Operators on Complex Vector Spaces
[75/0%]Suppose . Prove that if and , then dim for all integers .
Suppose is a positive integer, , and but . Prove that is linearly independent.
The result in this exercise is used in the proof of 8.45. Theorem 8.45 (every nilpotent operator has a Jordan basis): suppose is nilpotent. Then there is a basis of that is a Jordan basis for . Definition 8.44: a basis of is called a Jordan basis for if with respect to this basis has a block diagonal matrix with diagonal blocks , in which each is an upper-triangular matrix with in every diagonal entry, in every entry of the line directly above the diagonal, and in all other entries.
Suppose . Prove that
Suppose , and is a positive integer such that the minimal polynomial of is a polynomial multiple of . Prove that
Suppose and is a positive integer. Prove that
Suppose . Show that
Suppose and is a nonnegative integer such that
Prove that range for all .
Suppose . Prove that
Suppose and is a nonnegative integer. Prove that
Define by . Find all generalized eigenvectors of .
Suppose that . Prove that there is a basis of consisting of generalized eigenvectors of if and only if the minimal polynomial of equals for some .
Assume because the case follows from 5.27(b) and 8.9. This exercise states that the condition for there to be a basis of consisting of generalized eigenvectors of is the same as the condition for there to be a basis with respect to which has an upper-triangular matrix (see 5.44). Caution: If has an upper-triangular matrix with respect to a basis of , then is an eigenvector of but it is not necessarily true that are generalized eigenvectors of .
Theorem 5.27(b): if is a complex vector space and , then the minimal polynomial of has the form , where is a list of all eigenvalues of , possibly with repetitions.
Theorem 8.9 (a basis of generalized eigenvectors): if and , then there is a basis of consisting of generalized eigenvectors of .
Theorem 5.44 (necessary and sufficient condition to have an upper-triangular matrix): suppose is finite-dimensional and . Then has an upper-triangular matrix with respect to some basis of if and only if the minimal polynomial of equals for some .
Suppose is such that every vector in is a generalized eigenvector of . Prove that there exists such that is nilpotent.
Suppose and is nilpotent. Prove that is nilpotent.
Suppose is nilpotent and . Prove is not diagonalizable.
Suppose and . Prove that is diagonalizable if and only if every generalized eigenvector of is an eigenvector of .
For , this exercise adds another equivalence to the list of conditions for diagonalizability in 5.55. Theorem 5.55 (conditions equivalent to diagonalizability): suppose is finite-dimensional and , and let denote the distinct eigenvalues of . Then the following are equivalent: is diagonalizable; has a basis consisting of eigenvectors of ; ; .
Give an example of nilpotent operators on the same vector space such that neither nor is nilpotent.
Suppose are nilpotent and . Prove that and are nilpotent.
Suppose is nilpotent and is a positive integer such that .
Prove that is invertible and that .
Explain how you would guess the formula above.
Suppose is nilpotent. Prove that . If range , then this exercise improves 8.16.
Suppose is not nilpotent. Show that
For operators that are not nilpotent, this exercise improves 8.4.
Suppose is an inner product space and is normal and nilpotent. Prove that .
Suppose is such that . Prove that is nilpotent and that for every integer with .
Suppose is such that range . Prove that is nilpotent.
Give an example of an operator on a finite-dimensional real vector space such that 0 is the only eigenvalue of but is not nilpotent.
This exercise shows that the implication (a) in 8.17 does not hold without the hypothesis that . Theorem 8.17 (eigenvalues of nilpotent operator): suppose . Part (a): if is nilpotent, then is an eigenvalue of and has no other eigenvalues. Part (b): if and is the only eigenvalue of , then is nilpotent.
For each item in Example 8.15, find a basis of the domain vector space such that the matrix of the nilpotent operator with respect to that basis has the upper-triangular form promised by 8.18(c).
Theorem 8.18(c): there is a basis of with respect to which the matrix of has the form , where all entries on and below the diagonal equal .
Example 8.15 (nilpotent operators):
The operator defined by is nilpotent because .
The operator on whose matrix (with respect to the standard basis) is
is nilpotent, as can be shown by cubing the matrix above to get the zero matrix.
The operator of differentiation on is nilpotent because the th derivative of every polynomial of degree at most equals .
Suppose that is an inner product space and is nilpotent. Show that there is an orthonormal basis of with respect to which the matrix of has the upper-triangular form promised by 8.18(c).
Theorem 8.18(c): an operator is nilpotent if and only if there is a basis of with respect to which the matrix of has the form , where all entries on and below the diagonal equal .
Define by . Find the generalized eigenspaces corresponding to the distinct eigenvalues of .
Suppose is invertible. Prove that for every with .
Suppose . Suppose is invertible. Prove that and have the same eigenvalues with the same multiplicities.
Suppose and is such that . Prove that has at most two distinct eigenvalues.
Suppose and 3 and 8 are eigenvalues of . Let . Prove that .
Suppose and is an eigenvalue of . Explain why the exponent of in the factorization of the minimal polynomial of is the smallest positive integer such that .
Suppose and is an eigenvalue of with multiplicity . Prove that .
If , then this exercise improves 8.20. Theorem 8.20 (description of generalized eigenspaces): suppose and . Then .
Suppose and are the distinct eigenvalues of . Prove that
if and only if the minimal polynomial of equals for some positive integers .
The case follows immediately from and the generalized eigenspace decomposition (8.22); thus this exercise is interesting only when . Theorem 5.27(b): if is a finite-dimensional complex vector space and , then the minimal polynomial of has the form , where is a list of all eigenvalues of , possibly with repetitions. Theorem 8.22 (generalized eigenspace decomposition): suppose and , and let be the distinct eigenvalues of . Then is invariant under and is nilpotent for each , and .
Suppose and . Prove that there exist such that , the operator is diagonalizable, is nilpotent, and .
Suppose is a complex inner product space, is an orthonormal basis of , and . Let be the eigenvalues of , each included as many times as its multiplicity. Prove that
See the comment after Exercise 5 in Section 7A. Exercise 7A.5: suppose ; suppose is an orthonormal basis of and is an orthonormal basis of . Prove that . The comment after that exercise notes: the numbers in that equation depend on the orthonormal basis , but the right side does not depend on ; thus the equation shows that the sum on the left side does not depend on which orthonormal basis is used.
Give an example of an operator on whose characteristic polynomial equals .
Give an example of an operator on whose characteristic polynomial equals and whose minimal polynomial equals .
Give an example of an operator on whose characteristic and minimal polynomials both equal .
Give an example of an operator on whose characteristic polynomial equals and whose minimal polynomial equals .
Let be the operator on defined by . Find the characteristic polynomial and the minimal polynomial of .
Let be the operator on defined by
Find the characteristic polynomial and the minimal polynomial of .
Suppose and is such that . Prove that the characteristic polynomial of is , where and range .
Suppose and is an eigenvalue of . Explain why the following four numbers equal each other.
The exponent of in the factorization of the minimal polynomial of .
The smallest positive integer such that .
The smallest positive integer such that
The smallest positive integer such that
Suppose and is a unitary operator. Prove that the constant term in the characteristic polynomial of has absolute value 1.
Suppose that and are nonzero subspaces of such that
Suppose and each is invariant under . For each , let denote the characteristic polynomial of . Prove that the characteristic polynomial of equals .
Suppose are monic polynomials with the same zeros and is a polynomial multiple of . Prove that there exists such that the characteristic polynomial of is and the minimal polynomial of is .
This exercise implies that every monic polynomial is the characteristic polynomial of some operator.
Suppose and are block diagonal matrices of the form
where and are square matrices of the same size for each . Show that is a block diagonal matrix of the form
Suppose , and .
Show that if and only if .
Show that the multiplicity of as an eigenvalue of equals the multiplicity of as an eigenvalue of .
Use (b) and the result about the sum of the multiplicities (8.25) to show that if is an odd number, then has a real eigenvalue.
Theorem 8.25 (sum of the multiplicities equals ): suppose and . Then the sum of the multiplicities of all eigenvalues of equals .
Use (c) and the result about real eigenvalues of (Exercise 17 in Section 5A) to show that if is an odd number, then has an eigenvalue (thus giving an alternative proof of 5.34).
Exercise 17 in Section 5A (Exercise 5A.17): if , , and , then is an eigenvalue of if and only if is an eigenvalue of the complexification .
The complexification was defined in Exercise 33 in Section 3B: suppose is a real vector space and ; the complexification is defined by for all , where is the complexification of from Exercise 8 in Section 1B.
Suppose is the operator defined by . Prove that does not have a square root.
Define by .
Show that is nilpotent.
Find a square root of .
Suppose is a complex vector space. Prove that every invertible operator on has a cube root.
Suppose is a real vector space. Prove that the operator on has a square root if and only if is an even number.
Suppose is the operator defined by . Find a Jordan basis for .
Find a basis of that is a Jordan basis for the differentiation operator on defined by .
Suppose is nilpotent and is a Jordan basis for . Prove that the minimal polynomial of is , where is the length of the longest consecutive string of 1's that appears on the line directly above the diagonal in the matrix of with respect to .
Suppose and is a basis of that is a Jordan basis for . Describe the matrix of with respect to this basis.
Suppose is nilpotent. Explain why there exist and nonnegative integers such that (a) and (b) below both hold.
is a basis of .
.
Suppose and is a basis of that is a Jordan basis for . Describe the matrix of with respect to the basis obtained by reversing the order of the 's.
Suppose . Explain why every vector in each Jordan basis for is a generalized eigenvector of .
Suppose is diagonalizable. Show that is a diagonal matrix with respect to every Jordan basis for .
Suppose is nilpotent. Prove that if are vectors in and are nonnegative integers such that
and
then is a basis of . This exercise shows that . Thus the positive integer that appears above depends only on and not on the specific Jordan basis chosen for .
Suppose and . Prove that there does not exist a direct sum decomposition of into two nonzero subspaces invariant under if and only if the minimal polynomial of is of the form for some .
Suppose is an inner product space and . Define an operator by . Find a formula for .
Suppose satisfies . Prove that
Suppose and . Prove that the real and imaginary parts of are both integers.
Suppose is an inner product space and . Prove that
Suppose is an inner product space. Suppose is a positive operator and . Prove that .
Suppose is an inner product space and are orthogonal projections. Prove that .
Suppose is the operator whose matrix is
Someone tells you (accurately) that -48 and 24 are eigenvalues of . Without using a computer or writing anything down, find the third eigenvalue of .
Prove or give a counterexample: If , then .
Suppose is such that for all . Prove that .
Prove that the trace is the only linear functional such that
for all and .
Suppose and are inner product spaces and . Prove that if is an orthonormal basis of and is an orthonormal basis of , then
The numbers are the entries of the matrix of with respect to the orthonormal bases and . These numbers depend on the bases, but does not depend on a choice of bases. Thus this exercise shows that the sum of the squares of the absolute values of the matrix entries does not depend on which orthonormal bases are used.
Suppose and are finite-dimensional inner product spaces.
Prove that defines an inner product on .
Suppose is an orthonormal basis of and is an orthonormal basis of . Show that the inner product on from (a) is the same as the standard inner product on , where we identify each element of with its matrix (with respect to the bases just mentioned) and then with an element of .
Caution: The norm of a linear map as defined by 7.86 is not the same as the norm that comes from the inner product in (a) above. Unless explicitly stated otherwise, always assume that refers to the norm as defined by 7.86. The norm that comes from the inner product in (a) is called the Frobenius norm or the Hilbert-Schmidt norm.
Definition 7.86 (norm of a linear map, ): suppose . Then the norm of , denoted by , is defined by .
Find such that .