Basis for the nullspace of this matrix

In summary: The basis for the kernel is the set, {<1, 3, -11>}.In summary, the nullspace is the set of vectors, <x, y, z> such that <x, y, z> satisfies the equation Ax = 0, where A is the given matrix. The basis for the nullspace is the set, {<1, 3, -11>}.
  • #1
Noxide
121
0
this is apparently "really simple", but I just don't know how to do it from the examples I have and I feel like a moron...

what's the basis for the nullspace of this matrix

[ 2 3 1]
[ 5 2 1]
[ 1 7 2]
[ 6 -2 0]
 
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  • #2


I'm not sure if your notation is a list of vectors in the matrix or if that is the actual matrix so I can't be more exact for now than to remind you that the nullspace is the solution space of the system Ax = 0, so start off by solving for the coefficient matrix A augmented with 0. Remember also that the basis of a space is the set of linearly independent vectors that spans the space in question.
 
  • #3


Noxide said:
this is apparently "really simple", but I just don't know how to do it from the examples I have and I feel like a moron...

what's the basis for the nullspace of this matrix

[ 2 3 1]
[ 5 2 1]
[ 1 7 2]
[ 6 -2 0]
The nullspace is the set of vectors, <x, y, z> such that
[tex]\begin{bmatrix}2 & 3 & 1 \\ 5 & 2 & 1\\ 1 & 7 & 2\\6 & -2 & 0\end{bmatrix}\begin{bmatrix}x \\ y \\ z\end{bmatrix}= \begin{bmatrix}0 \\ 0 \\ 0 \end{bmatrix}[/tex]
That is the same as the four equations 2x+ 3y+ z= 0, 5x+ 2y+ z= 0, x+ 7y+ 2z= 0, and 6x- 2y= 0. If we subtract the first equation from the second, we get 3x- y= 0 or y= 3x. Putting that into 6x- 2y= 0 we get 6x- 2(3x)= 6x- 6x= 0 which is satisfied for all x.

If we subtract 2 times the first equation from the third we get -3x+ y= 0 or y= 3x again. Those equations all reduce to y= 3x which cannot be reduced further. Putting y= 3x into the first equation we get 2x+ 3(3x)+ z= 0 so z= -11x. Putting y= 3x into the second equation we get 5x+ 2(3x)+ z= 0 so z= -11x. Putting y= 3x into the third equation, we get x+ 7(3x)+ 2z= 0 so 2z= -22x and z= -11x.

That is, any solution of that equation, any vector in the kernel, can be written as <x, y, z>= <x, 3x, -11x>= x <1, 3, -11>.
 
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FAQ: Basis for the nullspace of this matrix

What is the basis for the nullspace of a matrix?

The basis for the nullspace of a matrix is the set of all vectors that when multiplied by the matrix result in the zero vector. In other words, it is the set of all solutions to the equation Ax = 0, where A is the matrix in question.

How is the basis for the nullspace of a matrix calculated?

To find the basis for the nullspace of a matrix, we use the process of Gaussian elimination to reduce the matrix to its row-echelon form. The columns that do not contain a leading 1 in the row-echelon form will form the basis for the nullspace.

Why is the basis for the nullspace important?

The basis for the nullspace is important because it provides us with information about the solutions to a system of linear equations. It can tell us if the system has a unique solution, infinite solutions, or no solution at all.

Can the basis for the nullspace be empty?

Yes, it is possible for the basis for the nullspace to be empty. This means that there are no vectors that satisfy the equation Ax = 0, and therefore the matrix has no nullspace.

How does the basis for the nullspace relate to linear independence?

The basis for the nullspace is composed of linearly independent vectors. This means that none of the vectors in the basis can be written as a linear combination of the others. This is important because it helps us determine the dimension of the nullspace, which is equal to the number of linearly independent vectors in the basis.

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