Idempotent Matrix: Eigenvalue Must be 0 or 1

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In summary, an idempotent matrix is a square matrix that remains unchanged when multiplied by itself. It can have eigenvalues of 0 or 1, with 0 indicating a projection matrix and 1 indicating an identity matrix. An idempotent matrix cannot have any other eigenvalues besides 0 or 1. These matrices have various real-world applications, such as in statistics, engineering, and computer science. Not all idempotent matrices are invertible, with only those with an eigenvalue of 1 being invertible.
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Dustinsfl
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An nxn matrix A is said to be idempotent if [tex]A^2=A[/tex]. Show that if [tex]\lambda[/tex] is an eigenvalue of an idempotent matrix, then [tex]\lambda[/tex] must be 0 or 1.

The only reason I can think of is that it must 0 or 1 because if you square the values 0 and 1 don't change.
 
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Alright so let x be an eigenvalue to A. That means that Av=xv for some vector v. Then xv=Av=A^2v=A(Av)=A(xv)=x(Av)=x^2v which implies x^2=x so x(x-1)=0 which implies that the eigenvalues to A are either 1 or 0
 

1. What is an idempotent matrix?

An idempotent matrix is a square matrix that, when multiplied by itself, results in the same matrix. In other words, the matrix remains unchanged after the multiplication. This is represented mathematically as A*A = A, where A is the idempotent matrix.

2. What is the significance of an idempotent matrix having eigenvalue of either 0 or 1?

The eigenvalue of an idempotent matrix determines its behavior when multiplied by itself. If the eigenvalue is 0, the matrix is a projection matrix, meaning it projects a vector onto a subspace. If the eigenvalue is 1, the matrix is an identity matrix, meaning it leaves a vector unchanged.

3. Can an idempotent matrix have other eigenvalues besides 0 or 1?

No, an idempotent matrix can only have eigenvalues of 0 or 1. This is because the matrix must satisfy the equation A*A = A, which can only be true if the eigenvalues are 0 or 1.

4. How are idempotent matrices used in real-world applications?

Idempotent matrices have various applications in fields such as statistics, engineering, and computer science. They are often used in linear transformations, data compression, and error correction codes. In statistics, idempotent matrices are used in regression analysis and in calculating sums of squares in ANOVA tables.

5. Are all idempotent matrices invertible?

No, not all idempotent matrices are invertible. If the eigenvalue of an idempotent matrix is 0, then it is not invertible. However, if the eigenvalue is 1, then the matrix is invertible and its inverse is itself.

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