Dimensions of Intersection of Matrices S and T

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Homework Help Overview

The discussion revolves around the dimensions of the intersection of two matrices, S and T, within the context of linear algebra and vector spaces. Participants explore the concept of intersection in relation to the dimensions of these matrices and their respective spans.

Discussion Character

  • Conceptual clarification, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the dimensions of matrices S and T, questioning the meaning of intersection and common elements. There are attempts to clarify whether the intersection refers to rows or columns and how to express the dimensions of the intersection.

Discussion Status

The discussion is active, with various interpretations being explored regarding the dimensions of the intersection. Some participants suggest that the intersection dimension is one, while others reference a formula relating the dimensions of the sum and intersection of vector spaces, leading to confusion about the correct dimension.

Contextual Notes

There are indications of confusion regarding basic set terminology and the definitions of vector spaces. Participants also express uncertainty about how to justify their answers and the implications of the dimensions of the intersection.

pyroknife
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I've attached the problem.

For S:
I form the matrix:
1 0
0 1
0 0
0 0

Thus the dimension is 2.

For T:
I form the matrix
0 0
1 0
0 1
0 0
Thus the dimension is also 2.

Is that the correct idea?



Also what does S ∩ T mean? I couldn't find the symbol in my textbook.
 

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Yes, the dimension for those matrices are 2, when talking about dimension we either talk about row or column dimension.
the S ∩ T means all the elements that are common in S and T.
 
What does common mean? A column that is included in both matrices?
 
Well in this case it would be the rows that both S and T have common elements in.
Hint: look past the parameters s,t
 
Hmmm I don't understand why in this case it would be rows?

The only row in common is the last row (0 0).
 
pyroknife said:
Hmmm I don't understand why in this case it would be rows?

The only row in common is the last row (0 0).

Sorry I misread your problem, since there are no common elements in each vector, there is no dimension for the intersection of S and T because they have no common elements
 
First "\cap" is the standard symbol for the "intersection" of two sets- it is the set contain all things that are in both sets. I am surprised that you are working with vector spaces but have not yet learned basic set terminology.

Second, this problem does NOT ask you to find the "intersection" of two vectors- vectors are not sets. It asks you to find the subspaces spanned by the two vectors. Any vector in S is of the form <a, 0, 0, 0> so this is a one dimensional space. In particular, it has second, third and fourth components 0. Any vector in T is of the form <0, b, 0, 0>. In particular, it has first, third and fourth components 0. Any vector in their intersection must be in both and so must sastisfy both conditions. The only vector that does that is <0, 0, 0, 0>, the zero vector. That is a subspace of dimension 0.
 
Aren't vectors in S of the form <s 0 0 0>and <0 t 0 0>
and vectors in T of the form <0 s 0 0> and <0 0 t 0>?
 
Yes, S is spanned by <1, 0, 0, 0> and <0, 1, 0, 0> and T is spanned by <0, 1, 0, 0> and <0, 0, 1, 0>. And since those are independent, they are bases for the subspaces so each has dimension 2.

The fact that <0, 1, 0, 0> is in both of those should make this problem of the intersection easy!
 
  • #10
Oh so the dimension of S∩T is just 1.
 
  • #11
For this case, when you say that the dimension of S∩T is one, would it be necessary to list the vector 0 1 0 0 as the one that exists in both? I guess I'm not sure how to to state it. I can obviously just say dim(S∩T)=1, but do I need to explain it in words or justify it?
 
  • #12
Typically, with a problem of this kind you should justify your answer. Any vector in S is of the form a(1, 0, 0, 0)+ b(0, 1, 0, 0) and any vector in T is of the form c(0, 1, 0, 0)+ d(0, 0, 1, 0). Any vector that is in their intersection can be written both ways so we must have a(1, 0, 0, 0)+ b(0, 1, 0, 0)= c(0, 1, 0, 0)+ d(0, 0, 1, 0) for some numbers a, b, c, and d. That is the same as (a, b, 0, 0)= (0, c, d, 0) so we must have a= 0, b= c, d= 0.

(Be very careful with your wording. You cannot talk about "the vector that exists in both" because the intersection, being a subspace, contains an infinite number of vectors.)
 
  • #13
Yeah, I just talked to my professor about it and he said the dimension is the size of a basis. By "size of a basis," does that just mean how many vectors span S∩T, which is likewise the dimension of S∩T. If so the basis of S∩T is spanned by the vector [ 0 1 0 0]^t. Thus the size of the basis is 1 and the dimension is 1.

Is that the right idea?
 
  • #14
oops
 
Last edited:
  • #15
I think you got it. [0 1 0 0]^t span both S and T, thus dim(SnT)=1.

I could be wrong though. Anyone else verify?
 
  • #16
Hmmm. There's a relationship dim(U+V)=dim(U)+dim(V)-dim(U ∩ T)
Where U is your S and V is your T.
Dim(U+V)=2=2+2-dim(U ∩ T)
Which makes dim(U ∩ T)=2
 
  • #17
hmmm That equation is saying there's 2, but i think hallsofivy says there's 1. I'm really confused. That equation does make sense tho, U+V is spanned by 2 linearly independent vectors.
 
  • #18
charlies1902 said:
Hmmm. There's a relationship dim(U+V)=dim(U)+dim(V)-dim(U ∩ T)
Where U is your S and V is your T.
Dim(U+V)=2=2+2-dim(U ∩ T)
Which makes dim(U ∩ T)=2

pyroknife said:
hmmm That equation is saying there's 2, but i think hallsofivy says there's 1. I'm really confused. That equation does make sense tho, U+V is spanned by 2 linearly independent vectors.
No, U+ V (Your S+ T) is spanned by three linearly independent vectors {< 1, 0, 0, 0>, <0, 1, 0, 0>, and <0, 0, 1, 0>, the three vectors you gave initially. So dim(U+ V)= 3, not two.
so dim(U+ V)= 3= 2+ 2- dim(U∩V)= 2+ 2- 1.
 
  • #19
Oh I think I misunderstood the meaning of dim(U+V). I thought you add U+V then find the dimension.
 

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