# Morphisms of free modules¶

AUTHORS:
• William Stein: initial version
• Miguel Marco (2010-06-19): added eigenvalues, eigenvectors and minpoly functions

TESTS:

sage: V = ZZ^2; f = V.hom([V.1,-2*V.0])
Free module morphism defined by the matrix
[ 0  1]
[-2  0]
Domain: Ambient free module of rank 2 over the principal ideal domain ...
Codomain: Ambient free module of rank 2 over the principal ideal domain ...
True

class sage.modules.free_module_morphism.FreeModuleMorphism(parent, A)

INPUT:

• parent - a homspace in a (sub) category of free modules
• A - matrix

EXAMPLES:

sage: V = ZZ^3; W = span([[1,2,3],[-1,2,8]], ZZ)
sage: phi = V.hom(matrix(ZZ,3,[1..9]))
sage: type(phi)
<class 'sage.modules.free_module_morphism.FreeModuleMorphism'>

change_ring(R)

Change the ring over which this morphism is defined. This changes the ring of the domain, codomain, and underlying matrix.

EXAMPLES:

sage: V0 = span([[0,0,1],[0,2,0]],ZZ); V1 = span([[1/2,0],[0,2]],ZZ); W = span([[1,0],[0,6]],ZZ)
sage: h = V0.hom([-3*V1.0-3*V1.1, -3*V1.0-3*V1.1])
sage: h.base_ring()
Integer Ring
sage: h
Free module morphism defined by the matrix
[-3 -3]
[-3 -3]...
sage: h.change_ring(QQ).base_ring()
Rational Field
sage: f = h.change_ring(QQ); f
Vector space morphism represented by the matrix:
[-3 -3]
[-3 -3]
Domain: Vector space of degree 3 and dimension 2 over Rational Field
Basis matrix:
[0 1 0]
[0 0 1]
Codomain: Vector space of degree 2 and dimension 2 over Rational Field
Basis matrix:
[1 0]
[0 1]
sage: f = h.change_ring(GF(7)); f
Vector space morphism represented by the matrix:
[4 4]
[4 4]
Domain: Vector space of degree 3 and dimension 2 over Finite Field of size 7
Basis matrix:
[0 1 0]
[0 0 1]
Codomain: Vector space of degree 2 and dimension 2 over Finite Field of size 7
Basis matrix:
[1 0]
[0 1]

eigenspaces(extend=True)

Compute a list of subspaces formed by eigenvectors of self.

INPUT:

• extend – (default: True) determines if field extensions should be considered

OUTPUT:

• a list of pairs (eigenvalue, eigenspace)

EXAMPLES:

sage: V = QQ^3
sage: h = V.hom([[1,0,0],[0,0,1],[0,-1,0]], V)
sage: h.eigenspaces()
[(1,
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[1 0 0]),
(-1*I,
Vector space of degree 3 and dimension 1 over Algebraic Field
Basis matrix:
[  0   1 1*I]),
(1*I,
Vector space of degree 3 and dimension 1 over Algebraic Field
Basis matrix:
[   0    1 -1*I])]

sage: h.eigenspaces(extend=False)
[(1,
Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[1 0 0])]

sage: h = V.hom([[2,1,0], [0,2,0], [0,0,-1]], V)
sage: h.eigenspaces()
[(-1, Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[0 0 1]),
(2, Vector space of degree 3 and dimension 1 over Rational Field
Basis matrix:
[0 1 0])]

sage: h = V.hom([[2,1,0], [0,2,0], [0,0,2]], V)
sage: h.eigenspaces()
[(2, Vector space of degree 3 and dimension 2 over Rational Field
Basis matrix:
[0 1 0]
[0 0 1])]

eigenvalues(extend=True)

Returns a list with the eigenvalues of the endomorphism of vector spaces.

INPUT:

• extend – boolean (default: True) decides if base field extensions should be considered or not.

EXAMPLES:

We compute the eigenvalues of an endomorphism of $$\QQ^3$$:

sage: V=QQ^3
sage: H=V.endomorphism_ring()([[1,-1,0],[-1,1,1],[0,3,1]])
sage: H.eigenvalues()
[3, 1, -1]


Note the effect of the extend option:

sage: V=QQ^2
sage: H=V.endomorphism_ring()([[0,-1],[1,0]])
sage: H.eigenvalues()
[-1*I, 1*I]
sage: H.eigenvalues(extend=False)
[]

eigenvectors(extend=True)

Computes the subspace of eigenvectors of a given eigenvalue.

INPUT:

• extend – boolean (default: True) decides if base field extensions should be considered or not.

OUTPUT:

A sequence of tuples. Each tuple contains an eigenvalue, a sequence with a basis of the corresponding subspace of eigenvectors, and the algebraic multiplicity of the eigenvalue.

EXAMPLES:

sage: V=(QQ^4).subspace([[0,2,1,4],[1,2,5,0],[1,1,1,1]])
sage: H=(V.Hom(V))(matrix(QQ, [[0,1,0],[-1,0,0],[0,0,3]]))
sage: H.eigenvectors()
[(3, [
(0, 0, 1, -6/7)
], 1), (-1*I, [
(1, 1*I, 0, -0.571428571428572? + 2.428571428571429?*I)
], 1), (1*I, [
(1, -1*I, 0, -0.571428571428572? - 2.428571428571429?*I)
], 1)]
sage: H.eigenvectors(extend=False)
[(3, [
(0, 0, 1, -6/7)
], 1)]
sage: H1=(V.Hom(V))(matrix(QQ, [[2,1,0],[0,2,0],[0,0,3]]))
sage: H1.eigenvectors()
[(3, [
(0, 0, 1, -6/7)
], 1), (2, [
(0, 1, 0, 17/7)
], 2)]
sage: H1.eigenvectors(extend=False)
[(3, [
(0, 0, 1, -6/7)
], 1), (2, [
(0, 1, 0, 17/7)
], 2)]

inverse_image(V)

Given a submodule V of the codomain of self, return the inverse image of V under self, i.e., the biggest submodule of the domain of self that maps into V.

EXAMPLES:

We test computing inverse images over a field:

sage: V = QQ^3; W = span([[1,2,3],[-1,2,5/3]], QQ)
sage: phi = V.hom(matrix(QQ,3,[1..9]))
sage: phi.rank()
2
sage: I = phi.inverse_image(W); I
Vector space of degree 3 and dimension 2 over Rational Field
Basis matrix:
[   1    0    0]
[   0    1 -1/2]
sage: phi(I.0) in W
True
sage: phi(I.1) in W
True
sage: W = phi.image()
sage: phi.inverse_image(W) == V
True


We test computing inverse images between two spaces embedded in different ambient spaces.:

sage: V0 = span([[0,0,1],[0,2,0]],ZZ); V1 = span([[1/2,0],[0,2]],ZZ); W = span([[1,0],[0,6]],ZZ)
sage: h = V0.hom([-3*V1.0-3*V1.1, -3*V1.0-3*V1.1])
sage: h.inverse_image(W)
Free module of degree 3 and rank 2 over Integer Ring
Echelon basis matrix:
[0 2 1]
[0 0 2]
sage: h(h.inverse_image(W)).is_submodule(W)
True
sage: h(h.inverse_image(W)).index_in(W)
+Infinity
sage: h(h.inverse_image(W))
Free module of degree 2 and rank 1 over Integer Ring
Echelon basis matrix:
[ 3 12]


We test computing inverse images over the integers:

sage: V = QQ^3; W = V.span_of_basis([[2,2,3],[-1,2,5/3]], ZZ)
sage: phi = W.hom([W.0, W.0-W.1])
sage: Z = W.span([2*W.1]); Z
Free module of degree 3 and rank 1 over Integer Ring
Echelon basis matrix:
[    2    -4 -10/3]
sage: Y = phi.inverse_image(Z); Y
Free module of degree 3 and rank 1 over Integer Ring
Echelon basis matrix:
[  6   0 8/3]
sage: phi(Y) == Z
True

lift(x)

Given an element of the image, return an element of the codomain that maps onto it.

Note that lift and preimage_representative are equivalent names for this method, with the latter suggesting that the return value is a coset representative of the domain modulo the kernel of the morphism.

EXAMPLE:

sage: X = QQ**2
sage: V = X.span([[2, 0], [0, 8]], ZZ)
sage: W = (QQ**1).span([[1/12]], ZZ)
sage: f = V.hom([W([1/3]), W([1/2])], W)
sage: f.lift([1/3])
(8, -16)
sage: f.lift([1/2])
(12, -24)
sage: f.lift([1/6])
(4, -8)
sage: f.lift([1/12])
Traceback (most recent call last):
...
ValueError: element is not in the image
sage: f.lift([1/24])
Traceback (most recent call last):
...
TypeError: element (= [1/24]) is not in free module


This works for vector spaces, too:

sage: V = VectorSpace(GF(3), 2)
sage: W = VectorSpace(GF(3), 3)
sage: f = V.hom([W.1, W.1 - W.0])
sage: f.lift(W.1)
(1, 0)
sage: f.lift(W.2)
Traceback (most recent call last):
...
ValueError: element is not in the image
sage: w = W((17, -2, 0))
sage: f(f.lift(w)) == w
True


This example illustrates the use of the preimage_representative as an equivalent name for this method.

sage: V = ZZ^3
sage: W = ZZ^2
sage: w = vector(ZZ, [1,2])
sage: f = V.hom([w, w, w], W)
sage: f.preimage_representative(vector(ZZ, [10, 20]))
(0, 0, 10)

minimal_polynomial(var='x')

Computes the minimal polynomial.

minpoly() and minimal_polynomial() are the same method.

INPUT:

• var - string (default: ‘x’) a variable name

OUTPUT:

polynomial in var - the minimal polynomial of the endomorphism.

EXAMPLES:

Compute the minimal polynomial, and check it.

sage: V=GF(7)^3
sage: H=V.Hom(V)([[0,1,2],[-1,0,3],[2,4,1]])
sage: H
Vector space morphism represented by the matrix:
[0 1 2]
[6 0 3]
[2 4 1]
Domain: Vector space of dimension 3 over Finite Field of size 7
Codomain: Vector space of dimension 3 over Finite Field of size 7

sage: H.minpoly()
x^3 + 6*x^2 + 6*x + 1

sage: H.minimal_polynomial()
x^3 + 6*x^2 + 6*x + 1

sage: H^3 + (H^2)*6 + H*6 + 1
Vector space morphism represented by the matrix:
[0 0 0]
[0 0 0]
[0 0 0]
Domain: Vector space of dimension 3 over Finite Field of size 7
Codomain: Vector space of dimension 3 over Finite Field of size 7

minpoly(var='x')

Computes the minimal polynomial.

minpoly() and minimal_polynomial() are the same method.

INPUT:

• var - string (default: ‘x’) a variable name

OUTPUT:

polynomial in var - the minimal polynomial of the endomorphism.

EXAMPLES:

Compute the minimal polynomial, and check it.

sage: V=GF(7)^3
sage: H=V.Hom(V)([[0,1,2],[-1,0,3],[2,4,1]])
sage: H
Vector space morphism represented by the matrix:
[0 1 2]
[6 0 3]
[2 4 1]
Domain: Vector space of dimension 3 over Finite Field of size 7
Codomain: Vector space of dimension 3 over Finite Field of size 7

sage: H.minpoly()
x^3 + 6*x^2 + 6*x + 1

sage: H.minimal_polynomial()
x^3 + 6*x^2 + 6*x + 1

sage: H^3 + (H^2)*6 + H*6 + 1
Vector space morphism represented by the matrix:
[0 0 0]
[0 0 0]
[0 0 0]
Domain: Vector space of dimension 3 over Finite Field of size 7
Codomain: Vector space of dimension 3 over Finite Field of size 7

preimage_representative(x)

Given an element of the image, return an element of the codomain that maps onto it.

Note that lift and preimage_representative are equivalent names for this method, with the latter suggesting that the return value is a coset representative of the domain modulo the kernel of the morphism.

EXAMPLE:

sage: X = QQ**2
sage: V = X.span([[2, 0], [0, 8]], ZZ)
sage: W = (QQ**1).span([[1/12]], ZZ)
sage: f = V.hom([W([1/3]), W([1/2])], W)
sage: f.lift([1/3])
(8, -16)
sage: f.lift([1/2])
(12, -24)
sage: f.lift([1/6])
(4, -8)
sage: f.lift([1/12])
Traceback (most recent call last):
...
ValueError: element is not in the image
sage: f.lift([1/24])
Traceback (most recent call last):
...
TypeError: element (= [1/24]) is not in free module


This works for vector spaces, too:

sage: V = VectorSpace(GF(3), 2)
sage: W = VectorSpace(GF(3), 3)
sage: f = V.hom([W.1, W.1 - W.0])
sage: f.lift(W.1)
(1, 0)
sage: f.lift(W.2)
Traceback (most recent call last):
...
ValueError: element is not in the image
sage: w = W((17, -2, 0))
sage: f(f.lift(w)) == w
True


This example illustrates the use of the preimage_representative as an equivalent name for this method.

sage: V = ZZ^3
sage: W = ZZ^2
sage: w = vector(ZZ, [1,2])
sage: f = V.hom([w, w, w], W)
sage: f.preimage_representative(vector(ZZ, [10, 20]))
(0, 0, 10)

sage.modules.free_module_morphism.is_FreeModuleMorphism(x)

EXAMPLES:

sage: V = ZZ^2; f = V.hom([V.1,-2*V.0])
sage: sage.modules.free_module_morphism.is_FreeModuleMorphism(f)
True
sage: sage.modules.free_module_morphism.is_FreeModuleMorphism(0)
False


#### Previous topic

Homspaces between free modules

#### Next topic

Morphisms defined by a matrix