Bases of linearly isomorphic vector spaces

In summary: Since \{Tv_1,\dots,Tv_n\} is linearly dependent, \alpha_{1}T(v_{1})+...+\alpha_{n}T(v_{n})=0 for some nonzero \alpha_{i}. Then there exists a j\in\mathbb{N}, 1\leq j\leq n such that \alpha_{1}T(v_{j}) =-(\alpha_{1}T(v_{1}) +...+\alpha_{j-1}T(v_{j-1})) . Is this on the right track?That could work, but I haven
  • #1
autre
117
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Finite-dimensional [itex]V[/itex] and [itex]W[/itex] are linearly isomorphic vector spaces over a field. Prove that if [itex]\{v_{1},...,v_{n}\}[/itex] is a basis for [itex]V[/itex], [itex]\{T(v_{1}),...,T(v_{n})\}[/itex] is a basis for [itex]W[/itex].

My attempt at a proof:

Let [itex]T:V\rightarrow W[/itex] be an isomorphism and [itex]\{v_{1},...,v_{n}\}[/itex] be a basis for [itex]V[/itex]. Since [itex]T[/itex] is an isomorphism, [itex]\forall v\in V,\exists T(v)\in W[/itex]. Therefore, if [itex]\{v_{1},...,v_{n}\}[/itex] spans [itex]V[/itex], [itex]\{T(v_{1}),...,T(v_{n})\}[/itex] spans [itex]W[/itex]. Since [itex]dim V=dimW[/itex], [itex]\{v_{1},...,v_{n}\}[/itex] is linearly independent, and is a basis for [itex]W[/itex].

I'm pretty sure I went wrong somewhere/claimed something I needed to prove. Any ideas where?
 
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  • #2
autre said:
Therefore, if [itex]\{v_{1},...,v_{n}\}[/itex] spans [itex]V[/itex], [itex]\{T(v_{1}),...,T(v_{n})\}[/itex] spans [itex]W[/itex].

You just state this, but you never really proved it. In fact, you never used that T is an isomorphism... that given [itex]v\in V[/itex] there exists [itex]T(v)\in W[/itex] is merely a consequence of T being a function. Given [itex]w\in W[/itex], how can you go about determining the coefficients of w in terms of the T(vi)?
 
  • #3
Do I use the fact that any [itex]w\in W [/itex] can be written as [itex]w=a_{1}T(v_{1})+...+a_{n}T(v_{n}) [/itex] or does that only follow after I show something else?
 
  • #4
autre said:
Do I use the fact that any [itex]w\in W [/itex] can be written as [itex]w=a_{1}T(v_{1})+...+a_{n}T(v_{n}) [/itex]
That's part of what you're trying to prove.

I think you should start by writing down the definition of "basis" that you want to use.
 
  • #5
I think you should start by writing down the definition of "basis" that you want to use.

A basis is a linearly independent spanning set. So [itex]\{v_{1},...,v_{n}\}[/itex] spans [itex]V[/itex] and is linearly independent. Does that imply that the set of all [itex]T(v)[/itex] is linearly independent since T is an isomorphism?
 
  • #6
autre said:
A basis is a linearly independent spanning set.
Good definition.

autre said:
So [itex]\{v_{1},...,v_{n}\}[/itex] spans [itex]V[/itex] and is linearly independent. Does that imply that the set of all [itex]T(v)[/itex] is linearly independent since T is an isomorphism?
It does, but the question is how. You need to verify that [itex]\{Tv_1,\dots,Tv_n\}[/itex] is a linearly independent set. Can you use the definition of linearly independent (and isomorphism) to do that?
 
  • #7
Can you use the definition of linearly independent (and isomorphism) to do that?

Since [itex]T[/itex] is an isomorphism, [itex]\forall v\in V[/itex] there exists only one [itex]T(v)\in W[/itex] such that [itex]v=T(v)[/itex]. Since [itex]\{v_{1},...,v_{n}\}[/itex] is linearly independent, [itex]\alpha_{1}v_{1}+...+\alpha_{n}v_{n}=0 [/itex] iff [itex]\forall i,\alpha_{i}=0[/itex]. Thus [itex]T(\alpha_{1}v_{1}+...+\alpha_{n}v_{n})=T(0)[/itex] and [itex]\{T(v_{1}),...,T(v_{n})\}[/itex] is linearly independent ...am I on the right track?
 
  • #8
autre said:
Since [itex]T[/itex] is an isomorphism, [itex]\forall v\in V[/itex] there exists only one [itex]T(v)\in W[/itex] such that [itex]v=T(v)[/itex].
This doesn't quite make sense, but you probably meant something different from what you said. Note that v and Tv aren't even members of the same space. If you meant that for all [itex]v\in V[/itex], there's a unique [itex]w\in W[/itex] such that [itex]Tv=w[/itex], then this is just what it means for T to be a function from V into W.

autre said:
Since [itex]\{v_{1},...,v_{n}\}[/itex] is linearly independent, [itex]\alpha_{1}v_{1}+...+\alpha_{n}v_{n}=0 [/itex] iff [itex]\forall i,\alpha_{i}=0[/itex].
This is correct, but I want your first step to be to apply the definition of "linearly independent" directly to [itex]\{Tv_1,\dots,Tv_n\}[/itex] to see if the definition is satisfied.

autre said:
Thus [itex]T(\alpha_{1}v_{1}+...+\alpha_{n}v_{n})=T(0)[/itex]
You can't say something like that when you haven't even specified what the v's and a's are. It looks like you have assumed that they are such that [itex]a_1v_1+\cdots+a_nv_n=0[/itex]. So you appear to be trying to prove that [itex]\{T(v_{1}),...,T(v_{n})\}[/itex] is linearly independent by having T act only on 0. This can't work.
 
  • #9
This is correct, but I want your first step to be to apply the definition of "linearly independent" directly to {Tv1,…,Tvn} to see if the definition is satisfied.

Suppose it is linearly dependent. Then, [itex]\alpha_{1}T(v_{1})+...+\alpha_{n}T(v_{n})=0 [/itex] for some nonzero [itex]\alpha_{i}[/itex]. Then there exists a [itex]j\in\mathbb{N}, 1\leq j\leq n [/itex] such that [itex]\alpha_{1}T(v_{j}) =-(\alpha_{1}T(v_{1}) +...+\alpha_{j-1}T(v_{j-1})) [/itex]. Is this on the right track?
 
  • #10
That could work, but I haven't tried to do it that way. This is what I had in mind: Prove that for all [itex]a_1,\dots,a_n\in\mathbb R[/itex] such that [itex]\sum_i a_iTv_i=0[/itex], we have [itex]a_1=a_2=\cdots=a_n=0[/itex]. (Replace ℝ with ℂ if it's a vector space over ℂ).
 
  • #11
Any idea on how to set that up? I tried to show it by contradiction.
 
  • #12
Just start like this: Let [itex]a_1,\dots,a_n[/itex] be arbitrary real numbers such that [itex]\sum_i a_i Tv_i=0[/itex]. We have [tex]0=\sum_i a_i Tv_i=\cdots[/tex] Now think of something to replace the dots with, and figure out what this means.
 
  • #13
it's often easier to prove linear independence rather than "not linear dependence".

make a linear combination of the T(vj) and set it = 0.

T is linear. use this fact to get T "of something".

then use the fact that T is an isomorphism, and thus 1-1,

to show what the "something" must be.

THEN...you should have a statement involving only the vj, and these are linearly independent, so...this should say something about a certain linear combination of them, which will maybe, just maybe, tell us something about the T(vj).
 

Related to Bases of linearly isomorphic vector spaces

1. What is a linearly isomorphic vector space?

A linearly isomorphic vector space is a mathematical structure that consists of a set of vectors and a set of scalars, along with operations of vector addition and scalar multiplication. This structure allows for the representation of mathematical concepts and relationships in a geometric way.

2. How are bases of linearly isomorphic vector spaces defined?

Bases of linearly isomorphic vector spaces are defined as a set of linearly independent vectors that span the entire vector space. This means that any vector in the space can be expressed as a linear combination of the basis vectors, and that the basis vectors do not have any redundant or unnecessary components.

3. Why are bases important in linear algebra?

Bases are important in linear algebra because they provide a way to represent and manipulate vectors in a systematic and efficient manner. They also allow for the definition of linear transformations, which are fundamental operations in linear algebra.

4. Can a linearly isomorphic vector space have more than one basis?

Yes, a linearly isomorphic vector space can have more than one basis. This is because there can be multiple sets of linearly independent vectors that span the same space. However, all bases for a given vector space will have the same number of vectors, known as the dimension of the vector space.

5. How are bases of linearly isomorphic vector spaces related to change of basis?

Change of basis is a process used to transform a set of vectors from one basis to another. This is important in linear algebra because it allows for the representation of vectors and linear transformations in different bases, which can make certain calculations and concepts easier to understand and work with.

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