A matrix satisfies A^2 - 4A + 5I = 0, then n is even.

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The discussion centers on proving that if a matrix A satisfies the equation A2 - 4A + 5I = 0, then the dimension n of the matrix must be even. The participants derive that (A - 2I)2 + I = 0, leading to the conclusion that the determinant of both sides must be computed. Additionally, it is established that for an m x n matrix A where m < n, the determinant of AT x A equals zero due to the rank deficiency of AT x A, which is n x n.

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Homework Statement



1) Let A be an n x n matrix with A^2 -4A +5I = 0. Show that n must be even.

2) Let A be an m x n matrix where m<n. Show that det(AT x A) = 0

The Attempt at a Solution



1) (A-2I)^2 +I=0

Not sure what to do after this though


Thanks in advance
 
Last edited:
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Hydroxide said:

Homework Statement



1) Let A be an n x n matrix with A^2 -4A +5I = 0. Show that n must be even.
An n x n matrix with real entries? If it can have complex entries, this isn't true. Anyways, what do you know about minimal polynomials and characteristic polynomials?
2) Let A be an m x n matrix where m<n. Show that det(A^T x A) = 0
What do you know about the relationships between rank, invertibility, and determinants.
1) (A-2I)^2 +I=0
Okay, that's not bad. So (A-2I)2 = -I. Compute the determinant of both sides.
 
Cheers I've got the first question now. Was easier than i thought.

I still can't do 2) though.

AKG said:
What do you know about the relationships between rank, invertibility, and determinants.

Could you explain further please?
 
What are the dimensions of the matrix ATA? What can you say about the rank of ATA?
 
AKG said:
What are the dimensions of the matrix ATA? What can you say about the rank of ATA?

ATA is n x n
We haven't covered ranks yet

I know that ATA can reduced so that it has one row of zero's hence det=0. But I don't know how to show it in general.
 
It may help to think of matrix multiplication with a vector as a linear combination of the columns of the matrix

i.e. For A\vec{c} = \vec{b}\\ b is a linear combination of the columns of A

And hence a matrix multiplication with a vector will produce a matrix whose columns are a linear combination of the columns of the first matrix.

i.e. For AB = C\\ C's columns are linear combinations of the columns of A

Sorry if the Latex is less than desirable, as you can see, I'm new here.
 
Last edited:

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