Is this matrix diagonalizable?

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In summary, the given matrix is not diagonalizable because the algebraic multiplicity of the eigenvalue -3 is 2, but the geometric multiplicity is either 1 or 2. This means there are not enough linearly independent eigenvectors to diagonalize the matrix.
  • #1
stunner5000pt
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is htis matrix diagonalizable?
[tex] \left( \begin{array}{ccc}4&0&0\\0&2&2\\2&3&1 \end{array} \right) [/tex]
the characteristic polynomial is [tex] (x+1)(x-4)^2 [/tex]
whats worng with the multiplicity here?
the back of the book says dim(E4) =1 and here multiplicity is 2?

but what about this problem
[tex] \left( \begin{array}{ccc}3&0&6\\0&-3&0\\5&0&2 \end{array} \right) [/tex]
whose characteristic polynomial is [tex] (\lambda +3)^2 (\lambda -8) = C_{A} (x) [/tex]
here the multiplicity of lambda = -3 is 2 and the [itex] dim(E_{-3}) = ??
what is the dimension of E (-3)??
 
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  • #2
The dimension of the eigenspace of -3 is the number of independent eigenvectors you can find for the eigenvalue -3. This will be either 1 or 2 eigenvectors. To find them, row reduce (A - (-3)I)x = 0.
 
  • #3
There's a difference between the algebraic multiplicity (AM, which is the multiplicity of the root in the characteristic polynomial) and the geometric multiplicity (GM, which is the dimension of the eigenspace belonging to that eigenvalue, so the number of linearly independant eigenvectors).
When AM > GM for a certain eigenvalue (GM > AM isn't possible), then the matrix is not diagonalizable since you won't have enough linearly independant eigenvectors.
 

FAQ: Is this matrix diagonalizable?

What does it mean for a matrix to be diagonalizable?

Diagonalizable matrices are square matrices that can be transformed into a diagonal matrix through a similarity transformation. This means that the matrix can be written as a product of three matrices: A = PDP^-1, where D is a diagonal matrix and P is an invertible matrix.

How can I determine if a matrix is diagonalizable?

To determine if a matrix is diagonalizable, you can calculate its eigenvalues and eigenvectors. If the matrix has n distinct eigenvalues, then it is diagonalizable. Alternatively, you can also check if the geometric and algebraic multiplicities of each eigenvalue are equal.

Can a non-square matrix be diagonalizable?

No, a non-square matrix cannot be diagonalizable. Only square matrices can have eigenvalues and eigenvectors, which are essential for determining if a matrix is diagonalizable.

What is the significance of diagonalizable matrices?

Diagonalizable matrices have many useful properties that make them important in various fields of mathematics and science. For example, they are often used in linear algebra to simplify calculations and solve systems of linear equations. They also have applications in physics, engineering, and computer science.

Are all diagonalizable matrices invertible?

No, not all diagonalizable matrices are invertible. A diagonalizable matrix is only invertible if all of its eigenvalues are non-zero. However, even if a diagonalizable matrix is not invertible, it can still be used for certain operations, such as diagonalization and similarity transformations.

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