Eigenvalues and Orthogonal Matrices: Proving Properties Without Prefix

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Homework Help Overview

The discussion revolves around properties of eigenvalues and orthogonal matrices, specifically focusing on proving that if \((A-I)^{2}=O\), then any eigenvalue \(\lambda\) of matrix \(A\) must equal 1, and that the determinant of an orthogonal matrix \(A\) is either +1 or -1.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the implications of the equation \((A-I)^{2}=O\) and question the assumption that \(A=I\). They discuss the relationship between eigenvalues and the matrix's properties, particularly focusing on how to derive eigenvalue conditions from the given matrix equation.
  • In the context of orthogonal matrices, participants examine the determinant relationship and question how the properties of determinants relate to the conclusion that \(\det(A)=\pm 1\).

Discussion Status

The discussion is active with participants providing various insights and questioning assumptions. Some participants have offered guidance on the implications of matrix operations and properties of determinants, while others are exploring different interpretations of the eigenvalue problem.

Contextual Notes

There is a mention of potential confusion regarding the zero-divisor property in matrix algebra, which may affect the interpretation of the eigenvalue conditions. Additionally, the discussion includes attempts to clarify the implications of the determinant properties without reaching a definitive conclusion.

Bertrandkis
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Question 1
Let A be an nxn matrix such that (A-I)^{2}=O where O is the zero matrix
Prove that if {\lambda} is an eigen value of A then {\lambda}=1
My attempt
If (A-I)^{2}=O then A=I (1)
if {\lambda} is an eigen value of A then Ax={\lambda}x (2)
replace (1) in (2) Ix={\lambda}x , but Ix=x therefore {\lambda}=1

Question 2
If A is an orthogonal Matrix, then prove that det(A)=+-1
My attempt
if A is orthogonal then AA^{T}=I and A^{-1}=A^{T}
therefore AA^{-1}=I and det(AA^{-1})=1 . Where does the + - comes from?
 
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1) You can't say A=I. It's not necessarily true. You do know (A-I)(A-I)x=0. Now let x be an eigenvector...
2) You've got det(A*A^T)=1. What can you say about the relationship between det(AB) and det(A) and det(B)? How about between det(A) and det(A^T)?
 
Dick
1)How do you know that (A-I)(A-I)x=0? Why not (A-I)(A-I)x={\lambda}x.
If (A-I)(A-I)x=0 and x being the eigen vector, this suggests that {\lambda}=0.

2)I know that det(A^{T})=det(A) but how does that prove that
det(A)=+-1) ?
 
The problem says (A-I)^2=0. Operating on a vector means (A-I)(A-I)x=0. (A-I)x=Ax-Ix. If Ax={\lambda}x that's (\lambda-1)x. Now apply the other (A-I). At the end you have a NUMBER times a nonzero vector equaling zero. So the number is zero.

det(A*A^T)=1=det(A^T)*det(A)=det(A)^2. Solving that equation for det(A) is just like solving x^2=1 for x. What are the solutions?
 
Last edited:
Dick's original point was simply that you cannot, from M2= 0, with M a matrix and 0 the zero matrix, conclude that M= 0 because there are "zero-divisors" in the algebra of matrices. For example,
M= \left(\begin{array}{cc} 1 & 1 \\ -1 & -1 \end{array}\left)
has the property that M2= 0.

Of course, saying M2= 0 means that M2x= 0x= 0 for any vector x. Separate that into M(Mx)= 0 and solve "twice".
 
for the first question I came up with this: 0=(A-I)^2=A^2-2A+I. so if Ax=\lambda x, for some
vector x \neq 0, then A^2x=\lambda^2x, and 0=(\lambda^2 - 2\lambda + 1)x=(\lambda - 1)^2x. thus \lambda = 1.
This looks very right, doesn't it?

For question 2, I figue that x^2=1 yields x=+-1.
Thanks To all.
 

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