In order for the square of a matrix to be equal to the matrix

In summary, Idempotent Matrix Proof shows that in order for A2 to be defined, A must be a square matrix. The matrix {{1, 2, 3}, {4, 5, 6}, {7, 8, 9}} is a singular matrix that does not satisfy A2 = A. Therefore, A must equal I. Finally, if A is idempotent and non-singular, then In is idempotent.
  • #1
megalomaniac
18
0
Idempotent Matrix Proof

Homework Statement



Given a matrix A where A2 = A, find the properties of A.


Homework Equations



detA = ai1ci1 + ai2ci2 + ... + aincin (where cij = (-1)i+j*detAij)


aij = ai1a1j + ai2a2j + ... + ainanj

The Attempt at a Solution



In order for A2 to be defined, A must be a square matrix.

I have concluded that A must either equal the identity matrix I, or A must be singular.

I am having trouble proving this in the general case.
 
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  • #2
Hint: If A is not singular, it has an inverse. Use this fact.
 
  • #3
Well I found a counter-example that disproves that A is singular. The matrix {{1, 2, 3}, {4, 5, 6}, {7, 8, 9}} is a singular matrix that does not satisfy A2 = A.

So A must equal I. So AA-1 = I. But I still need a good way to prove this, and proofs are my deficiency.
 
  • #4
No, all you have done is to prove that singularity does not guarantee that A2=A.

Hint: The zero matrix is singular.
 
  • #5
Ok, now I'm just having problems determining the general properties of singular matrices that would make A2 = A
 
  • #6
Thus far I have shown,

Suppose A is an idempotent nxn matrix.

In the case of a non-singular matrix, in order to be invertible, there exists an nxn matrix B such that AB = BA = In, where B = A-1

Since A = B and B = A-1, then A = A-1

AA = In

Therefore In is idempotent.

Would this show that if A = I, then A is idempotent?

Also, now how would I go about showing the only other way for A to be idempotent would be if A is singular, since not all singular matrices are idempotent?

--Thank you.
 
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  • #7
megalomaniac said:
Since A = B
That was a big leap. You need to show this.

Therefore In is idempotent.
Isn't it kind of obvious that the identity matrix is idempotent?

Would this show that if A = I, then A is idempotent?
Trivially, yes. What you have not done is to show that the nxn identity matrix is the only nonsingular nxn idempotent matrix.

Yet another hint: An interesting subset of the idempotent matrices are the diagonal idempotent matrices. What can you say about the diagonal elements?
 
  • #8
D H said:
An interesting subset of the idempotent matrices are the diagonal idempotent matrices. What can you say about the diagonal elements?

Isn't the only diagonal idempotent matrix the identity matrix?
 
  • #9
Yes, but you have not yet shown this (yet).

There are also singular diagonal idempotent matrices. You might want to think about these for a bit, and whether they have any similarity to non-diagonal idempotent matrices.
 
  • #10
If A is idempotent and non-singular:

If I premultiply both sides by A-1, then I get:

A = InA = A-1AA = A-1A = In.

Would this be valid?

As for the diagonal idempotent matrices, they have full rank and therefore are non-singular and symmetric and non-diagonal idempotent matrices would be singular.

EDIT: And each entry of a diagonal idempotent matrix would have to be 0 or 1.
 
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  • #11
megalomaniac said:
If A is idempotent and non-singular:

If I premultiply both sides by A-1, then I get:

A = InA = A-1AA = A-1A = In.
Finally.

As for the diagonal idempotent matrices, they have full rank and therefore are non-singular and symmetric and non-diagonal idempotent matrices would be singular.

[tex]\bmatrix 1 & 0 \\ 0 & 0\endbmatrix[/tex]

This matrix is diagonal, is idempotent, and is not full rank.

EDIT: And each entry of a diagonal idempotent matrix would have to be 0 or 1.
Better.
 
  • #12
So for all diagonal idempotent matrices, A2 = A iff ai2 = ai for all i=1,...,n. This can only occur for i values of 0 and 1. Therefore, a diagonal matrix is idempotent iff each diagonal entry is 0 or 1.

So any idempotent diagonal matrix will be singular (save for I), but this still doesn't encompass all singular idempotent matrices.

I appreciate your help!
 
  • #13
megalomaniac said:
So for all diagonal idempotent matrices, A2 = A iff ai2 = ai for all i=1,...,n. This can only occur for i values of 0 and 1. Therefore, a diagonal matrix is idempotent iff each diagonal entry is 0 or 1.

So any idempotent diagonal matrix will be singular (save for I), but this still doesn't encompass all singular idempotent matrices.

I appreciate your help!
You're welcome.

Regarding the non-diagonal idempotent matrices. I dropped a BIG clue in post #9. You haven't picked up on it yet. Reread the post. Ponder over each word.
 
  • #14
So far it seems that the sum of the diagonal entries of an idempotent singular matrix must equal one, and the rows and/or columns must be linearly dependent.
 
  • #15
Ok, I have determined that detA equals the product of the eigenvalues. So in order for A to be singular, at least one eigenvalue must be zero. Where would I go from here to prove a singular idempotent matrix must have at least one zero eigenvalue?

-Thanks!
 
  • #16
You don't need to do that. Any singular matrix has at least one zero eigenvalue.

The key word in post #9 was similarity. Forget eigenvalues. Think similarity.
 
  • #17
So am I to show that a singular diagonal idempotent matrix is similar to a singular non-diagonal idempotent matrix? I'm sorry, I'm still unsure on how to go about this, my mind's been all over the place.
 
  • #18
Try the other way around first. You already know that a diagonal matrix whose diagonal elements are either zero or one is idempotent. Show that an arbitrary similarity transform yields another idempotent matrix.
 
  • #19
I haven't spent too much time dealing with similar matrices, but I'm assuming I am to use the fact that if B=P-1AP for some invertible matrix P, then A is similar to B. And A would be an idempotent diagonal matrix in this case?
 
  • #20
Yes. So what is B2 if B=P-1AP and A2=A?
 
  • #21
So B2=(P-1)2A2P2 = AI = A?
 
  • #22
No. Matrix math doesn't work that way. Try again.
 
  • #23
Ha oops,

How about: P-1APP-1AP = P-1AIAP = P-1AAP = P-1AP. So B2 = B ?
 
  • #24
There you go.
 
  • #25
But how does that prove that A must be singular?
 
  • #26
It doesn't. It shows that a matrix that is similar to an idempotent matrix is idempotent.
 
  • #27
But I'm trying to prove that if an idempotent matrix is not the identity matrix, then it must be singular. How do I make this leap?

-Thank you!
 
  • #28
megalomaniac said:
But how does that prove that A must be singular?
Obvious point: the identity matrix satisfies I2= I but is not singular.

A2= A is equivalent to A2- A= A(A-I)= 0. It does NOT follow that "A= 0 or A= I" but it does follow that either A or A- I has determinant 0.
 
  • #29
HallsofIvy said:
A2= A is equivalent to A2- A= A(A-I)= 0. It does NOT follow that "A= 0 or A= I" but it does follow that either A or A- I has determinant 0.

Oh wow! I never looked at it that way! How does it follow that A has determinant 0?

-Thanks!
 
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  • #30
I was thinking, since I've proven the only non-singular idempotent matrix is the identity matrix, wouldn't it follow that the only other idempotent matrices must be singular?
 
  • #32
Wow I'm an imbecile. I skipped over that fact and just focused on trying to prove which singular matrices would fit the bill, but this was not required.

Thank you so much for your guidance! I learned more than what the proof expected of me.
 

1. What is a square matrix?

A square matrix is a matrix with the same number of rows and columns, meaning it has an equal number of elements in each row and column. It is denoted by the dimensions of the matrix, such as a 3x3 or 4x4 matrix.

2. How can a matrix be equal to its own square?

In order for a matrix to be equal to its own square, the matrix must be a special type known as an idempotent matrix. This means that when the matrix is multiplied by itself, the result is the same matrix. This can only occur when the matrix has certain properties, such as being symmetric or having certain values along the main diagonal.

3. What are the conditions for a matrix to be idempotent?

There are a few conditions that a matrix must meet in order to be idempotent. First, it must be a square matrix. Second, it must have at least one eigenvalue of either 0 or 1. Third, it must have a set of linearly independent eigenvectors. Lastly, the matrix must be diagonalizable, meaning it can be transformed into a diagonal matrix using a similarity transformation.

4. Can any matrix be equal to its own square?

No, not all matrices can be equal to their own square. As mentioned before, the matrix must meet certain conditions, such as being idempotent, in order for this to be true. Additionally, not all matrices are square, and therefore cannot even be squared.

5. What are some applications of idempotent matrices?

Idempotent matrices have various applications in mathematics, computer science, and engineering. They are commonly used in linear algebra, statistics, and optimization problems. In computer science, they are used in algorithms and data structures, such as in graph theory and Markov chains. In engineering, they are used in control systems and signal processing.

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