eigenspace
Let be a vector space over a field . Fix a linear transformation on . Suppose is an eigenvalue of . The set is called the eigenspace (of ) corresponding to . Let us write this set .
Below are some basic properties of eigenspaces.
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1.
can be viewed as the kernel of the linear transformation . As a result, is a subspace of .
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2.
The dimension of is called the geometric multiplicity of . Let us denote this by . It is easy to see that , since the existence of an eigenvalue means the existence of a non-zero eigenvector corresponding to the eigenvalue.
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3.
is an invariant subspace under (-invariant).
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4.
iff .
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5.
In fact, if is the sum of eigenspaces corresponding to eigenvalues of other than , then .
From now on, we assume finite-dimensional.
Let be the set of all eigenvalues of and let . We have the following properties:
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1.
If is the algebraic multiplicity of , then .
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2.
Suppose the characteristic polynomial of can be factored into linear terms, then is diagonalizable iff for every .
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3.
In other words, if splits over , then is diagonalizable iff .
For example, let be given by . Using the standard basis, is represented by the matrix
From this matrix, it is easy to see that is the characteristic polynomial of and is the only eigenvalue of with . Also, it is not hard to see that only when . So is a one-dimensional subspace of generated by . As a result, is not diagonalizable.
Title | eigenspace |
---|---|
Canonical name | Eigenspace |
Date of creation | 2013-03-22 17:23:07 |
Last modified on | 2013-03-22 17:23:07 |
Owner | CWoo (3771) |
Last modified by | CWoo (3771) |
Numerical id | 9 |
Author | CWoo (3771) |
Entry type | Definition |
Classification | msc 15A18 |