Equivalent sets in different vector spaces?

In summary: Algebra, then adding a vector with a multiplier would be adding a binary operation to an unary one, which would not be a valid operation in that algebra. Just to add to that I am only considering linear transformations. The one you were pointing to isn't a linear transformation. But does that make a nonlinear transformation? In what space could it occur?Yes, this is a linear transformation. It occurs in the space of real numbers.
  • #1
pivoxa15
2,255
1
{1, x, 2x^2} is a basis for V (the polynomial vector space with maximum power 2)

then could I say that the coordinate vectors with respect to V, which form the set {(1,0,0), (0,1,0), (0,0,2)} for R^3 is equivalent to the above set in V?

Although the word equivalent is not defined. But it is true that any property one set has automatically implies to the other set? If yes then it seems it is much easier to work with the set in R^3.
 
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  • #2
what are you trying to understand?
 
  • #3
You can formally identify V and any copy of R^3 by, or any 3d vector space over the same field, by identifying basis vectors, though I don't see why you'd want to do it in this case. They are after all just vector spaces and the only invariants ofa vector space are the underlying basefield and the dimension: i.e. given any two vector spaces of the same dimension over F they are (non-canonically) isomorphic.
 
  • #4
Of course, R3 and V are isomorphic.

I think what you are saying is that the function [itex]f:V \rightarrow R^3[/itex] defined by f(a+ bx+ cx2)= a(1, 0, 0)+ b(0, 1, 0)+ (c/2)(0, 0, 2) is an isomorphism. But then if two vector spaces are isomorphic then must have the same dimension. And then any function which maps a basis of one bijectively to a basis of the other is an isomorphism.
 
  • #5
pivoxa15 said:
Although the word equivalent is not defined. But it is true that any property one set has automatically implies to the other set? If yes then it seems it is much easier to work with the set in R^3.

What you mean by "equivalent" is what they've called "isomorphic".

They will share all the properties that follow from their usual vector space qualities.

It's not really much easier to work with R^3 than the polynomials, a little less to write I suppose.
 
  • #6
isomorphic is what I was looking for in equivalence. So properties in one set implies the other. That is what I needed to know.
 
  • #7
But note that the term "isomorphic" refers to the entire space, not just the two bases.
 
  • #8
pivoxa15 said:
{1, x, 2x^2} is a basis for V (the polynomial vector space with maximum power 2)

then could I say that the coordinate vectors with respect to V, which form the set {(1,0,0), (0,1,0), (0,0,2)} for R^3 is equivalent to the above set in V?

Although the word equivalent is not defined. But it is true that any property one set has automatically implies to the other set? If yes then it seems it is much easier to work with the set in R^3.

Although it is true that the two spaces are isomorphic under linear operations( addition, multiplication by scalars), they will not be isomorphic under more complicated operations. They certianly won't be isomorphic if you throw multiplication into the mix. x * x^2 = x^3 is not an element of the original space. If you like, that space is not closed under multiplication. As you can guess, there is no corressponding operation in R^3 that is going to do this; at least, not a nice neat one.

If all you're doing is adding, and multiplying by scalars, then yes, use the R^3 representation. This is what you will eventually have to do anyway if you were to say, represent this on a computer.
 
  • #9
ObsessiveMathsFreak said:
Although it is true that the two spaces are isomorphic under linear operations( addition, multiplication by scalars), they will not be isomorphic under more complicated operations. They certianly won't be isomorphic if you throw multiplication into the mix. x * x^2 = x^3 is not an element of the original space. If you like, that space is not closed under multiplication. As you can guess, there is no corressponding operation in R^3 that is going to do this; at least, not a nice neat one.

If all you're doing is adding, and multiplying by scalars, then yes, use the R^3 representation. This is what you will eventually have to do anyway if you were to say, represent this on a computer.

The question was about vector spaces. The only operations defined for a vector space are addition and scalar multiplication.
 
  • #10
HallsofIvy said:
The question was about vector spaces. The only operations defined for a vector space are addition and scalar multiplication.

Just to add to that I am only considering linear transformations. The one you were pointing to isn't a linear transformation. But does that make a nonlinear transformation? In what space could it occur?
 
  • #11
My point was that allowing multiplication of vectors in the way ObsessiveMathFreak was talking about gives an "Algebra", not a "Vector Space" which is what we were discussing. Multiplication is a "binary" operation (a*b requires a and b) while a "transformation" is "unary": a single vector is mapped into another. If you were working in an algebra in which multiplication of vectors was defined the such transformations as
A(v)= u*v (for fixed v) would be linear but B(v)= v*v would not.
 

Related to Equivalent sets in different vector spaces?

1. What are equivalent sets in different vector spaces?

Equivalent sets in different vector spaces refer to sets of vectors that have the same span or linear independence, but exist in different vector spaces.

2. How do you determine if two sets are equivalent in different vector spaces?

To determine if two sets are equivalent in different vector spaces, you can check if the vectors in one set can be linearly expressed in terms of the vectors in the other set, or if the span of both sets is the same.

3. Can equivalent sets in different vector spaces have different dimensions?

Yes, equivalent sets in different vector spaces can have different dimensions. This is because the dimension of a vector space is determined by the number of linearly independent vectors, which can be different even if the span is the same.

4. How are equivalent sets in different vector spaces useful in linear algebra?

Equivalent sets in different vector spaces are useful in linear algebra as they allow for the comparison and connection of different vector spaces. They also help in understanding the structure and properties of vector spaces.

5. Can equivalent sets in different vector spaces have different bases?

Yes, equivalent sets in different vector spaces can have different bases. This is because a basis of a vector space is not unique, and different bases can span the same vector space.

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