Null Space Closed under Vector Addition
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Theorem
Let:
- $\map {\mathrm N} {\mathbf A} = \set {\mathbf x \in \R^n : \mathbf A \mathbf x = \mathbf 0}$
be the null space of $\mathbf A$, where:
- $\mathbf A_{m \times n} = \begin {bmatrix}
a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots & \vdots & \ddots & \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} \\ \end{bmatrix}$, $\mathbf x_{n \times 1} = \begin{bmatrix} x_1 \\ x_2 \\ \vdots \\ x_n \end{bmatrix}$ and $\mathbf 0_{m \times 1} = \begin {bmatrix} 0 \\ 0 \\ \vdots \\ 0 \end {bmatrix}$ are matrices
- the column matrix $\mathbf x_{n \times 1}$ is interpreted as a vector in the real Euclidean space $\R^n$.
Then $\map {\mathrm N} {\mathbf A}$ is closed under vector addition:
- $\forall \mathbf v, \mathbf w \in \map {\mathrm N} {\mathbf A}: \mathbf v + \mathbf w \in \map {\mathrm N} {\mathbf A}$
Proof
Let $\mathbf v, \mathbf w \in \map {\mathrm N} {\mathbf A}$.
By the definition of null space:
\(\ds \mathbf A \mathbf v\) | \(=\) | \(\ds \mathbf 0\) | ||||||||||||
\(\ds \mathbf A \mathbf w\) | \(=\) | \(\ds \mathbf 0\) |
Next, observe that:
\(\ds \mathbf A \paren {\mathbf v + \mathbf w}\) | \(=\) | \(\ds \mathbf A \mathbf v + \mathbf A \mathbf w\) | Matrix Multiplication Distributes over Matrix Addition | |||||||||||
\(\ds \) | \(=\) | \(\ds \mathbf 0 + \mathbf 0\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \mathbf 0\) |
The order is correct, by hypothesis.
Hence the result, by the definition of null space.
$\blacksquare$
Also see
- Null Space Contains Zero Vector
- Null Space Closed under Scalar Multiplication
- Null Space is Subspace
Sources
- For a video presentation of the contents of this page, visit the Khan Academy.