Prove true or false eigenvalue question

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In summary, the conversation is discussing the connection between the restriction A^2 + A = 0 and its effects on the eigenvalues of a matrix. The attempt at a solution involves finding matrices that satisfy this restriction and examining their eigenvalues. It is noted that in all cases where -1 is on the diagonal, the eigenvalue is always negative. However, further clarification is needed in determining the relationship between the two.
  • #1
blockdummy
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Homework Statement



Prove true or false.

If A^2+A=0 then λ=1 may not be an eigenvalue.


Homework Equations



To find the eigenvalues of A I find the solutions to det(λ-A).

The definition of an eigenvalue from my understanding, AX = λX.

A(A+I) = 0


The Attempt at a Solution



I'm unable to find the connection between the restriction of A^2+A=0 and its effects on the eigenvalues.

Since A^2 + A =0 , I've thought of some matrices where this is true.

Scenarios:

A = 0

A =\begin{pmatrix}
-1\end{pmatrix}

A = \begin{pmatrix}
-1 & 0\\
0 & -1\end{pmatrix}

A = \begin{pmatrix}
-1 & -1\\
0 & 0\end{pmatrix}


It seems that when you have -1 on the diagonal the first equation holds true and the eigenvalues are -1 or 0. With that being said, this statement appears true, but I have no idea how to find scenarios which could be counterexamples nor do I have a formal proof if the statement is indeed true.

Clarification 1: Since I've only been able to find matrices with -1 (after reduction) on the diagonal to satisfy A^2 + A = 0, it appears that the eigenvalue will be always negative because when I find the characteristic polynomial its always in the form of (λ+1)^n which gives me a negative eigenvalue.

Any help would be appreciated.
 
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  • #2
(try using the X2 button just above the Reply box

hi blockdummy! welcome to pf! :smile:

(try using the X2 button just above the Reply box :wink:)

if 1 is an eigenvalue and x is the eigenvector, then (A2 + A)x = … ? :wink:
 
  • #3
Hmm...

(A2 + A)x = (1)x

Is it correct to assume that both sides have the same eigenvector?

If so the x's cancel and... (A2 + A) = 1 which is a contradiction. This doesn't seem correct since the only way this wouldn't be a contradiction would be if λ=0.
 
  • #4
hi blockdummy! :smile:
blockdummy said:
(A2 + A)x = (1)x

nooo …

try again :wink:
If so the x's cancel …

how??

you can't divide by a vector!​
 

Related to Prove true or false eigenvalue question

What is an eigenvalue?

An eigenvalue is a scalar value that represents the magnitude of a vector in a specific direction when a linear transformation is applied to the vector.

What is the purpose of proving a true or false eigenvalue question?

The purpose of proving a true or false eigenvalue question is to determine whether a given vector is an eigenvector for a particular linear transformation, and if so, to find its corresponding eigenvalue.

How do you prove a true eigenvalue question?

To prove a true eigenvalue question, you need to show that the given vector is indeed an eigenvector for the given linear transformation, and then find its corresponding eigenvalue by solving the characteristic equation.

What is the characteristic equation?

The characteristic equation is a polynomial equation in which the eigenvalue is the variable. It is formed by setting the determinant of the matrix equal to zero and solving for the eigenvalue.

Can a linear transformation have more than one eigenvalue?

Yes, a linear transformation can have multiple eigenvalues. This means that there can be multiple vectors that are eigenvectors for the same transformation, each with its corresponding eigenvalue.

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