Diagonalizable endomorphism has trivial null space

In summary, a diagonalizable endomorphism is a linear transformation that can be represented by a diagonal matrix with respect to some basis. A null space, or kernel, is the set of all vectors that are mapped to the zero vector by a given linear transformation. It is important for a diagonalizable endomorphism to have a trivial null space in order to ensure it is one-to-one. An endomorphism is diagonalizable if and only if it has a full set of linearly independent eigenvectors. A non-square matrix cannot be diagonalizable as it must have the same number of rows and columns to have a full set of linearly independent eigenvectors.
  • #1
Daaavde
30
0
Is it correct to state that a diagonalizable endomorphism has always kernel = {0}?
 
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  • #2
Is the zero operator a diagonalizable endomorphism?
 
  • #3
I still don't understand.
 
  • #4
R13's point was that the zero map is diagonalizable and has kernel the whole space.
 
  • #5
Right, that's the case of the zero operator. But what if my eigenvalues are all non-zero (hence my eigenvectors are all linear indipendent)?
 
  • #6
In that case your operator has trivial kernel.
 
  • #7
Perfect. Thank you.
 

1. What is a diagonalizable endomorphism?

A diagonalizable endomorphism is a linear transformation on a vector space that can be represented by a diagonal matrix with respect to some basis. This means that the transformation only stretches or shrinks each basis vector by a certain scalar value.

2. What is a null space?

A null space, also known as a kernel, is the set of all vectors that are mapped to the zero vector by a given linear transformation. In other words, it is the set of all inputs that result in an output of zero.

3. Why is it important for a diagonalizable endomorphism to have a trivial null space?

Having a trivial null space means that the only vector that is mapped to the zero vector is the zero vector itself. This is important because it ensures that the linear transformation is one-to-one, meaning that each input has a unique output. This is necessary for certain applications, such as solving systems of linear equations.

4. How can you determine if an endomorphism is diagonalizable?

An endomorphism is diagonalizable if and only if it has a full set of linearly independent eigenvectors. This means that the eigenvectors span the entire vector space and can be used as a basis for the transformation's matrix representation.

5. Can a non-square matrix be diagonalizable?

No, a non-square matrix cannot be diagonalizable. In order for a matrix to be diagonalizable, it must have the same number of rows and columns, meaning it must be a square matrix. This is necessary for the matrix to have a full set of linearly independent eigenvectors.

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