Linear algebra - subspaces

In summary, a counterexample for statement 1 is given by choosing W=Sp\{(1,0)\}, U_1= Sp\{(1,1)\}, U_2= Sp\{(3,1)\}, which also contradicts statement 2.
  • #1
estro
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Suppose V is a vector space over R and [tex]U_1, U_2, W [/tex] are subspaces of V.

Prove or contradict:

1. [tex] W \cap (U_1+U_2) = (W \cap U_1)+(W \cap U_2)[/tex]
2. [tex] If\ U_1 \oplus W = U_2 \oplus W\ then\ U_1=U_2 [/tex]

I'm not sure how to approach this problem, and will appreciate any guidance.
Thanks!

(For the first one I had an idea to use theorem which links between dimension and subspaces equivalence, but both sides of the equation are to complex)
 
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  • #2
If you want to prove two subspaces are equal to each other, it's usually done the same as any time you want to prove two sets are equal: Show that each subspace is contained inside the other. For example, if [tex]v\in W\cap(U_1 + U_2)[/tex] can you prove that [tex]v\in (W\cap U_1) + (W\cap U_2)[/tex]? That and showing the reverse would give you that 1 is true.

I'm not claiming this is true though, I haven't checked whether 1 is true. Whenever you have a problem that asks to 'prove or contradict', it's usually a good idea to try to make a couple of examples first; either you'll get a counterexample and you'll be done or you'll be able to get some intuition for why the statement is true that might help when making the general proof
 
  • #3
Office_Shredder said:
If you want to prove two subspaces are equal to each other, it's usually done the same as any time you want to prove two sets are equal: Show that each subspace is contained inside the other. For example, if [tex]v\in W\cap(U_1 + U_2)[/tex] can you prove that [tex]v\in (W\cap U_1) + (W\cap U_2)[/tex]? That and showing the reverse would give you that 1 is true.

I'm not claiming this is true though, I haven't checked whether 1 is true. Whenever you have a problem that asks to 'prove or contradict', it's usually a good idea to try to make a couple of examples first; either you'll get a counterexample and you'll be done or you'll be able to get some intuition for why the statement is true that might help when making the general proof

Thanks for the quick response!
I actually tried to show bi-directional contain, but the fact that V is not necessarily finite dimensional made me uncomfortable. Don't I have to worry about that?
 
  • #4
You should only worry about it if you're going to pick a basis, or apply a theorem that only holds for finite dimensional vector spaces (like rank nullity). You shouldn't have to do that though.

Have you tried coming up with some examples for these? For 1), just pick a vector space like R2 and a couple of one dimensional vector subspaces and see what happens
 
  • #5
I think I have contra-example for 1:

[tex] W=Sp\{(1,0),(0,1)\}\ ,U_1=Sp\{(1,0)\}\ ,U_2=Sp\{(1,1)\} [/tex]

Then: [tex] R^2=W\cap(U_1+U_2)=(W \cap U_1) + (W \cap U_2)=<not\ sure\ how\ to\ prove\ this\, for\ now\only\ based\ on\ intuition>=Sp(\{1,0\})[/tex]

What do you think?
 
  • #6
In your example [tex]W\cap U_1=U_1[/tex] and [tex]W \cap U_2=U_2[/tex] so the right hand side is also the plane. Having [tex]U_1[/tex] and [tex]U_2[/tex] span the plane is a good idea, but W needs to be refined
 
  • #7
[tex] W=Sp\{(1,0)\}, U_1= Sp\{(1,1)\}, U_2= Sp\{(3,1)\} [/tex]

Then: [tex] R^2=W\cap(U_1+U_2)=(W \cap U_1) + (W \cap U_2)=Sp(\{0,0\})=Sp\{0\}[/tex]

It seems to contradict 2 also, am I right this time? (Set operations confuse me when applied on vector spaces)
 
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  • #8
[tex]W\cap(U_1+U_2)=W[/tex], not R2, but other than that it's a good example. You can use what you have there to give a counterexample for 2, but you haven't said yet how it does so
 
  • #9
[tex]W=Sp\{(1,0)\}, U_1= Sp\{(1,1)\}, U_2= Sp\{(3,1)\}[/tex]

[tex] (*1)\ U_1+W = U_2+W [/tex]
[tex] (*2)\ U_1 \cap W= (0,0,0) [/tex] <Should I prove such things, or it's ok to leave it in this way?>
[tex] (*3)\ U_2 \cap W= (0,0,0) [/tex]

From (*1) and (*2) and (*3) [tex]U_1 \oplus W = U_2 \oplus W[/tex] is valid, but [tex] U_1 \neq U_2 [/tex]
 
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1. What is a subspace in linear algebra?

A subspace in linear algebra is a subset of a vector space that also satisfies the properties of a vector space. This means that it is closed under addition and scalar multiplication, and contains the zero vector.

2. How can I determine if a set of vectors is a subspace?

To determine if a set of vectors is a subspace, you can check if it satisfies the three properties of a vector space: closure under addition, closure under scalar multiplication, and contains the zero vector. You can also use the subspace test, which states that if all vectors in the set are linear combinations of a basis for the vector space, then it is a subspace.

3. What is the dimension of a subspace?

The dimension of a subspace is the number of basis vectors needed to span the subspace. This is also known as the number of linearly independent vectors in the subspace.

4. Can a subspace have a dimension of 0?

Yes, a subspace can have a dimension of 0. This means that the subspace only contains the zero vector.

5. How can subspaces be useful in real-world applications?

Subspaces are useful in many real-world applications, such as computer graphics, economics, and engineering. They allow for efficient representation and manipulation of data and can help solve complex problems by breaking them down into smaller, more manageable subspaces.

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