Eigenvectors and eigenvalues #
This file defines eigenspaces, eigenvalues, and eigenvalues, as well as their generalized counterparts. We follow Axler's approach [Axl15] because it allows us to derive many properties without choosing a basis and without using matrices.
An eigenspace of a linear map f
for a scalar μ
is the kernel of the map (f - μ • id)
. The
nonzero elements of an eigenspace are eigenvectors x
. They have the property f x = μ • x
. If
there are eigenvectors for a scalar μ
, the scalar μ
is called an eigenvalue.
There is no consensus in the literature whether 0
is an eigenvector. Our definition of
HasEigenvector
permits only nonzero vectors. For an eigenvector x
that may also be 0
, we
write x ∈ f.eigenspace μ
.
A generalized eigenspace of a linear map f
for a natural number k
and a scalar μ
is the kernel
of the map (f - μ • id) ^ k
. The nonzero elements of a generalized eigenspace are generalized
eigenvectors x
. If there are generalized eigenvectors for a natural number k
and a scalar μ
,
the scalar μ
is called a generalized eigenvalue.
The fact that the eigenvalues are the roots of the minimal polynomial is proved in
LinearAlgebra.Eigenspace.Minpoly
.
The existence of eigenvalues over an algebraically closed field
(and the fact that the generalized eigenspaces then span) is deferred to
LinearAlgebra.Eigenspace.IsAlgClosed
.
References #
Tags #
eigenspace, eigenvector, eigenvalue, eigen
The submodule genEigenspace f μ k
for a linear map f
, a scalar μ
,
and a number k : ℕ∞
is the kernel of (f - μ • id) ^ k
if k
is a natural number
(see Def 8.10 of [Axl15]), or the union of all these kernels if k = ∞
.
A generalized eigenspace for some exponent k
is contained in
the generalized eigenspace for exponents larger than k
.
Equations
Instances For
Let M
be an R
-module, and f
an R
-linear endomorphism of M
,
and let μ : R
and k : ℕ∞
be given.
Then x : M
satisfies HasUnifEigenvector f μ k x
if
x ∈ f.genEigenspace μ k
and x ≠ 0
.
For k = 1
, this means that x
is an eigenvector of f
with eigenvalue μ
.
Instances For
Let M
be an R
-module, and f
an R
-linear endomorphism of M
.
Then μ : R
and k : ℕ∞
satisfy HasUnifEigenvalue f μ k
if
f.genEigenspace μ k ≠ ⊥
.
For k = 1
, this means that μ
is an eigenvalue of f
.
Instances For
Let M
be an R
-module, and f
an R
-linear endomorphism of M
.
For k : ℕ∞
, we define UnifEigenvalues f k
to be the type of all
μ : R
that satisfy f.HasUnifEigenvalue μ k
.
For k = 1
this is the type of all eigenvalues of f
.
Equations
- f.UnifEigenvalues k = { μ : R // f.HasUnifEigenvalue μ k }
Instances For
The underlying value of a bundled eigenvalue.
Equations
- ↑f k = Subtype.val
Instances For
Equations
- Module.End.UnifEigenvalues.instCoeOut k = { coe := ↑f k }
Equations
- Module.End.UnivEigenvalues.instDecidableEq f k = inferInstanceAs (DecidableEq { x : R // f.HasUnifEigenvalue x k })
A nilpotent endomorphism has nilpotent eigenvalues.
See also LinearMap.isNilpotent_trace_of_isNilpotent
.
Alias of the reverse direction of Module.End.hasUnifEigenvalue_iff_mem_spectrum
.
The generalized eigenrange for a linear map f
, a scalar μ
, and an exponent k ∈ ℕ∞
is the range of (f - μ • id) ^ k
if k
is a natural number,
or the infimum of these ranges if k = ∞
.
Instances For
The exponent of a generalized eigenvalue is never 0.
If there exists a natural number k
such that the kernel of (f - μ • id) ^ k
is the
maximal generalized eigenspace, then this value is the least such k
. If not, this value is not
meaningful.
Equations
- f.maxUnifEigenspaceIndex μ = monotonicSequenceLimitIndex ((f.genEigenspace μ).comp WithTop.coeOrderHom.toOrderHom)
Instances For
For an endomorphism of a Noetherian module, the maximal eigenspace is always of the form kernel
(f - μ • id) ^ k
for some k
.
Generalized eigenspaces for exponents at least finrank K V
are equal to each other.
A generalized eigenvalue for some exponent k
is also
a generalized eigenvalue for exponents larger than k
.
A generalized eigenvalue for some exponent k
is also
a generalized eigenvalue for positive exponents.
Generalized eigenvalues are actually just eigenvalues.
Every generalized eigenvector is a generalized eigenvector for exponent finrank K V
.
(Lemma 8.11 of [Axl15])
Generalized eigenspaces for exponents at least finrank K V
are equal to each other.
The restriction of f - μ • 1
to the k
-fold generalized μ
-eigenspace is nilpotent.
The restriction of f - μ • 1
to the generalized μ
-eigenspace is nilpotent.
The submodule eigenspace f μ
for a linear map f
and a scalar μ
consists of all vectors x
such that f x = μ • x
. (Def 5.36 of [Axl15])
Equations
- f.eigenspace μ = (f.genEigenspace μ) 1
Instances For
A nonzero element of an eigenspace is an eigenvector. (Def 5.7 of [Axl15])
Equations
- f.HasEigenvector μ x = f.HasUnifEigenvector μ 1 x
Instances For
A scalar μ
is an eigenvalue for a linear map f
if there are nonzero vectors x
such that f x = μ • x
. (Def 5.5 of [Axl15])
Equations
- f.HasEigenvalue a = f.HasUnifEigenvalue a 1
Instances For
The eigenvalues of the endomorphism f
, as a subtype of R
.
Equations
- f.Eigenvalues = f.UnifEigenvalues 1
Instances For
Equations
- ↑f = ↑f 1
Instances For
A nilpotent endomorphism has nilpotent eigenvalues.
See also LinearMap.isNilpotent_trace_of_isNilpotent
.
Alias of the reverse direction of Module.End.hasEigenvalue_iff_mem_spectrum
.
A nonzero element of a generalized eigenspace is a generalized eigenvector. (Def 8.9 of [Axl15])
Equations
- f.HasGenEigenvector μ k x = f.HasUnifEigenvector μ (↑k) x
Instances For
A scalar μ
is a generalized eigenvalue for a linear map f
and an exponent k ∈ ℕ
if there
are generalized eigenvectors for f
, k
, and μ
.
Equations
- f.HasGenEigenvalue μ k = f.HasUnifEigenvalue μ ↑k
Instances For
The exponent of a generalized eigenvalue is never 0.
The union of the kernels of (f - μ • id) ^ k
over all k
.
Instances For
If there exists a natural number k
such that the kernel of (f - μ • id) ^ k
is the
maximal generalized eigenspace, then this value is the least such k
. If not, this value is not
meaningful.
Equations
- f.maxGenEigenspaceIndex μ = f.maxUnifEigenspaceIndex μ
Instances For
For an endomorphism of a Noetherian module, the maximal eigenspace is always of the form kernel
(f - μ • id) ^ k
for some k
.
A generalized eigenvalue for some exponent k
is also
a generalized eigenvalue for exponents larger than k
.
The eigenspace is a subspace of the generalized eigenspace.
All eigenvalues are generalized eigenvalues.
All generalized eigenvalues are eigenvalues.
Generalized eigenvalues are actually just eigenvalues.
The restriction of f - μ • 1
to the k
-fold generalized μ
-eigenspace is nilpotent.
The restriction of f - μ • 1
to the generalized μ
-eigenspace is nilpotent.
The restriction of f - μ • 1
to the generalized μ
-eigenspace is nilpotent.
The eigenspaces of a linear operator form an independent family of subspaces of M
. That is,
any eigenspace has trivial intersection with the span of all the other eigenspaces.
Alias of Module.End.eigenspaces_iSupIndep
.
The eigenspaces of a linear operator form an independent family of subspaces of M
. That is,
any eigenspace has trivial intersection with the span of all the other eigenspaces.
Eigenvectors corresponding to distinct eigenvalues of a linear operator are linearly independent.
Eigenvectors corresponding to distinct eigenvalues of a linear operator are linearly independent. (Lemma 5.10 of [Axl15])
We use the eigenvalues as indexing set to ensure that there is only one eigenvector for each
eigenvalue in the image of xs
.
See Module.End.eigenvectors_linearIndependent'
for an indexed variant.
If f
maps a subspace p
into itself, then the generalized eigenspace of the restriction
of f
to p
is the part of the generalized eigenspace of f
that lies in p
.
If p
is an invariant submodule of an endomorphism f
, then the μ
-eigenspace of the
restriction of f
to p
is a submodule of the μ
-eigenspace of f
.
Generalized eigenrange and generalized eigenspace for exponent finrank K V
are disjoint.
If an invariant subspace p
of an endomorphism f
is disjoint from the μ
-eigenspace of f
,
then the restriction of f
to p
has trivial μ
-eigenspace.
The generalized eigenspace of an eigenvalue has positive dimension for positive exponents.
A linear map maps a generalized eigenrange into itself.