Having problems understanding nullspace

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In summary, the conversation discussed finding a matrix A with V as its row space and a matrix B with V as its nullspace, as well as finding a basis for the space of 2x3 matrices whose nullspace contains (2,1,1). The solution involved using matrix multiplication and solving equations to find a combination of variables for the matrices. The basis for the nullspace was found to be three matrices.
  • #1
PenTrik
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Homework Statement


If V is the subspace spanned by (1,1,1) and (2,1,0), find a matrix A that has V as its row space. Find a matrix B that has V as its nullspace

Homework Equations


Ax = 0 for a nullspace

The Attempt at a Solution



So straight off the bat, I think I can solve the first part. Should be simple enough right? Matrix A that has V as its row space is just the matrix
[[1,1,1]
[2,1,0]]

But how do I find matrix B that has V as its nullspace?
The only thing I can possibly think of its to do what I have done before which is to do the rref

Which I think gives me
[[1,0,-1]
[0,1,2]]

Do I run linear combination on the row space from here?Also, a similar question that I am having problems with is
Find a basis for the space of a 2x3 matrices whose nullspace contains (2,1,1)

I'm not even sure how to approach this question. My gut instinct tells me to run matrix multiplication on this one, such that

[tex]
\begin{pmatrix} x_{11} & x_{12} & x_{13} \\ x_{21} & x_{22} & x_{23} \end{pmatrix} \begin{pmatrix} 2 \\ 1 \\ 1 \end{pmatrix} = \begin{pmatrix} 0 \\ 0 \\ 0 \end{pmatrix}
[/tex]

This is about as far as my understanding of nullspaces carries me.
 
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  • #2
PenTrik said:

Homework Statement


If V is the subspace spanned by (1,1,1) and (2,1,0), find a matrix A that has V as its row space. Find a matrix B that has V as its nullspace


Homework Equations


Ax = 0 for a nullspace


The Attempt at a Solution



So straight off the bat, I think I can solve the first part. Should be simple enough right? Matrix A that has V as its row space is just the matrix
[[1,1,1]
[2,1,0]]

But how do I find matrix B that has V as its nullspace?
The only thing I can possibly think of its to do what I have done before which is to do the rref
Do the matrix multiplication
[tex]\begin{bmatrix}a & b & c \\d & e & f\end{bmatrix}\begin{bmatrix}1 & 0 \\ 0 & 1 \\ -1 & 2\end{bmatrix}[/tex]
and set it equal to
[tex]\begin{bmatrix}0 & 0 \\ 0 & 0\end{bmatrix}[/tex]
That will give you four equations, a- c= 0, b+ 2c= 0, d- f= 0, e+ 2f= 0. That is four equations in six variables. You can solve for 4 of the variables in terms of the other 2. Notice that the problem says "find a matrix". There are an infinite number of such matrices.

Which I think gives me
[[1,0,-1]
[0,1,2]]

Do I run linear combination on the row space from here?


Also, a similar question that I am having problems with is
Find a basis for the space of a 2x3 matrices whose nullspace contains (2,1,1)

I'm not even sure how to approach this question. My gut instinct tells me to run matrix multiplication on this one, such that

[tex]
\begin{pmatrix} x_{11} & x_{12} & x_{13} \\ x_{21} & x_{22} & x_{23} \end{pmatrix} \begin{pmatrix} 2 \\ 1 \\ 1 \end{pmatrix} = \begin{pmatrix} 0 \\ 0 \\ 0 \end{pmatrix}
[/tex]

This is about as far as my understanding of nullspaces carries me.
Exactly what you needed to do! (Except that the matrix on the right should have only two rows.) When you do that multiplication you get
[tex]\begin{bmatrix} 2x_{11}+ x_{12}+ x_{13} \\ 2x_{21}+ x_{22}+ x_{23}\end{bmatrix}= \begin{bmatrix} 0 \\ 0\end{bmatrix}[/tex]
which gives you two equation for the six variables: [itex]2x_{11}+ x_{12}+ x_{13}= 0[/itex] and [itex]2x_{21}+ x_{22}+ x_{23}= 0[/itex]. Now you can solve for 2 of those in terms of the other 4 very easily: [itex]x_{12}= -2x_{11}- x_{13}[/itex] and [itex]x_{22}= -x_{21}- x_{23}[/itex]. Put those into the original matrix:
[tex]\begin{bmatrix} x_{11} & -2x_{11}- x_{13} & x_{13} \\ x_{21} & -2x_{21}- x_{23} & x_{23} \end{bmatrix}[/tex]
[tex]= \begin{bmatrix} x_{11} & -2x_{11} & 0 \\ 0 & 0 & 0 \end{bmatrix}+ \begin{bmatrix}0 & -1 & 1 \\ 0 & 0 & 0\end{bmatrix}[/tex]
[tex]+ \begin{bmatrix}0 & 0 & 0 \\ x_{21} & -2x_{21} & 0\end{bmatrix}+ \begin{bmatrix}0 & 0 & 0 \\ 0 & -x_{23} & x_{23}\end{bmatrix}[/tex]

[tex]= x_{11}\begin{bmatrix}1 & -2 & 0 \\ 0 & 0 & 0\end{bmatrix}+ x_{13}\begin{bmatrix} 0 & 0 & 0 \\ 1 & -2 & 0\end{bmatrix}+ x_{23}\begin{bmatrix}0 & 0 & 0 \\ 0 & -1 & 1\end{bmatrix}[/tex]
Do you get the point?
 
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  • #3
So for the first part, this would mean that my solution is basically whatever combination I can get out of the equations I have. So if I make a = 1 and d = 1, then my matrix becomes

[[1,-2,1]
[1,-2,1]]

So is this a possible solution to the nullspace?

as for part two:
this means that the basis of my nullspace would be
[[1,2,0]
[0,0,0]]

and
[[0,0,0]
[1,-2,0]]

and

[[0,0,0]
[0,-1,1]]

Though I thought basis of a nullspace were normally written as vectors rather than matrixes? Or does this make the vectors, <0,0,0>,<0,-1,1>,<1,-2,0>
 
  • #4
you were asked to find a basis for "the space of a 2x3 matrices". In this case your vector space is a space of matrices. Your vectors are matrices!
 
  • #5
Oh, now I understand.
Much thanks, you cleared a lot of this up.
 

1. What is the nullspace?

The nullspace, also known as the kernel, is the set of all vectors that when multiplied by a given matrix result in the zero vector. In other words, it is the solution space for the homogeneous equation Ax = 0.

2. Why is understanding the nullspace important?

Understanding the nullspace is important because it provides insight into the behavior of a matrix. It helps identify linear dependence and can be used to solve systems of linear equations and find solutions to homogeneous systems.

3. How do you find the nullspace of a matrix?

To find the nullspace of a matrix, you can use Gaussian elimination or row reduction to put the matrix into reduced row echelon form. The columns with leading 1's in the reduced matrix form the basis for the nullspace.

4. Can a matrix have multiple nullspaces?

Yes, a matrix can have multiple nullspaces. If a matrix has more than one zero row after row reduction, then there are infinitely many solutions to the homogeneous equation Ax = 0, and therefore multiple nullspaces.

5. How does the nullspace relate to the rank of a matrix?

The rank of a matrix is equal to the number of pivot columns in its reduced row echelon form. The dimension of the nullspace is equal to the number of non-pivot columns. Therefore, the rank and nullspace are complementary, with the sum of their dimensions equal to the number of columns in the matrix.

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