My answer for eigenspace is valid right?

  • Thread starter Rijad Hadzic
  • Start date
In summary, to determine if your eigenspace answer is correct, you need to ensure that it satisfies all the properties of an eigenspace. This can be done by comparing it to the definition of an eigenspace and verifying it with matrix operations. It is possible for your eigenspace answer to be incorrect if you make mistakes or if it does not meet all the necessary criteria. If this happens, review your work and seek help if needed. While there is no easy way to find the eigenspace, following systematic steps and having a good understanding of linear algebra can make the process easier.
  • #1
Rijad Hadzic
321
20

Homework Statement


Determine the characteristic polynomials, eigenvalues, and corresponding eigenspaces of the given 2x2 matricies

Homework Equations

The Attempt at a Solution


[itex]

\begin{pmatrix}
5 & 2\\
-8 & -3 \\
\end{pmatrix}
[/itex]
thus

[itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

determinant is = to: [itex] \lambda^2 -2\lambda + 1 [/itex]

which gives value lambda = 1

plugging into [itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

you get[itex]

\begin{pmatrix}
4 & 2\\
-8 & -4 \\
\end{pmatrix}
[/itex]

using rref you get[itex]

\begin{pmatrix}
1 & .5\\
0 & 0\\
\end{pmatrix}
[/itex]

setting x2 = r, I get eigenspace r*[itex]

\begin{pmatrix}
-1/2\\
1 \\
\end{pmatrix}
[/itex]

but my book is telling me the anser is r*[itex]

\begin{pmatrix}
1\\
-2 \\
\end{pmatrix}
[/itex]

our answers are the same thing right?
 
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  • #2
Rijad Hadzic said:

Homework Statement


Determine the characteristic polynomials, eigenvalues, and corresponding eigenspaces of the given 2x2 matricies

Homework Equations

The Attempt at a Solution


[itex]

\begin{pmatrix}
5 & 2\\
-8 & -3 \\
\end{pmatrix}
[/itex]
thus

[itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

determinant is = to: [itex] \lambda^2 -2\lambda + 1 [/itex]

which gives value lambda = 1

plugging into[itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

you get[itex]

\begin{pmatrix}
4 & 2\\
-8 & -4 \\
\end{pmatrix}
[/itex]

using rref you get[itex]

\begin{pmatrix}
1 & .5\\
0 & 0\\
\end{pmatrix}
[/itex]

setting x2 = r, I get eigenspacer*[itex]

\begin{pmatrix}
-1/2\\
1 \\
\end{pmatrix}
[/itex]

but my book is telling me the anser isr*[itex]

\begin{pmatrix}
1\\
-2 \\
\end{pmatrix}
[/itex]

our answers are the same thing right?

Of course they are. If ##v## is an eigenvector then so is ##cv## for any nonzero ##c##. Your values of ##r## just differ by a factor of -2.
 
  • #3
Dick said:
Of course they are. If ##v## is an eigenvector then so is ##cv## for any nonzero ##c##. Your values of ##r## just differ by a factor of -2.

alright ty was just making sure. I do overthink small things like this but your explanation makes sense.
 
  • #4
Rijad Hadzic said:

Homework Statement


Determine the characteristic polynomials, eigenvalues, and corresponding eigenspaces of the given 2x2 matricies

Homework Equations

The Attempt at a Solution


[itex]

\begin{pmatrix}
5 & 2\\
-8 & -3 \\
\end{pmatrix}
[/itex]
thus

[itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

determinant is = to: [itex] \lambda^2 -2\lambda + 1 [/itex]

which gives value lambda = 1

plugging into[itex]

\begin{pmatrix}
5-\lambda & 2\\
-8 & -3-\lambda \\
\end{pmatrix}
[/itex]

you get[itex]

\begin{pmatrix}
4 & 2\\
-8 & -4 \\
\end{pmatrix}
[/itex]

using rref you get[itex]

\begin{pmatrix}
1 & .5\\
0 & 0\\
\end{pmatrix}
[/itex]

setting x2 = r, I get eigenspacer*[itex]

\begin{pmatrix}
-1/2\\
1 \\
\end{pmatrix}
[/itex]

but my book is telling me the anser isr*[itex]

\begin{pmatrix}
1\\
-2 \\
\end{pmatrix}
[/itex]

our answers are the same thing right?

You should point out that "1" is a double eigenvalue; that is, the eigenvalues of the matrix are 1,1. You might also want to point out that this matrix is "deficient": its "eigenspace" has only one dimension and so does not span the whole space. (It I were marking this question I would give full points only if the student mentioned those things---but of course, I am not marking it.)
 
  • #5
Thread moved to Calculus section. Questions about eigen-<whatever> are well beyond precalculus, IMO.
 

1. Is my eigenspace answer correct?

The validity of your eigenspace answer depends on whether it satisfies all the properties of an eigenspace. These include being a subspace of the original vector space and containing all the eigenvectors corresponding to a particular eigenvalue. Make sure to check these properties before concluding that your answer is valid.

2. How do I know if my eigenspace answer is valid?

To determine the validity of an eigenspace answer, you can compare it to the definition of an eigenspace and check if it satisfies all the necessary properties. Additionally, you can also verify your answer by performing matrix operations to see if the eigenvectors do indeed transform into scalar multiples of themselves.

3. Can my eigenspace answer be incorrect?

Yes, it is possible for your eigenspace answer to be incorrect. This can happen if you make a mistake in identifying the eigenvalues or corresponding eigenvectors, or if your answer does not satisfy all the properties of an eigenspace. Double-check your work and make sure to follow the correct steps to find the eigenspace.

4. What should I do if my eigenspace answer is incorrect?

If you realize that your eigenspace answer is incorrect, go back and review your work. Check for any mistakes in identifying the eigenvalues or eigenvectors, and make sure your answer satisfies all the properties of an eigenspace. If you are still unsure, seek help from a teacher or colleague.

5. Is there an easy way to find the eigenspace?

There is no one-size-fits-all method to find the eigenspace, as it depends on the specific matrix and eigenvalue you are working with. However, there are systematic steps you can follow, such as finding the null space of the matrix minus the eigenvalue times the identity matrix. It is important to have a good understanding of linear algebra and the properties of eigenspaces to make the process easier.

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