Lower triangular matrix eigenvectors problem

In summary, the problem involved finding the eigenvectors and eigenvalues for a given matrix. The first eigenvalue was incorrectly calculated as positive instead of negative, and the eigenvectors were also calculated incorrectly due to a typo in the equation. The correct equations are (1-4c/3)*v_1 = 0 and (c/3)*v_1 = (c/3 -1)*v_2, resulting in the eigenvectors <(c/3-1), 4/3> and <0, 1> for λ_1 and λ_2 respectively. The error was resolved and the correct solutions were obtained.
  • #1
eherrtelle59
25
0
Ok, this is starting to come back to me, but I'm stuck again

Homework Statement




M=\begin{bmatrix}
(1-\frac{4}{3}) & 0 \\
-\frac{c}{3} & -c \\
\end{bmatrix}


Find eigenvectors and eigenvalues.

Homework Equations





The Attempt at a Solution



Eigenvalues are [itex] λ_1= (1-\frac{4}{3})>0[/itex] and [itex] λ_2=-c>0 [/itex]

Eigenvector for [itex] λ_2 [/itex] is <0 1>
For [itex]λ_1[/itex], I should get [itex]<(\frac{c}{3}-1) (\frac{4}{3})> [/itex]

However, I end up with (without writing out the matrix again, just giving the equation mind you)

[itex] -c*e_2 = e_1 - \frac{4}{3}*e_1 +\frac{c}{3}*e_1 [/itex]

This is [itex] -c*e_2 = (1-c)*e_1 [/itex]which gets an eigenvector of something like <(1-c) c>

Anyone see my error? Thanks
 
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  • #2
The clearly negative eigenvalue being allegedly positive is the first thing that struck me as odd, but not really a big deal in the grand scheme of things

I don't understand what you did to get that equation (the left hand side looks like Me2, and the right hand side is completely unclear to me where it came from, but the fact that you have a scaling of e1= a scaling of e2 seems pretty suspicious), or what you are claiming the eigenvector for the first eigenvalue is since it only has one entry as written - is it supposed to be ( (c/3-1), 4/3)?
 
  • #3
"The clearly negative eigenvalue being allegedly positive is the first thing that struck me as odd, but not really a big deal in the grand scheme of things"

That's a typo on my part. λ_2 should be negative i.e. -c<0

"is it supposed to be ( (c/3-1), 4/3)?"

Yes

To show explicitly what I did, using the standard eigenvector equation with v_i instead of e_i


\begin{bmatrix}
(1-(4/3)c) & 0 \\
-c/3 & -c \\
\end{bmatrix} *\begin{bmatrix}
v_1 \\
v_2 \\
\end{bmatrix}

= \begin{bmatrix}
(1-4c/3)*v_1 \\
(1-4c/3)*v_1\\
\end{bmatrix}

When you multiply this matrices (as sort of shown...latex skills withstanding) then you get the equation I've written previously.
 
  • #4
"but the fact that you have a scaling of e1= a scaling of e2 seems pretty suspicious"

When finding eigenvectors I always get equations like this.
 
  • #5
I'm sorry everyone, that should be multiply by

\begin{pmatrix}
(1-4c/3)v_1\\
(1-4c/3)v_2\\
\end{pmatrix}
which does indeed give the right answer,

(c/3)*v_1 = (c/3 -1)*v_2

Sorry for wasting everyone's time, I've finally got it now. Thank you!
 

Related to Lower triangular matrix eigenvectors problem

1. What is a lower triangular matrix?

A lower triangular matrix is a square matrix where all the elements above the main diagonal are zero. This means that the elements in the lower left part of the matrix can have non-zero values, but all the elements in the upper right part are zero.

2. What is an eigenvector?

An eigenvector is a vector that, when multiplied by a given matrix, results in a scaled version of itself. In other words, it is a vector that does not change direction when multiplied by a matrix, but only gets scaled by a factor known as the eigenvalue.

3. What is the lower triangular matrix eigenvectors problem?

The lower triangular matrix eigenvectors problem refers to finding the eigenvectors of a lower triangular matrix. This problem is important in linear algebra and has many applications in various fields, such as computer graphics, engineering, and physics.

4. How do you find the eigenvectors of a lower triangular matrix?

To find the eigenvectors of a lower triangular matrix, you can use the standard method of solving for the eigenvalues and then finding the corresponding eigenvectors. However, in the case of a lower triangular matrix, the eigenvalues are simply the diagonal elements of the matrix, and the eigenvectors can be easily determined by setting up a system of equations and solving for the unknown variables.

5. What are the properties of eigenvectors of a lower triangular matrix?

There are several properties of eigenvectors of a lower triangular matrix, including:

  • The eigenvectors are orthogonal to each other, meaning they are at right angles to each other.
  • The eigenvectors are also orthogonal to the matrix, meaning when multiplied by the matrix, the result is a zero vector.
  • The eigenvectors are linearly independent, meaning none of them can be expressed as a linear combination of the others.
  • The eigenvectors form a basis for the vector space spanned by the matrix.

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