 
  • Like
Likes M Sally
  • #5
Ray Vickson said:
For ##\lambda_1 = 25 - 5 \sqrt{5} \doteq 18.8196## the equations ##(\mathbf{A} - \lambda_1 \mathbf{I}) \mathbf{x} = \mathbf{0}## read as
$$
\begin{array}{rcl}
(-5 + 5 \sqrt{5}) x_1 -10 x_2 =0 \\
-10 x_1 + (5+5 \sqrt{5}) x_2 = 0\\
(15 + 5 \sqrt{5}) x_3 = 0
\end{array}
$$
The first two equations are equivalent, so keeping only the first one we get the general solution as
$$x_2 = \frac{1}{2}(\sqrt{5}-1) x_1, \: x_3 = 0,$$
where ##x_1## is ab arbitrary nonzero real number.

The ratio of ##x_2## to ##x_1## is ##x_2: x_1 = (1/2)(\sqrt{5}-1) \doteq 0.6180339880##. For the book's solution this ratio is .6180658176, which could be made closer to the true result by including more precision in the printed vales of the components. The norm of the book's as-printed eigenvector is 1.002376215, which is nearly equal to 1, so the book is choosing ##x_1## to make ##\sqrt{x_1^2 + x_2^2 + x_3^2} = 1,## which is one of the standard normalizations for eigenvectors.

Thanks for explaining!
 

What is an eigenvector for a 3x3 matrix?

An eigenvector for a 3x3 matrix is a vector that, when multiplied by the matrix, results in a scalar multiple of itself. In other words, the direction of the vector remains unchanged but its magnitude is scaled.

How do you find eigenvectors for a 3x3 matrix?

To find eigenvectors for a 3x3 matrix, you must first find the eigenvalues by solving the characteristic equation. Then, for each eigenvalue, you can find the corresponding eigenvector by solving the equation (A - λI)v = 0, where A is the original matrix, λ is the eigenvalue, and v is the eigenvector.

What do the eigenvectors of a 3x3 matrix represent?

The eigenvectors of a 3x3 matrix represent the directions in which the matrix has a special linear transformation. They are also often used to find the principal components or dominant features of a dataset.

How many eigenvectors does a 3x3 matrix have?

A 3x3 matrix has three eigenvectors. This is because the number of eigenvectors is equal to the number of columns or rows in the matrix.

What are some applications of eigenvectors for a 3x3 matrix?

Eigenvectors for a 3x3 matrix have various applications in fields such as physics, engineering, and data analysis. They are used in quantum mechanics to describe the spin states of particles, in structural engineering to analyze the stability of structures, and in data science for dimensionality reduction and pattern recognition.

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