Exploring Vector Spaces U, V, and W: Solving U⊕V = U⊕W for U, V, and W

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In summary, U⊕V is the same as U⊕W because U⊕W is the set of all vectors of the form <x, 0> for any real number x.
  • #1
srn
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U⊕V = U⊕W; find U, V and W

I need to give an example of different vectorspaces U, V, W so that [itex]U \oplus V = U \oplus W[/itex].

Can anyone give a hint please? It's basically asking for V and W such that [itex]u_i + v_i = u_i + w_i[/itex] yet V and W have to be different. How?
 
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  • #2
You are working with tensor products right?? You didn't mean to type [itex]\oplus[/itex] for direct sum??
 
  • #3
srn said:
I need to give an example of different vectorspaces U, V, W so that U⊗V = U⊗W.

Can anyone give a hint please? It's basically asking for V and W such that [itex]u_i + v_i = u_i + w_i[/itex] yet V and W have to be different. How?

Hi srn! :smile:

So... U, V and W have to be different, such as U=<(1,0)>, V = <(1,1)> and W=<(0,1)>?
 
  • #4
Thanks for the replies. And sorry, clearly posted this too late because I messed up the symbol in the question. :( Meant to say direct sum indeed...

I like Serena said:
Hi srn! :smile:

So... U, V and W have to be different, such as U=<(1,0)>, V = <(1,1)> and W=<(0,1)>?
Hey. :) Yes they do. But here the direct sums are not equal though, right? I guess you meant the tensor product? Sorry :(
 
  • #5
srn said:
Hey. :) Yes they do. But here the direct sums are not equal though, right? I guess you meant the tensor product? Sorry :(

Are you sure they are not equal (when taking the direct sum)??
What are the direct sums??
 
  • #6
If [itex](R,S, +)[/itex] is a vectorspace with [itex]U, W[/itex] as subspaces, then [itex]U \oplus W = \{u + w | u \in U, w \in W\}[/itex] and every [itex]s \in S[/itex] can only be written in one possible way (as the sum of vectors of U and W). I.e. it's every possible combination of elements in [itex](R, U, +)[/itex] and [itex](R, W, +)[/itex].

Suppose U=<(1,0)>, V = <(1,1)> and W=<(0,1)> are subspaces, then

[itex]U \oplus W = R^2[/itex]. But how is [itex]U \oplus V = R^2[/itex]? I'm imagining [itex]R^2[/itex]. V is every possible vector through [itex]\stackrel{\rightarrow}{o}[/itex] with [itex]arg(v) = 1[/itex]. Then [itex]U \oplus V[/itex] would be the area under y = x for [itex]x > 0, y > 0[/itex]. How can you form (0,1) for example?

edit: come to think of it, would [itex](R, V, +)[/itex] also contain (0,1) and (1,2) etc? I sort of assumed from "[itex]\forall v \in V[/itex] and [itex]\forall r \in R: rv \in V[/itex]" that [itex](R, V, +)[/itex] would only contain (1,1), (2,2) etc, is that incorrect?

I'm sort of confused because my book says that if [itex]U \cap V \neq (0,0)[/itex] then [itex]U \oplus V[/itex] cannot exist. From the example, [itex]U \cap V[/itex] would be [itex]\{((x,0) | x \in R\}[/itex], but then (1,0) would be both in U and V?
 
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  • #7
If V = <(1,1)> then how can (1,0) be in V? There is no scalar a such that a*(1,1) = (1,0). Similarly, there is no scalar b such that b*(1,0) = (1,1). So the intersection of U and V is indeed (0,0).
 
  • #8
Uh, right. So the intersection is (0,0) but [itex]U + V \neq R^2[/itex]. There's no scalars so that [itex]a\cdot (1,0) + b\cdot (1,1) = (0,1)[/itex], for example. So U and V cannot form [itex]R^2[/itex] and the direct sums are hence not equal? edit: ooops, a = -1 and b = 1 :) so they do actually form R^2

Sidenote:

If U=<(1,0) then V=<(0,1)> and W=<(0,-1)> would form the same direct sum space, and that also answers the question I think? edit: eh, no, (R, V, +) is equal to (R, W, +) now.
 
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  • #9
Let U be the subspace of R2 spanned by <1, 0>. That is U is the set of all vectors of the form <x, 0> for any real number x. Let V be the vector space spanned by <0, 1> and let W be the subspace spanned by <1, 1>.

You can then show that U⊕V= U⊕W.
 

1. What does U⊗V = U⊗W mean?

The notation U⊗V = U⊗W in linear algebra means that the tensor product of U and V is equal to the tensor product of U and W. This means that the two expressions are equivalent and can be used interchangeably.

2. How do you find U, V, and W in U⊗V = U⊗W?

To find U, V, and W in the equation U⊗V = U⊗W, you can solve for each variable by dividing both sides of the equation by the remaining variables. For example, if you know U and V, you can find W by dividing both sides by U⊗V.

3. What is a tensor product?

A tensor product is a mathematical operation that combines two vector spaces to create a new vector space. It is often used in linear algebra to represent the relationship between two vector spaces.

4. How is the tensor product related to other linear algebra operations?

The tensor product is related to other linear algebra operations such as the direct sum and direct product. It can also be used to define the outer product and inner product of two vectors.

5. Can U, V, and W be any type of vector space in U⊗V = U⊗W?

Yes, U, V, and W can be any type of vector space in U⊗V = U⊗W. The tensor product operation is defined for any vector spaces, including finite-dimensional, infinite-dimensional, and even abstract vector spaces. However, the properties and behaviors of the tensor product may vary depending on the type of vector spaces used.

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