Understanding Eigenvectors: Troubleshooting and Verification

In summary, the conversation discussed the process of finding eigenvectors for a given matrix and the resulting eigenvalues. The individual was having trouble verifying their results and discussed their process for finding the null spaces. However, there was a discrepancy in the resulting eigenvectors, with one being [1,-1] and the other being [-4/3,1]. It was pointed out that eigenvectors can be multiplied by any constant and still be considered the same, so the correct eigenvector is [4/3,1].
  • #1
awl2k
1
0
Hello people!

I am having a bit trouble with verifying my result when i compute the eigenvectors for the following matrix:

A=[[3,4],[3,2]]

I know for sure that the eigenvalues is respectively -1 and 6, so i start finding a solution for the following null spaces:

1) N(A--1I)=[[4,4|0],[3,3|0]]~[[1,1|0],[0,0|0]] => x1 = x2 so the the vector x2[1,-1] will be a solution and therefor the first eigenvector is [1,-1]

2) N(A-6I)=[[-3,4|0],[3,-4|0]]~[[1,-4/3|0],[0,0|0]] => x1=4/3 so this indicate that x2[-4/3,1] will be a solution to the null space, and therefor the second eigen vector i [-4/3,1].

However the result should be [1,-1] [4,3] respectively. What am i doing wrong?
 
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  • #2
[-4/3,1] is not an eigenvector of 6. The correct eigenvector is [4/3,1] because the equation you get is 3x-4y=0.
 
  • #3
Eigenvectors are always undermined up to a multiplicative factor, since if A*x = λ*x, then
A*(nx) = λ*(nx). So (4/3,1) and (4,3) are the same eigenvector.
 

1. What is an eigenvector?

An eigenvector is a vector that, when multiplied by a square matrix, results in a scalar multiple of itself. This scalar multiple is known as the eigenvalue.

2. Why is understanding eigenvectors important in science?

Eigenvectors are important in science because they help us understand the behavior and properties of linear transformations. They also have many applications in fields such as physics, engineering, and data analysis.

3. How do you calculate eigenvectors?

To calculate eigenvectors, you first need to find the eigenvalues of a matrix by solving the characteristic equation. Then, for each eigenvalue, you can find its corresponding eigenvector by solving a system of linear equations.

4. Can eigenvectors have complex values?

Yes, eigenvectors can have complex values. This is because the eigenvalues and eigenvectors of a matrix are determined by the algebraic and geometric properties of the matrix, rather than the type of values it contains.

5. What is the relationship between eigenvectors and eigenvalues?

Eigenvectors and eigenvalues are closely related. Eigenvectors are associated with specific eigenvalues, and the eigenvalues determine the scaling factor for the eigenvector. In other words, eigenvectors and eigenvalues are like two sides of the same coin.

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