Zero eigenvalue and null space

In summary, if there is a linear operator ##T## in a finite dimensional complex vector space with a zero eigenvalue, then the corresponding eigenvector ##v## satisfies ##Tv=0v=0##. This means that the null space of ##T## consists of all eigenvectors with the zero eigenvalue, and the 0 vector. On the other hand, if ##T## does not have a zero eigenvalue, its null space is just the 0 vector. In this case, ##T## is equivalent to being injective.
  • #1
maNoFchangE
116
4
Suppose ##T## is an operator in a finite dimensional complex vector space and it has a zero eigenvalue. If ##v## is the corresponding eigenvector, then
$$
Tv=0v=0
$$
Does it mean then that ##\textrm{null }T## consists of all eigenvectors with the zero eigenvalue?
What if ##T## does not have zero eigenvalue? Does it mean that its null space is just the zero vector?

Thanks
 
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  • #2
maNoFchangE said:
Suppose ##T## is an operator in a finite dimensional complex vector space and it has a zero eigenvalue. If ##v## is the corresponding eigenvector, then
$$
Tv=0v=0
$$
Does it mean then that ##\textrm{null }T## consists of all eigenvectors with the zero eigenvalue?
What if ##T## does not have zero eigenvalue? Does it mean that its null space is just the zero vector?

Thanks
Yes.
(Except that ##\textrm{null }T## consists of all eigenvectors with the zero eigenvalue and the 0 vector.)
 
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Likes maNoFchangE
  • #3
Samy_A said:
Yes.
So, the answer to all of my questions is affirmative?
Then, if ##T## does not have a zero eigenvalue, it's equivalent of being injective.
 
  • #4
maNoFchangE said:
So, the answer to all of my questions is affirmative?
Then, if ##T## does not have a zero eigenvalue, it's equivalent of being injective.
For a linear operator, yes.
(I should have mentioned that in my first answer too, I just assumed you meant that T is a linear operator.)
 
  • #5
Yes, it's linear.
 

Related to Zero eigenvalue and null space

What is a zero eigenvalue?

A zero eigenvalue is a value that results when solving for the eigenvalues of a matrix or linear transformation. It indicates that there is at least one eigenvector associated with this value, and it is also known as a characteristic value or latent root.

What is the significance of a zero eigenvalue?

The significance of a zero eigenvalue lies in its relationship to the null space of a matrix. A zero eigenvalue indicates that there is at least one linearly independent vector in the null space of the matrix, which can provide valuable information about the properties and behavior of the matrix.

How is the null space related to zero eigenvalues?

The null space of a matrix is defined as the set of all vectors that, when multiplied by the matrix, result in a zero vector. Zero eigenvalues are related to the null space because they indicate the presence of linearly independent vectors in the null space.

What is the difference between a zero eigenvalue and a zero matrix?

A zero eigenvalue is a numerical value that is obtained through the process of solving for eigenvalues, while a zero matrix is a matrix in which all elements are equal to zero. A zero eigenvalue is a property of a matrix, while a zero matrix is a specific type of matrix.

How can zero eigenvalues be used in practical applications?

Zero eigenvalues can be used in a variety of practical applications, such as in data analysis and machine learning algorithms. They can also be used to analyze the stability of a system, as well as to identify important features or patterns in a dataset. Additionally, zero eigenvalues are commonly used in solving differential equations and in quantum mechanics.

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