Eigenvalue kind of nilpotent problem

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In summary, if a fixed vector and linear mapping are given, and there exist certain numbers that make a certain equation equal to 0, then it is possible for there to be other numbers and powers that make a similar equation equal to 0. However, this only happens if the vector is equal to 0. Additionally, if two polynomials with no common factor make the same equation equal to 0, then the vector must also be equal to 0.
  • #1
jostpuur
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If a vector [tex]v\in V[/tex] and a linear mapping [tex]T:V\to V[/tex] are fixed, and there exists numbers [tex]\lambda_1\in\mathbb{C}[/tex], [tex]n_1\in\mathbb{N}[/tex] so that

[tex]
(T - \lambda_1)^{n_1}v = 0,
[/tex]

is it possible that there exists some [tex]\lambda_2\neq\lambda_1[/tex], and [tex]n_2\in\mathbb{N}[/tex] so that

[tex]
(T - \lambda_2)^{n_2}v = 0?
[/tex]

(Here complex numbers are interpreted as multiplication operators [tex]V\to V[/tex], [tex]v\mapsto \lambda v[/tex], as usual.)
 
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  • #2
That happens iff v=0. This is the statement that the intersection of different generalized eigenspaces is {0}.
 
  • #3
Furthermore, if f,g are any two polynomials with no common factor and f(T)v=g(T)v=0 then you can conclude that v=0.
 

FAQ: Eigenvalue kind of nilpotent problem

What is the Eigenvalue kind of nilpotent problem?

The Eigenvalue kind of nilpotent problem is a mathematical problem that involves finding the eigenvalues of a matrix that is nilpotent, meaning that when raised to a certain power, it becomes the zero matrix.

Why is the Eigenvalue kind of nilpotent problem important?

This problem is important in various fields of science, such as physics, engineering, and computer science, as it allows for the analysis and prediction of the behavior of systems described by nilpotent matrices.

How is the Eigenvalue kind of nilpotent problem solved?

The Eigenvalue kind of nilpotent problem is typically solved by finding the characteristic polynomial of the nilpotent matrix and then solving for its roots, which are the eigenvalues.

What is the significance of the eigenvalues in this problem?

The eigenvalues of a nilpotent matrix provide important information about the behavior and stability of the system described by the matrix. They can also be used to find the corresponding eigenvectors, which represent the directions in which the system changes the most.

Are there any real-world applications of the Eigenvalue kind of nilpotent problem?

Yes, there are many real-world applications of this problem, such as in the study of electrical circuits, mechanical systems, and chemical reactions. It is also used in computer graphics and image processing for data compression and image enhancement.

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