Proof of vector dimensions using inequalities

In summary: Indeed, since $\mathbf v_1$ and $\mathbf v_2$ are linearly independent, $W$ must have at least dimension $2$, which is what we were still looking for.Effectively you are using that fact to conclude that $\mathbf w_1$ and $\mathbf w_2$ must be linear independent (and not zero) as well.
  • #1
TheFallen018
52
0
Hello all!

I've got this problem I'm trying to do, but I'm not sure what the best way to approach it is.

View attachment 8713

It's obvious that there can only be 2 dimensions, because there's only two linearly independent vectors in the span. However, what would be a good way of using the inequalities to prove it? I can't think of a good way to do that.

Any ideas would be great!

Thanks :)
 

Attachments

  • Screenshot_36.png
    Screenshot_36.png
    16.6 KB · Views: 65
Physics news on Phys.org
  • #2
Hey Fallen18!

It is not given that there are 2 linearly independent vectors in the span.
That's why we only get $\le 2$ from the span.
 
  • #3
Klaas van Aarsen said:
Hey Fallen18!

It is not given that there are 2 linearly independent vectors in the span.
That's why we only get $\le 2$ from the span.

Good point. w1 and w2 could technically be multiples of each other, making W a one dimensional set. However, how would you do a $\ge$ 2 proof? Couldn't w2 be a multiple of w1, and w3 also be a multiple of w1? In that case I would be unsure on how to continue. Thanks
 
  • #4
TheFallen018 said:
Good point. w1 and w2 could technically be multiples of each other, making W a one dimensional set. However, how would you do a $\ge$ 2 proof? Couldn't w2 be a multiple of w1, and w3 also be a multiple of w1? In that case I would be unsure on how to continue. Thanks

W could even be 0-dimensional, since the $w_i$ could be zero-vectors.
Hpwever, it is also given that the $v_i$ are linearly independent and also in W...
 
  • #5
Klaas van Aarsen said:
W could even be 0-dimensional, since the $w_i$ could be zero-vectors.
Hpwever, it is also given that the $v_i$ are linearly independent and also in W...

Oh, yes, I should have made that clear in my first post. My reasoning for it having to be two dimensional, is since v1 and v2 are in the set and linearly independent, then they must be part of the span, in that for example w1=v1 and w2=v2, or something like that. However, now that I think about it, it could mean that v1 and v2 are only independent to each other, which makes them far less useful. I'm hoping my first assumption was right though. What do you think?

Edit:
Oh, I think I see the significance of that now. If v1 and v2 are linearly independent, then w1, w2 at least must be unique vectors. If they were the zero vectors, or multiples of each other, v1 and v2 couldn't be linearly independent. Therefore w1 and w2 are linearly independent, and since w3 is a combination of w1 and w2 then this must be a two dimensional set. However, that's still not solving it using inequalities, so I'm not sure that will do the trick.
 
Last edited:
  • #6
TheFallen018 said:
Oh, yes, I should have made that clear in my first post. My reasoning for it having to be two dimensional, is since v1 and v2 are in the set and linearly independent, then they must be part of the span, in that for example w1=v1 and w2=v2, or something like that. However, now that I think about it, it could mean that v1 and v2 are only independent to each other, which makes them far less useful. I'm hoping my first assumption was right though. What do you think?

Edit:
Oh, I think I see the significance of that now. If v1 and v2 are linearly independent, then w1, w2 at least must be unique vectors. If they were the zero vectors, or multiples of each other, v1 and v2 couldn't be linearly independent. Therefore w1 and w2 are linearly independent, and since w3 is a combination of w1 and w2 then this must be a two dimensional set. However, that's still not solving it using inequalities, so I'm not sure that will do the trick.

Indeed, since $\mathbf v_1$ and $\mathbf v_2$ are linearly independent, $W$ must have at least dimension $2$, which is what we were still looking for.
Effectively you are using that fact to conclude that $\mathbf w_1$ and $\mathbf w_2$ must be linear independent (and not zero) as well.

That is:
  1. $\mathbf v_1$ and $\mathbf v_2$ are linearly independent and in $W$, therefore $\text{dim}\ W \ge 2$.
  2. $\mathbf w_1$, $\mathbf w_2$, $\mathbf w_3$ span $W$ and $\mathbf w_3$ is a linear combination of $\mathbf w_1$ and $\mathbf w_2$, therefore $\text{dim}\ W \le 2$.
  3. Since $\text{dim}\ W \ge2$, $\mathbf w_1$ and $\mathbf w_2$ must be linearly independent.
 

1. What is "Proof of vector dimensions using inequalities"?

"Proof of vector dimensions using inequalities" is a mathematical technique used to prove the dimensions of vector spaces by using inequalities, rather than direct calculations. It is often used in linear algebra to prove the dimensions of higher-dimensional vector spaces.

2. How is "Proof of vector dimensions using inequalities" different from other methods of proving vector dimensions?

Unlike other methods, "Proof of vector dimensions using inequalities" does not require direct calculations or the use of specific examples. Instead, it relies on the properties of vector spaces and inequalities to prove the dimensions.

3. What are the benefits of using "Proof of vector dimensions using inequalities"?

One of the main benefits of using this technique is that it can be applied to a wide range of vector spaces, including higher-dimensional spaces. It also provides a more elegant and concise proof compared to other methods.

4. Are there any limitations to using "Proof of vector dimensions using inequalities"?

One limitation is that it may not work for all types of vector spaces. Additionally, it may be more difficult to understand for those who are not familiar with the properties of vector spaces and inequalities.

5. How can "Proof of vector dimensions using inequalities" be applied in real-world situations?

This technique can be applied in various real-world situations, such as in engineering and physics, where vector spaces are used to model and solve problems. It can also be used in computer science to analyze data and optimize algorithms.

Similar threads

  • Linear and Abstract Algebra
Replies
7
Views
814
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
9
Views
584
  • Linear and Abstract Algebra
Replies
1
Views
1K
Replies
1
Views
1K
Replies
8
Views
970
  • Linear and Abstract Algebra
Replies
33
Views
844
  • Calculus and Beyond Homework Help
Replies
15
Views
954
Replies
3
Views
2K
  • Linear and Abstract Algebra
Replies
3
Views
1K
Back
Top