> [!summary]
The null space is a set of vectors that are mapped to the zero vector.
>
**Key Equations:**
$\text{Null}(L)=\left\{ A \vec{x}=\vec{0} \quad |\vec{x} \in \mathbb{R}^n \right\}$
>[!info]+ Read Time
**⏱ 2 mins**
# Definition
The null space is an analytical representation of a [[Kernel|kernel]].
The null space of a [[Matrix Mapping (Transformations)|linear transformation]] ($L: \mathbb{R}^n\to \mathbb{R}^m$) is a [[Subspace|subspace]] of the [[Domain & Codomain|domain]] $\mathbb{R}^n$, that are mapped to the [[Zero Vector|zero vector]] in the [[Domain & Codomain|codomain]] $\mathbb{R}^m$. The null space is written as $\text{Null}(L)$ formally defined below
$
\begin{array}{c}
\text{Null}(L) &= \left\{ L(\vec{x})=\vec{0} \quad |\vec{x} \in \mathbb{R}^n \right\} \\
&= \left\{ A \vec{x}=\vec{0} \quad |\vec{x} \in \mathbb{R}^n \right\}
\end{array}
$
> [!note]+ Visualization of a null space
![[np_g_1.gif]]
The linear transformation of a set of vectors from $\mathbb{R}^2\to \mathbb{R}^1$ mapping to the zero vector.
## Proof of Subspace
> [!warning] Assumptions
To prove null space is a [[Subspace|subspace]] of the domain through the [[Subspace|subspace tests]], assume the following:
> - If $\vec{x},\vec{y}\in \text{null}(A)$ then $A\vec{x} = \vec{0}$ and $A\vec{x}=\vec{0}$
> - $c\in \mathbb{R}$
**Zero vector:**
$A \vec{0}= \vec{0} \quad \Rightarrow \vec{0}\in \text{null}(A)$
**Closed under vector addition:**
$
A(\vec{x} +\vec{y})=A \vec{x}+A \vec{y}= \vec{0}+ \vec{0}=\vec{0} \quad \Rightarrow \vec{x} + \vec{y} \in \text{null}(A)
$
**Closed under scalar multiplication:**
$
A(c \vec{x} ) = c(A \vec{x}) =c \cdot \vec{0} = \vec{0} \quad \Rightarrow c \vec{x} \in \text{null}(A)
$
# Resources
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