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The geometric multiplicity of an eigenvalue does not exceed its algebraic multiplicity
Statement
Let be an endomorphism of a finite-dimensional vector space, and let be an eigenvalue. Then
Facts & Assumptions
Given: A finite-dimensional -vector space , , and an eigenvalue .
Geometric multiplicity is , while algebraic multiplicity is the largest exponent of dividing (Algebraic multiplicity as the exponent of in , and geometric multiplicity as ).
A linearly independent subset of a finite-dimensional space extends, without Choice, to a basis (If and is a linear subspace of , then is finite-dimensional, , and if and only if , clause 3).
The matrix of a linear map records the coordinate columns of the images of the basis vectors (Coordinate columns and matrices of linear maps relative to ordered bases).
The characteristic polynomial of a block-triangular matrix is the product of those of its diagonal blocks (The characteristic polynomial of a block upper- or lower-triangular matrix is the product of the characteristic polynomials of its diagonal blocks).
Proof
Put . Choose a basis of the eigenspace and extend it by [L2] to a basis of .
Since for , [L3] makes the matrix of in this basis block upper triangular with leading diagonal block .
By [L4], for the characteristic polynomial of the other diagonal block.
Thus divides , so the maximal exponent in [L1] is at least . This is the claimed inequality; because is an eigenvalue.
Depends on
- Algebraic multiplicity as the exponent of $x-\lambda$ in $\chi_T$, and geometric multiplicity as $\dim E_\lambda(T)$
- The characteristic polynomial of a block upper- or lower-triangular matrix is the product of the characteristic polynomials of its diagonal blocks
- If $\dim_F V = n$ and $U$ is a linear subspace of $V$, then $U$ is finite-dimensional, $\dim_F U \le n$, and $\dim_F U = n$ if and only if $U = V$
- Coordinate columns $[v]_{\mathcal B}$ and matrices $[T]_{\mathcal B}^{\mathcal C}$ of linear maps relative to ordered bases
Used by
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 98 results over 21 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- H. Pinkham, Linear Algebra, §12.2 (standard reference, not scraped)