Linear Algebra Done Right: Proofs
Proofs for the exercises in Sheldon Axler’s Linear Algebra Done Right, 4th edition. All of the proofs are checked by Claude Opus 5.5.
Vector spaces
1C Subspaces
Exercise 1C.1(b)
Proof. Zero vector.
, thus is not in the given set, hence it is not a subspace of .
Exercise 1C.1(c)
Needs revising
Proof. Additive identity.
. Substituting the corresponding coordinates ; thus the given set includes the additive identity.
Closure under addition.
Let’s take and so that . Since but , it does not satisfy the closure under addition. Thus it is not a subspace of .
Exercise 1C.1(d)
Exercise 1C.2(b)
Exercise 1C.3
Proof. Let . .
Additive identity: let denote the zero function; it is differentiable, since . It is also in the , since .
Closed under addition. , for at least the zero function is in it. Let . Let . , since the derivative of the sums of two differentiable functions equal to the sum of their derivatives. ; thus .
Closed under scalar multiplication. Let and . . Let . Then . ; thus .
Hence is a subspace of .
Exercise 1C.23
Needs revising
Finite-dimensional vector spaces
2A Span and linear independence
Exercise 2A.2
Proof. .
Let . Then there exist , where . Define , , , and . Then
so . Hence . Conversely, because and is closed under scalar multiplication and vector addition. Thus .
Exercise 2A.4(a)
Proof. Suppose is linearly independent, and suppose . Then . Taking gives a nonzero scalar with , contradicting the linear independence of . Therefore .
Conversely, suppose , and suppose . Then there exists , such that . Multiplying both sides of by , , hence contradicting . Therefore if and .
Thus is linearly independent if and only if the .
Exercise 2A.4(b)
Proof. Let .
Suppose there exists , such that . Take and . Then . Since , is dependent. Symmetrically, the same is for . Thus if either of the two vectors , is a scalar multiple of the other, then is dependent.
Suppose is dependent. Then there exist , not both , such that . Suppose . Then there exist . Multiplying both sides of by gives us ; hence . Symmetrically, for , .
Exercise 2A.6
Needs revising
Proof. Let , , and .
Suppose the list is linearly dependent. Then there exist , not all , such that . Suppose . Then . Solving the linear system of equations: . , hence contradicting the linear dependence. Hence . Solving the linear system of the first two equations in terms of for , we have and . Substituting both in the third equation, . , so there exists . Multiplying both sides of the equation: . Hence .
Suppose . Take , , and . Then . Hence there exist , not all , such that . Therefore the list is linearly dependent.
Thus the list is linearly dependent if and only if .
Exercise 2A.7(a)
Exercise 2A.7(b)
Exercise 2A.10
Needs revising
Exercise 2A.11
Exercise 2A.13
Proof. Suppose is linearly independent, and suppose for contradiction that . Then for some . Then , contradicting the linear independence of .
Suppose , and suppose for contradiction that is linearly dependent. Then there exist , not all , such that . Suppose . Multiplying both sides by gives . Then , contradicting . Suppose . Then there exist , not all , such that , thus contradicting the linear independence of .
Therefore is linearly independent .
2B Bases
Exercise 2B.3(a)
Exercise 2B.3(b)
Proof. , so is independent in . By 2.32 we can extend to a basis of . Take and where . Suppose there exist such that . The equation forces . Therefore is independent. Let . Then
Therefore spans . Thus is a basis of .
Exercise 2B.3(c)
Needs revising
Proof. Let . Suppose . The list spans , so there exist such that . We have , where and . Thus , hence .
Suppose . Then there exists . Thus . Because is linearly independent, . Thus , hence .
Therefore .
Exercise 2B.4(a)
Proof. Let . Then and , so . Splitting that vector into a sum, we have .
Let , , and .
, because and ; and ; and . Hence . is a linear combination of , hence . Thus .
Suppose there exist such that . Then . The first, fourth, and fifth coordinates give , , and . Hence , therefore is linearly independent.
Exercise 2B.4(b)
Proof. Take and where .
Suppose there exist such that . The first, fourth, and fifth coordinates force , , and . Substituting corresponding values to other coordinates, , ; hence . Therefore is linearly independent.
, so , because span is a subspace, so it is closed under linear combination. Suppose . Take , , , , and . Then
So . Hence .
Exercise 2B.4(c)
Proof. Let and . The list spans , so there exist such that where and . , hence . Conversely, and are subspaces of , so .
Suppose . Then there exist such that . Hence . Since is linearly independent, so . Hence , thus .
Thus .
2C Dimension
Exercise 2C.1
Show that the subspaces of are precisely , all lines in containing the origin, and .
Proof. is a subspace of : ; ; for every . Let be a line in containing the origin. Then for some nonzero . Then is a subspace of : take , so ; let , so since ; let , so , where , by the compatibility of scalar multiplication with field multiplication, hence closed under scalar multiplication. is a subspace of itself, as expected.
Let be a subspace of .
Case 1. If , done.
Case 2. Suppose . contains some nonzero , and so it contains the line . Case 2.1. is exactly that line, done. Case 2.2. Otherwise, contains some nonzero that is not a multiple of , i.e., for all (and vice versa).
Since is a subspace of : for any , by closure under scalar multiplication; by closure under vector addition. Let’s define , so .
Let’s define . Suppose . Then . Suppose , so . Take . Then both and hold. Hence , contradicting the assumption that is not a multiple of . Suppose . Then , because is a nonzero vector, so . Take . Then both and hold. Hence , contradicting the assumption that is not a multiple of . Thus .
Let . Then we have a linear system of equations comprising and . Solving the system we have and . (), so there exist such that . So and was arbitrary, hence , and because , so . , since is a subset of , and , thus .
Exercise 2C.2
Show that the subspaces of are precisely , all lines in containing the origin, all planes in containing the origin, and .
Proof. is a subspace of : ; ; let , so .
We define a line in containing the origin as for some nonzero . Then is a subspace of : take , so ; let , so where ; let , so where .
We define a plane in containing the origin as for some vectors where neither of them is a multiple of the other. Then is a subspace of : take , so ; let and , so where ; let , so where .
is a subspace of : ; let , so ; let and , so .
Let be a subspace of . A subspace of a finite-dimensional is finite-dimensional with , hence .
Case 1. Suppose . Then by definition has a basis of length , hence . By definition of a span of an empty list, .
Case 2. Suppose . Then by definition has a basis of length , hence where is linearly independent, so is some nonzero vector (otherwise it is linearly dependent). By definition of a span, , i.e., a line containing the origin.
Case 3. Suppose . Then by definition has a basis of length , hence where is linearly independent. Suppose for some . Then , contradicting the linear independence of (coefficient of is ). Symmetrically, suppose . Then , again, contradicting the linear independence of (coefficient of is ). So are vectors where neither is a multiple of the other. Then by definition of a span, , i.e., a plane containing the origin.
Case 4. Suppose . . We have , so by 2.39 (subspace of full dimension equals the whole space) .
Exercise 2C.3
(a) Let . Find a basis of .
(b) Extend the basis in (a) to a basis of .
(c) Find a subspace of such that .
Proof. (a) because is finite-dimensional and is a subspace of (by 2.37). Take such that . Then since . So , because implies (by 2.39) which is not the case. Take polynomials , , , and where each one is in (; ; ; ). Suppose and We can see that the left side has a term. Because the right side has no term, this implies that . Because , we see that the left side has a term, which implies that . Because , we can conclude that . Because , we can also conclude that . Hence the list is a linearly independent list in . Thus , so .
Thus the linearly independent list has length , hence is a basis of (by 2.38).
Proof. (c) Suppose is a subspace of such that . Then . Since (by 2.43), we can conclude that , because , (from (a)), and .
Let .
Suppose . Since and is a basis of , there exist such that . Since and is a basis of , there exists such that . Then , so . Since is linearly independent, . Hence , thus . , because is in every subspace. Therefore .
(by 2.43). Since , we can conclude that , because a subspace of full dimension equals the whole space (by 2.39).
Since and , we have .
Exercise 2C.13
Suppose and are both five-dimensional subspaces of . Prove that .
Proof. We are given . Since is a subspace of (by 1.40), (by 2.37). By 2.43,
Suppose . Then and so , which contradicts . Therefore .
Exercise 2C.15
Suppose is finite-dimensional and are subspaces of with . Prove that .
Proof. For any two subspaces and of , the following holds by 2.43: . Then . A subspace of is not greater than (by 2.37), so , where is a subspace of . So the following inequality holds: . Then and so we have the following:
, where . Hence , thus . Therefore, .
Linear maps
3A Vector space of linear maps
Exercise 3A.3
Needs revising
Suppose that . Show that there exist scalars for and such tha
for every .
Proof. Suppose that . Let . We can rewrite as a linear combination using the standard basis of . Let such vectors where has a 1 in k-th slot and 0 everywhere else. Then . By additivity and homogeneity of linear maps, . Because , it has coordinates where each is in . Let’s denote each k-th m-dimensional vector’s j-th coordinate using . Then
Thus there exist scalars for and such that
Since was arbitrary, it is true for every .
Exercise 3A.7
Show that every linear map from a one-dimensional vector space to itself is multiplication by some scalar. More precisely, prove that if and , then there exist such that for all .
Exercise 3A.11
Suppose is finite-dimensional and . Prove that is a scalar multiple of the identity if and only if for every .
Proof. .
Suppose there exists such that . Let and . Then
Since was arbitrary, ; since was arbitrary, this holds for every .
Suppose for every . If , then for any scalar . Otherwise, fix a nonzero . We can extend the list to a basis of ; let be such vectors, so is a basis of . Define . Linear map lemma ensures its linearity. Write in the basis: for some scalars . Then . , so . Since depends on , let . Let be nonzero. Then there exists scalar such that . Since was an arbitrary nonzero vector, every nonzero satisfies for some scalar .
Suppose the list is linearly independent. If , then , contradicting linear independence, so . Since , there exists a scalar such that . Hence, by additivity in linear maps, , thus . Then by linear independence. Thus .
Suppose the list is linearly dependent. Then there exist scalars , not all , such that . Suppose . Then , so , i.e., is a scalar multiple of , so . Suppose : then , contradicting , so . Then . Hence and , so . Then . Since , . Since , , so . Symmetrically, suppose . Then with . Then , so and . Hence with and , thus , so .
Choose a nonzero and fix . Then for any nonzero , the previous cases give , so ; . Hence for every , so .
Therefore, is a scalar multiple of the identity if and only if for every .
Exercise 3A.13
Needs revising
Suppose is finite-dimensional. Prove that every linear map on a subspace of can be extended to a linear map on . In other words, show that if is a subspace of and , then there exists such that for all .
Proof. Let and . Let be a basis . Let for each .
We can extend the list to a basis of . Let the list be such a basis.
Let be arbitrary. By linear map lemma, there exists a linear map such that for each and for each . By additivity and homogeneity,
where .
Let be arbitrary. Then there exists such that . by additivity and homogeneity in . We can rewrite . Then .
Hence . Since was arbitrary, for all .
Exercise 3A.15
Suppose is a linearly dependent list of vectors in . Suppose also that . Prove that there exist such that no satisfies for each .
Proof. Since is linearly dependent, there exist , not all , such that . Fix with . Because , choose a nonzero , and define and for .
Suppose there exists linear map that satisfies for each . Then applying to both sides of the equation , we have . By linearity, . Then . Since , multiplying by gives , a contradiction. Therefore no such exists.
Exercise 3A.16
Suppose is finite-dimensional with . Prove that there exist such that .
Proof. Define . Since , . Let be a basis of .
Choose and , where, by linear independence, both vectors are nonzero and is not multiple of (and vice versa). Hence .
Take such that and such that for all . Suppose . and , so , a contradiction. Hence .