Finding a Basis for a set of vectors

In summary, H is a subspace of ℝ^4 with a basis of span(1, -1, 1, 0) and (-3, 1, 0, 1). The vectors can be obtained by rewriting the given set in matrix form and reducing it to its basis vectors. The dimensions of the subspace are 2.
  • #1
Smazmbazm
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Homework Statement



Let H be the set of all vectors of the form [itex](a-3b, b-a, a, b)[/itex] where [itex]a[/itex] and [itex]b[/itex] are arbitrary real scalars. Show that H is a subspace of [itex]ℝ^4[/itex] and find a basis for it.

Right, I've shown it's a proper subspace, just need help with finding a basis. Is [itex]{a-3b, b}[/itex] a suitable basis for this?

I achieved this but putting the vectors into matrix form

1 -3
-1 1
1 0
0 1

Reducing them to end up with

1 -3
0 0
0 0
0 1

Is this a proper way to solve this question? Thanks in advanced.
 
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  • #2
I believe so. That basis spans a two dimensional substance, because a-3b, and b-a are both linear combination of the remaining two vectors: a, b. By reducing you show that the two were linear combinations, so they went to zero, and you're left with the two basis vectors. Consider one last modification, though:

##\left[
\begin{array}{cc}
1 & 0 \\
0 & 1 \\
0 & 0 \\
0 & 0
\end{array}
\right]##

The space is just span(a,b).
 
  • #3
Great, thanks for that. Makes sense
 
  • #4
What, exactly is your answer? Once you have row reduced, the only 4 dimensional vectors we can get from that matrix are (1, 0, 0, 0) and (-3, 0, 0, 1). That clearly cannot be a basis for this space because the second and third components would always be 0 which is not the case here.

And what do you mean by "Is a−3b,b a suitable basis for this?". a and b, and so a- 3b, are numbers, not vectors and so cannot be a "basis".

Here is how I would do it. H is the set of all vectors of the form (a- 3b, b- a, a, b).

(a- 3b, b- a, a, b)= (a, -a, a, 0)+ (-3b, b, 0, b)= a(1, -1, 1, 0)+ b(-3, 1, 0, 1).

And now a basis, and the dimension, are obvious.
 
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  • #5
It's been so long since I've had linear algebra, that is exactly how it's done. I got caught up with the linear dependence. But, HallsofIvy is exactly correct

$$
a \left(\begin{array}{c}1 \\ -1 \\ 1 \\ 0\end{array}\right) + b\left(\begin{array}-3 \\ 1 \\ 0 \\ 1\end{array}\right) $$gives you the basis vectors. While the subsspace is still dim = 2, it's formed by span##\{\left(\begin{array}{c}1 \\ -1 \\ 1 \\ 0\end{array}\right),\left(\begin{array}-3 \\ 1 \\ 0 \\ 1\end{array}\right)\}##.

Sorry about the dodgy reply.
 

FAQ: Finding a Basis for a set of vectors

What is a basis for a set of vectors?

A basis for a set of vectors is a set of linearly independent vectors that span the vector space. In simpler terms, it is a set of vectors that can be combined in different ways to represent any vector in the vector space.

How do you find a basis for a set of vectors?

To find a basis for a set of vectors, you need to first check if the vectors are linearly independent. If they are not, you can use Gaussian elimination or row reduction to reduce the set of vectors to a linearly independent set. Then, you can use these linearly independent vectors as the basis for the set.

Why is it important to find a basis for a set of vectors?

Finding a basis for a set of vectors is important because it allows us to represent any vector in the vector space using a combination of the basis vectors. This makes it easier to perform operations on vectors and understand the properties of the vector space.

Can a set of vectors have more than one basis?

Yes, a set of vectors can have multiple bases. This is because there can be different combinations of linearly independent vectors that can span the same vector space. However, all bases for a set of vectors will have the same number of vectors.

Is it possible for a set of vectors to not have a basis?

No, a set of vectors must have a basis. This is because any vector space must have a set of basis vectors that can be used to represent all of the vectors in that space. If a set of vectors is not linearly independent, it can be reduced to a linearly independent set that can serve as the basis for the vector space.

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