Isomorphisms preserve linear independence

In other words, if ##T## is injective, then ##\{v_1, ..., v_k\}## being linearly independent implies ##\{T(v_1), ... , T(v_2)\}## is linearly independent.
  • #1
GlassBones
16
1

Homework Statement



Let ##T:V \rightarrow W## be an ismorphism. Let ##\{v_1, ..., v_k\}## be a subset of V. Prove that ##\{v_1, ..., v_k\}## is a linearly independent set if and only if ##\{T(v_1), ... , T(v_2)\}## is a linearly independent set.

Homework Equations

The Attempt at a Solution


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##\rightarrow##: I began with the definition of linear independent vectors.
But I realized this could map to vectors that become dependent vectors in ##W##.

I suppose the fact that T is an isomorphism is a hint. Can anyone give me ideas?
 
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  • #2
GlassBones said:
I suppose the fact that T is an isomorphism is a hint.
It is not a hint, it is a requirement and part of the question. In order to show that A holds iff B is true, then clearly the properties of B must somehow come into play.

So what are the properties of isomorphisms between vector spaces?
 
  • #3
GlassBones said:
I suppose the fact that T is an isomorphism is a hint. Can anyone give me ideas?
A hint would be that injectivity is sufficient.
 

1. What is an isomorphism?

An isomorphism is a mathematical concept that describes a one-to-one correspondence between two objects or structures. In linear algebra, an isomorphism is a linear transformation that preserves the structure and properties of vector spaces.

2. How do isomorphisms preserve linear independence?

Isomorphisms preserve linear independence by preserving the relationships between vectors in a vector space. This means that if a set of vectors is linearly independent in one vector space, the corresponding set of vectors in the other vector space will also be linearly independent.

3. Can an isomorphism change the dimension of a vector space?

No, an isomorphism cannot change the dimension of a vector space. It preserves the dimension of the vector space, meaning that if the original vector space has a certain dimension, the transformed vector space will have the same dimension.

4. How do you prove that an isomorphism preserves linear independence?

To prove that an isomorphism preserves linear independence, you can use the definition of an isomorphism and show that the transformation preserves the relationships between the vectors in the two vector spaces. This can be done by showing that if a set of vectors is linearly independent in one vector space, the corresponding set of vectors in the other vector space is also linearly independent.

5. Are all isomorphisms also linear transformations?

Yes, all isomorphisms are also linear transformations. This is because isomorphisms preserve the structure and properties of vector spaces, and linear transformations are defined as functions that preserve vector addition and scalar multiplication.

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