Jump to content

Linear algebra (Osnabrück 2024-2025)/Part I/Exercise sheet 23/refcontrol

From Wikiversity



Exercise for the break

Compute the characteristic polynomialMDLD/characteristic polynomial of the matrixMDLD/matrix

(253742375).




Exercises

Determine the characteristic polynomial and the eigenvalues of the linear mapping

φ:33,

given by the matrix

A=(242023061)

with respect to the standard basis.


===Exercise Exercise 23.3

change===

Let K be a fieldMDLD/field and let M denote an n×n-matrixMDLD/matrix over K. Show that for every λK, the relation

χM(λ)=det(λEnM)

holds.[1]


Let K be a field and let M be an n×n-matrixMDLD/matrix over K. Where can you find the determinantMDLD/determinant of M within the characteristic polynomialMDLD/characteristic polynomial χM?


Let K be a field,MDLD/field and let M denote an n×n-matrixMDLD/matrix over K. How can we find the trace(M) in the characteristic polynomialMDLD/characteristic polynomial χM?


Determine the characteristic polynomialMDLD/characteristic polynomial of a matrix

(abcd).

What is the relevance of the coefficients of this polynomial?


Determine the characteristic polynomialMDLD/characteristic polynomial of a matrix

(abcdefghi).

What is the relevance of the coefficients of this polynomial?


Compute the characteristic polynomialMDLD/characteristic polynomial of the matrix

(X24X+7X16X5X254X2+3X26X23XX2+8X+9X23X+5)

over the field of rational functionsMDLD/field of rational functions (1) (X).


Compute the characteristic polynomial,MDLD/characteristic polynomial the eigenvaluesMDLD/eigenvalues and the eigenspacesMDLD/eigenspaces of the matrix

(5734)

over .


Determine the characteristic polynomial,MDLD/characteristic polynomial the eigenvalues,MDLD/eigenvalues and the eigenspacesMDLD/eigenspaces of the matrixMDLD/matrix

M=(1214312)

over .


Determine the eigenvalues and the eigenspaces of the linear mapping

φ:33,vMv,

given by the matrix

M=(205010805).


We consider the linear mapping

φ:33

that is given by the matrix

A=(212+i0i1+i001+2i),

with respect to the standard basis.

a) Determine the characteristic polynomial and the eigenvalues of A.


b) Compute, for every eigenvalue, an eigenvector.


c) Establish a matrix for φ with respect to a basis of eigenvectors.


Let

A=(466020335)Mat3×3().

Compute:

  1. the eigenvalues of A;
  2. the corresponding eigenspaces;
  3. the geometric and algebraic multiplicities of each eigenvalue;
  4. a matrix CMat3×3() such that C1AC is a diagonal matrix.


Let

M=(1100011000111001).
  1. Determine the characteristic polynomialMDLD/characteristic polynomial of M.
  2. Determine a zero of the characteristic polynomial of M, and write the polynomial using the corresponding linear factor.
  3. Show that the characteristic polynomial of M has at least two real roots.


Let λ be a zero of the polynomial

X3+2X22.

Show that

(1(1+λ)31(1+λ)21(1+λ)1)

is an eigenvectorMDLD/eigenvector of the matrix

(1100011000111001)

for the eigenvalueMDLD/eigenvalue λ.


To solve the following exercise, besides the preceding exercises also Exercise 10.16 is helpful. ===Exercise Exercise 23.16

change===

We consider the mapping

Ψ:0404

that assigns to a four tuple (a,b,c,d) the four tuple

(|ba|,|cb|,|dc|,|ad|).

Show that there exists a tuple (a,b,c,d), for that arbitrary iterations of the mapping do never reach the zero tuple.


Let K be a field,MDLD/field and let M denote an n×n-matrixMDLD/matrix over K with the property, that the characteristic polynomialMDLD/characteristic polynomial splits into linear factors, that is,

χM=(Xλ1)μ1(Xλ2)μ2(Xλk)μk.

Show that

trace(M)=i=1kμiλi.


Let K be the field with two elements,MDLD/field with two elements we consider the matrixMDLD/matrix

M=(1000)

over K. Show that the characteristic polynomialMDLD/characteristic polynomial χM is not the zero polynomial, but that

χM(λ)=0

holds for all λK.


===Exercise Exercise 23.19

change===

Show that a square matrix and its transposed matrixMDLD/transposed matrix have the same characteristic polynomial.MDLD/characteristic polynomial


What is wrong in the following argumentation:

"For two n×n-matricesMDLD/matrices M,N, the characteristic polynomialsMDLD/characteristic polynomials fulfill the relation

χMN=χMχN.

This is because, by definition, we have

χMN=det(XEnMN)=det(XEnM)det(XEnN)=χMχN,

where the equation in the middle rests on the multiplication theorem for determinants“.


Let M be an n×n-matrix,MDLD/matrix with the characteristic polynomialMDLD/characteristic polynomial

χM=Xn+cn1Xn1+cn2Xn2++c2X2+c1X+c0.

Determine the characteristic polynomial of the scaled matrix sM, sK.


Let K be a field, aK and m,n+ numbers with 1mn. Give an example of an n×n-matrixMDLD/matrix M, such that a is an eigenvalueMDLD/eigenvalue for M with algebraic multiplicityMDLD/algebraic multiplicity n and geometric multiplicityMDLD/geometric multiplicity m.


Let KL be a field extension.MDLD/field extension Let an n×n-matrixMDLD/matrix M over K be given. Show that the characteristic polynomialMDLD/characteristic polynomial χMK[X] coincides with the characteristic polynomial of M, considered as a matrix over L.


===Exercise Exercise 23.24

change===

Show that the characteristic polynomial of a linear mappingMDLD/linear mapping φ:VV on a finite-dimensionalMDLD/finite-dimensional (vs) K-vector spaceMDLD/vector space V is well-defined, that is, independent of the chosen basis.MDLD/basis (vs)


Let V be a finite-dimensionalMDLD/finite-dimensional (vs) K-vector space, and let φEnd(V). Show that the following statements are equivalent:

  1. The linear mapping φ is an isomorphism.
  2. 0 is not an eigenvalue of φ.
  3. The constant term of the characteristic polynomial χφ is 0.


Let

φ:VV

be an endomorphismMDLD/endomorphism (vs) on a finite-dimensionalMDLD/finite-dimensional K-vector spaceMDLD/vector space V, and let aK an eigenvalueMDLD/eigenvalue of φ. Show that a is also an eigenvalue of the dual mappingMDLD/dual mapping

φ:VV.


We consider the real matrix

M=(1110).


a) Determine

Mn(10)

for n=1,2,3,4.


b) Let

(xn+1yn+1):=Mn(10).

Establish a relation between the sequences xn and yn, and determine a recursive formula for these sequences.


c) Determine the eigenvalues and the eigenvectors of M.


===Exercise Exercise 23.28

change===

Let K denote a field,MDLD/field and let V denote a K-vector spaceMDLD/vector space of finite dimension. Let

φ:VV

be a linear mapping.MDLD/linear mapping Suppose that the characteristic polynomialMDLD/characteristic polynomial χφ factors into different linear factors.MDLD/linear factors (1K) Show that φ is diagonalizable.MDLD/diagonalizable


Let φ:VV a linear mappingMDLD/linear mapping on a K-vector spaceMDLD/vector space V over a field K. Show the following properties.

  1. The zero spaceMDLD/zero space 0V is φ-invariant.MDLD/invariant (subspace)
  2. V is φ-invariant.
  3. EigenspacesMDLD/Eigenspaces are φ-invariant.
  4. Let U1,U2V be φ-invariant linear subspaces. Then also U1U2 and U1+U2 are φ-invariant.
  5. Let UV be a φ-invariant linear subspace. Then also the image spaceMDLD/image space φ(U) and the preimage spaceMDLD/preimage space φ1(U) are φ-invariant.


Let φ:VV a linear mappingMDLD/linear mapping on a K-vector spaceMDLD/vector space V over a field K, and let vV. Show that the smallest φ-invariant linear subspaceMDLD/invariant linear subspace of V that contains v, equals

φn(v),n.


===Exercise Exercise 23.31

change===

Let K be a field,MDLD/field let V be a K-vector space,MDLD/vector space and let

φ:VV

a linear mapping.MDLD/linear mapping Let UV be a φ-invariant linear subspaceMDLD/invariant linear subspace of V. Show that, for a polynomial PK[X], the space U is also P(φ)-invariant.


Let φ:VV be a linear mappingMDLD/linear mapping on a K-vector spaceMDLD/vector space V. Let v1,,vn be a basisMDLD/basis (vs) of V, such that φ is described, with respect to this basis, by an upper triangular matrix.MDLD/upper triangular matrix Show that the linear subspacesMDLD/linear subspaces

v1,,vi

are φ-invariantMDLD/invariant (endomorphism) for every i.


Let φ:VV a linear mappingMDLD/linear mapping on a K-vector spaceMDLD/vector space V over a field K. Show that the subset of V, defined by

U={vV there exists an n with φn(v)=0},

is an φ-invariant linear subspace.MDLD/invariant linear subspace


Let φ:VV be a linear mappingMDLD/linear mapping on a finite-dimensionalMDLD/finite-dimensional K-vector spaceMDLD/vector space V. Let kn. Show that there exists an invariant linear subspaceMDLD/invariant linear subspace (endomorphism) UV of dimension k, if and only if there exists a basisMDLD/basis (vs) of V such that the describing matrixMDLD/describing matrix of φ, with respect to this basis, has the form

(a11a1ka1k+1a1nak1akkakk+1akn00ak+1k+1ak+1n00ank+1ann).


Let φ:VV be a linear mappingMDLD/linear mapping on the finite-dimensionalMDLD/finite-dimensional K-vector spaceMDLD/vector space V. Let kn. Show that there exists a direct sum decompositionMDLD/direct sum decomposition V=UW into invariant linear subspacesMDLD/invariant linear subspaces (endomorphism) U,WV of dimension k and nk, if and only if there exists a basisMDLD/basis (vs) of V such that the describing matrixMDLD/describing matrix of φ with respect to this basis has the form

(a11a1k00ak1akk0000ak+1k+1ak+1n00ank+1ann).


Let V be a finite-dimensionalMDLD/finite-dimensional K-vector space,MDLD/vector space and UV a linear subspace.MDLD/linear subspace Show that

R(U)={φEnd(V)U is a φinvariant linear subspace}

is, with the natural addition and multiplication of endomorphisms, a ring,MDLD/ring and a linear subspaceMDLD/linear subspace of End(V). Determine the dimensionMDLD/dimension (vs) of this space.




Hand-in-exercises

Compute the characteristic polynomialMDLD/characteristic polynomial of the matrixMDLD/matrix

(385471245).


Compute the characteristic polynomial,MDLD/characteristic polynomial the eigenvaluesMDLD/eigenvalues and the eigenspacesMDLD/eigenspaces of the matrix

(2754)

over .


Let

A=(507626406)Mat3×3().

Compute:

  1. the eigenvalues of A;
  2. the corresponding eigenspaces;
  3. the geometric and algebraic multiplicities of each eigenvalue;
  4. a matrix CMat3×3() such that C1AC is a diagonal matrix.


Determine for every λ the algebraicMDLD/algebraic (multiplicity) and geometricMDLD/geometric (multiplicity) multiplicities for the matrixMDLD/matrix

M=(345012003).


Show that the characteristic polynomialMDLD/characteristic polynomial of the so-called companion matrix

M=(010000100001a0a1an2an1)

equals

χM=Xn+an1Xn1++a1X+a0.


Let

φ:33

be a linear mapping.MDLD/linear mapping Show that φ has at least one eigenvector.MDLD/eigenvector




Footnotes
  1. The main difficulty might be here to recognize that there is indeed something to show.


<< | Linear algebra (Osnabrück 2024-2025)/Part I | >>
PDF-version of this exercise sheet
Lecture for this exercise sheet (PDF)