Diagonalizing A: Is it Possible with Rational Numbers?

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In summary, we discussed the diagonalizability of a real matrix A with A²=I and added the condition that A is in O(m,m). We used the result that an involution is always diagonalizable over the reals and discussed another characterization for diagonalizable matrices. We also mentioned the minimal polynomial of an involution and its connection to our theorem. Additionally, we explored how to find a basis of eigen vectors for A and discussed the possibility of using rationals or integers instead of reals for diagonalization.
  • #1
quasar987
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Hello matrix gurus,

Is is true that if A is real with A²=I (eigenvalues ±1), it is diagonalizable over R?

What if I add that A is in O(m,m), where O(m,m) is the split indefinite orthogonal group of 2m x 2m matrices M such that [itex]M^TI_{m,m}M=I_{m,m}[/itex], where [itex]I_{m,m}[/itex] is the block diagonal matrix diag(I_m,-I_m) for I_m the m x m identity matrix?

Thanks
 
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Yes, an involution is always diagonalizable over the reals.

We use the following result:

Another characterization: A matrix or linear map is diagonalizable over the field F if and only if its minimal polynomial is a product of distinct linear factors over F. (Put in another way, a matrix is diagonalizable if and only if all of its elementary divisors are linear.)

See http://en.wikipedia.org/wiki/Diagonalizable_matrix A proof can be found in Hoffman & Kunze theorem 6 page 204.

The minimal polynomial of an involution is [itex]x^2-1=(x+1)(x-1)[/itex] and satisfies our theorem.
 
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  • #3
quasar987 said:
Hello matrix gurus,

Is is true that if A is real with A²=I (eigenvalues ±1), it is diagonalizable over R?

What if I add that A is in O(m,m), where O(m,m) is the split indefinite orthogonal group of 2m x 2m matrices M such that [itex]M^TI_{m,m}M=I_{m,m}[/itex], where [itex]I_{m,m}[/itex] is the block diagonal matrix diag(I_m,-I_m) for I_m the m x m identity matrix?

Thanks

A.v - v and A.v + v are both eigen vectors of A. They can not both be zero.
Use this inductively to find a basis of the vector space made up of eigen vectors of A.

e.g.
If A.v is not a multiple of v then both A.v - v and A.v + v are non-zero eigen vectors. Choose any other vector that is not in the span of v and A.v. and continue.

One certainly does not need all of the reals to diagonalize A. The rationals will work. I think all you really need to be able do is divide by 2.

Over the integers A can not always be diagonalized. The map (1,0) -> (1,-1) (0,1) -> (0,-1) is an example. The problem of inequivalent integer representations of groups is daunting.
 
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1. What does the equation A²=Id mean?

The equation A²=Id means that the square of a matrix A is equal to the identity matrix Id. In other words, when a matrix is multiplied by itself, the result is the identity matrix.

2. What is the significance of A diagonalizable?

A matrix being diagonalizable means that it can be transformed into a diagonal matrix by using a similarity transformation. This allows for easier calculations and analysis of the matrix.

3. How do you determine if a matrix is diagonalizable?

A matrix is diagonalizable if it has a full set of eigenvectors. This means that the matrix must have n linearly independent eigenvectors, where n is the size of the matrix. Additionally, the eigenvectors must span the entire vector space.

4. What are the benefits of having a diagonalizable matrix?

Having a diagonalizable matrix allows for easier calculations, as the diagonal form of the matrix makes it simpler to perform operations such as multiplication and inversion. It also provides more insight into the properties and behavior of the matrix.

5. Can a non-square matrix be diagonalizable?

No, only square matrices can be diagonalizable. This is because non-square matrices do not have eigenvectors and therefore cannot be transformed into a diagonal form.

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