Commuting Invertible Matrices

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In summary, if A is an invertible (n×n, real) matrix that commutes with ALL other invertible (n×n, real) matrices, then A is of the form cI, where c is any real number not equal to 0. The easiest way to show this is to use matrices B of the form I with an additional 1 at one other entry.
  • #1
T-O7
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Hey all,
I'm having trouble showing the following point:
if A is an invertible (n×n, real) matrix that commutes with ALL other invertible (n×n, real) matrices, then A is of the form cI, where c is any real number not equal to 0.

Anyone know how to show this?
 
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  • #2
Try picking some particularly simple matrices B (such as having only a single nonzero entry!) and use AB = BA to get equations for the entries of A.
 
  • #3
Thanks for the suggestion. So I had to use matrices B of the form I with an additional 1 at one other entry. By brute force, calculating the corresponding entries of AB would eventually give that all diagonal entries of A were the same, and that all other non diagonal entries must be zero. Sweet.
 
  • #4
Actually, I would pick my B's so they have only one nonzero entry, rather than being the identity with an additional nonzero entry.

I think this is the easiest approach to understand, though not the shortest.
 
  • #5
Yes, I was considering that, but B must also be invertible, so I had to complicate B a little bit by adding the diagonal 1's.
 
  • #6
Ah, good point, I had missed that.

However, note this (reversible) deduction:

A(I+B) = (I+B)A
A + AB = A + BA
AB = BA


B commutes with A iff (I+B) commutes with A, so you could still work with my B's, if you choose.
 
  • #7
That's wonderful! Thanks a lot for the help :smile:
 
  • #8
Here's a conceptual suggestion. Think of A as a transformation and let v be any non zero vector. We want to show first that Av = cv for some constant c.

Choose a basis involving v as first vector and define another transformation B that takes v to v and the other basis vectors to 0. Then applying AB = BA to v shows that ABv = Av = BAv, so B acts on Av != 0 as the identity. Since A is invertible, Av is not zero, so then Av = cv for some non zero constant c, since multiples of v are the only non zero vectors B takes to themselves.

Thus every vector v is an "eigenvector" for A, i.e. Av always equals cv for some c possibly depending on v. Now if every vector is an eigen - vector, we claim all the eigenvalues must be equal.

To see that, assume that Av = cv and Aw = dw, where v and w are in different directions, and look at A(v+w) = cv + dw = e(v+w), and check that we must have c=d=e.

Now why is that? well then cv + dw -ev -ew = 0 = (c-e)v + (d-e)w, hence
(c-e)v = (e-d)w, so these multiples of v and w are equal.

But since v, w are in different directions, their only equal multiples are zero, so d=e, c=e. QED.
 

1. What is a commuting invertible matrix?

A commuting invertible matrix is a square matrix that can be multiplied with another matrix in any order without changing the result. This means that the two matrices commute with each other.

2. How do you determine if two matrices commute with each other?

To determine if two matrices commute, you can simply multiply them in both orders and see if the results are the same. If the products are equal, then the matrices commute with each other.

3. What are some properties of commuting invertible matrices?

Commuting invertible matrices have several properties, including:

  • They have the same determinant
  • They have the same trace
  • They have the same eigenvalues
  • They have the same rank

4. Can non-square matrices commute with each other?

No, non-square matrices cannot commute with each other. In order for matrices to commute, they must have the same dimensions.

5. How are commuting invertible matrices useful in scientific research?

Commuting invertible matrices are useful in various fields of science, such as physics, engineering, and computer science. They are commonly used in the study of linear transformations and in solving systems of equations. They also have applications in cryptography and coding theory.

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