4.6 Dimension: Class Notes
Theorem 4.6.2
Let be a finite-dimensional vector space, and let be any basis for .
a) If a set in has more than vectors, then it is linearly dependent.
b) If a set in has fewer than vectors, then it does not span .
The proof of this essentially involves counting variables and equations in a linear system.
Theorem 4.6.1
All bases for a finite-dimensional vector space have the same number of vectors.
Definition
The dimension of a finite-dimensional vector space is denoted by and is defined to be the number of vectors in a basis for (in some physical contexts, “dimension” is referred to as degrees of freedom). In addition, the zero vector space is defined to have dimension zero.
Recall that the basis for the zero vector space is .
Solution Spaces of Homogeneous Systems
Find a basis for the solution space of each homogeneous linear system, and find the dimension of that space.
#1
Solution
Row reduce the coefficient matrix:
So and , with free:
Answer: The basis is , .
#5
Solution
, so with and ,
Answer: The basis is , .
#8
In each part, find a basis for the given subspace of , and state its dimension.
a. All vectors of the form .
b. All vectors of the form , where and .
c. All vectors of the form , where .
Solution
a)
Answer: ; dimension:
b)
Answer: ; dimension:
c)
Answer: ; dimension:
Theorem 4.6.4
Let be an -dimensional vector space, and let be a set in with exactly vectors. Then is a basis for if and only if spans or is linearly independent.
Tip: This proof is optional.
Proof: () If is a basis for , then spans and is linearly independent by definition.
() Suppose has exactly vectors and spans . If is not linearly independent, then (there exists) (such that) . But then can be removed without affecting , contradicting that is -dimensional. Thus, is independent.
Suppose has exactly vectors and is linearly independent. If does not span , then (there exists) (such that) . Then is independent, again contradicting that is -dimensional. Thus spans .
Theorem 4.6.5
Let be a finite set of vectors in a finite-dimensional vector space .
a) If spans but is not a basis for , then can be reduced to a basis for by removing appropriate vectors from .
b) If is a linearly independent set that is not already a basis for , then can be enlarged to a basis for by inserting appropriate vectors into .
#12
Find standard basis vectors for that can be added to the set to produce a basis for .
a. ,
b. ,
Solution
a) Put , , and the standard basis vectors in the columns of a matrix and row reduce:
and , then :
Pivot columns are , so the desired basis is
Answer:
Note: this answer is not unique. would also work.
#18
Find a basis for the subspace of that is spanned by the vectors , , , .
Solution
Put the vectors in the columns of a matrix and row reduce:
Since the pivot columns are and , the desired basis is
Answer:
Note: and . Again, the answer is not unique.
#20
In each part, let be multiplication by and find the dimension of the subspace of consisting of all vectors for which .
a. b.
Solution
Want: such that .
a)
Answer: dimension of the kernel:
b)
Answer: dimension: