Mathematics for Applied Sciences (Osnabrück 2023-2024)/Part I/Exercise sheet 28



Exercises

Exercise

Compute the characteristic polynomial of the matrix


Exercise

Compute the characteristic polynomial, the eigenvalues and the eigenspaces of the matrix

over .


Exercise

Show that the characteristic polynomial of a linear mapping on a finite-dimensional -vector space is well-defined, that is, independent of the chosen basis.


Exercise

Let be a field and let denote an -matrix over . Show that for every , the relation

holds.[1]


Exercise

Let be a field and let be an -matrix over . Where can you find the determinant of within the characteristic polynomial ?


Exercise

Show that the characteristic polynomial of the so-called Companion matrix

equals


Exercise

We consider the real matrix

a) Determine

for .

b) Let

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

c) Determine the eigenvalues and the eigenvectors of .


Exercise

Let

  1. Determine the characteristic polynomial of .
  2. Determine a zero of the characteristic polynomial of , and write the polynomial using the corresponding linear factor.
  3. Show that the characteristic polynomial of has at least two real roots.


Exercise

Let be a zero of the polynomial

Show that

is an eigenvector of the matrix

for the eigenvalue .


To solve the following exercise, the two exercises above and also Exercise 24.31 are helpful.

Exercise

We consider the mapping

which assigns to a four tuple the four tuple

Show that there exists a tuple , for which arbitrary iterations of the mapping do never reach the zero tupel.


Exercise

Determine the eigenvalues and the eigenspaces of the linear mapping

given by the matrix


Exercise

We consider the linear mapping

which is given by the matrix

with respect to the standard basis.

a) Determine the characteristic polynomial and the eigenvalues of .

b) Compute, for every eigenvalue, an eigenvector.

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


Exercise

Let

Compute:

  1. the eigenvalues of ;
  2. the corresponding eigenspaces;
  3. the geometric and algebraic multiplicities of each eigenvalue;
  4. a matrix such that is a diagonal matrix.


Exercise

Determine the eigenspace and the geometric multiplicity for of the matrix


Exercise

Show that the matrix

is diagonalizable over .


Exercise

Let be a matrix with (pairwise) different eigenvalues. Show that the determinant of is the product of the eigenvalues.


Exercise

Let be a field, and numbers with . Give an example of an -matrix , such that is an eigenvalue for with algebraic multiplicity and geometric multiplicity .


Exercise

Determine, which of the following elementary-geometric mappings are linear, which are diagonalizable and which are trigonalizable.

  1. The reflection in the plane, given by the line as axis.
  2. The translation with the vector .
  3. The rotation by degree counter-clockwise around the origin.
  4. The reflection with as center.


Exercise

Determine, whether the real matrix

is trigonalizable or not.


Exercise

Suppose that a linear mapping

is given by the matrix

with respect to the standard basis. Find a basis, such that is described by the matrix

with respect to this basis.


The next exercises use the following definition.

Let be a field, a vector space over and

a linear mapping. A linear subspace is called -invariant, if

holds.

Exercise

Let a linear mapping on a -vector space over a field . Show the following properties.

  1. The zero space is -invariant.
  2. is -invariant.
  3. Eigenspaces are -invariant.
  4. Let be -invariant linear subspaces. Then also and are -invariant.
  5. Let be a -invariant linear subspace. Then also the image space and the preimage space are -invariant.


Exercise

Let a linear mapping on a -vector space over a field , and let . Show that the smallest -invariant linear subspace of , which contains , equals


Exercise

Let a linear mapping on a -vector space over a field . Show that the subset of , defined by

is an -invariant linear subspace.


Exercise

Let be a linear mapping on a -vector space . Let be a basis of , such that is described, with respect to this basis, by an upper triangular matrix. Show that the linear subspaces

are -invariant for every .


Exercise

Determine, whether the real matrix

is trigonalizable or not.




Hand-in-exercises

Exercise (2 marks)

Compute the characteristic polynomial of the matrix


Exercise (3 marks)

Compute the characteristic polynomial, the eigenvalues and the eigenspaces of the matrix

over .


Exercise (4 marks)

Let

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


Exercise (4 marks)

Let

Compute:

  1. the eigenvalues of ;
  2. the corresponding eigenspaces;
  3. the geometric and algebraic multiplicities of each eigenvalue;
  4. a matrix such that is a diagonal matrix.


Exercise (4 marks)

Determine for every the algebraic and geometric multiplicities for the matrix


Exercise (4 marks)

Decide whether the matrix

is trigonalizable over .


Exercise (3 marks)

Determine whether the real matrix

is trigonalizable or not.




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


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