logo

Row Space, Column Space, Null Space 📂Matrix Algebra

Row Space, Column Space, Null Space

Definition1

A=[a11a12a1na21a22a2nam1am2amn] A = \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}

For a matrix AA, the mm number of Rn\mathbb{R}^{n} vectors made from the rows of AA

r1=[a11a12a1n]r2=[a21a22a2n]rm=[am1am2amn] \begin{align*} \mathbf{r}_{1} =& \begin{bmatrix} a_{11} & a_{12} & \cdots & a_{1n} \end{bmatrix} \\ \mathbf{r}_{2} =& \begin{bmatrix} a_{21} & a_{22} & \cdots & a_{2n} \end{bmatrix} \\ &\vdots \\ \mathbf{r}_{m} =& \begin{bmatrix} a_{m1} & a_{m2} & \cdots & a_{mn} \end{bmatrix} \end{align*}

are called the row vectors of AA. The nn number of Rm\mathbb{R}^{m} vectors made from the columns of AA

c1=[a11a21am1],c2=[a12a22am2],,cn=[a1na2namn] \mathbf{c}_{1} = \begin{bmatrix} a_{11} \\ a_{21} \\ \vdots \\ a_{m1} \end{bmatrix},\quad \mathbf{c}_{2} = \begin{bmatrix} a_{12} \\ a_{22} \\ \vdots \\ a_{m2} \end{bmatrix},\quad \dots,\quad \mathbf{c}_{n} = \begin{bmatrix} a_{1n} \\ a_{2n} \\ \vdots \\ a_{mn} \end{bmatrix}

are called the column vectors of AA.

A=[a11a12a1na21a22a2nam1am2amn]=[r1r2rm]=[c1c2cn] \begin{align*} A =& \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} = \begin{bmatrix} \mathbf{r}_{1} \\ \mathbf{r}_{2} \\ \vdots \\ \mathbf{r}_{m} \end{bmatrix} \\ =& \begin{bmatrix} \mathbf{c}_{1} & \mathbf{c}_{2} & \cdots & \mathbf{c}_{n} \end{bmatrix} \end{align*}

The Rn\mathbb{R}^{n} subspace generated by the row vectors r1,r2,,rm\mathbf{r}_{1}, \mathbf{r}_{2},\dots,\mathbf{r}_{m} of AA is called the row space of AA and is denoted as follows.

R(A)orrow(A) \mathcal{R} (A) \quad \text{or} \quad \text{row}(A)

The Rm\mathbb{R}^{m} subspace generated by the column vectors c1,c2,,cn\mathbf{c}_{1}, \mathbf{c}_{2},\dots,\mathbf{c}_{n} of AA is called the column space of AA and is denoted as follows.

C(A)orcol(A) \mathcal{C} (A) \quad \text{or} \quad \text{col}(A)

The set of solutions to the homogeneous system of linear equations Ax=0A \mathbf{x} =\mathbf{0} is called the null space of AA and is denoted as follows.

N(A)ornull(A) \mathcal{N}(A) \quad \text{or} \quad \text{null}(A)

Explanation

Such concepts were devised to solve

Ax=b \begin{equation} A\mathbf{x} = \mathbf{b} \end{equation}

systems of linear equations. That is, in linear algebra, there is interest in the relationship between the solutions of (1)(1) and the row space, column space, and null space of AA. In particular, finding the basis of the row space is related to solving linear systems. Specifically, the dimension of the row space and column space is called the rank, and the dimension of the null space is called the nullity.

Note that the column space is also called the image. If one considers the matrix AA as a concept of a function, then the function corresponding to ARm×nA \in \mathbb{R}^{m \times n} can also be seen as TA:RnRmT_{A} : \mathbb{R}^{n} \to \mathbb{R}^{m}.

Theorem 1

A necessary and sufficient condition for the linear system Ax=bA \mathbf{x} = \mathbf{b} to have a solution is bC(A)\mathbf{b} \in \mathcal{C}(A).

Theorem 2

Let x0\mathbf{x}_{0} be some solution to Ax=bA\mathbf{x} = \mathbf{b}. Let us call S={v1,v2,,vk}S= \left\{ \mathbf{v}_{1}, \mathbf{v}_{2}, \dots, \mathbf{v}_{k} \right\} a basis for N(A)\mathcal{N}(A). Then, all solutions of Ax=bA\mathbf{x} = \mathbf{b} can be expressed as follows.

x=x0+c1v1+c2v2++ckvk \begin{equation} \mathbf{x} = \mathbf{x}_{0} + c_{1}\mathbf{v}_{1} + c_{2}\mathbf{v}_{2} + \cdots + c_{k}\mathbf{v}_{k} \end{equation}

Conversely, for all constants c1,c2,,ckc_{1}, c_{2}, \dots, c_{k}, the above x\mathbf{x} is a solution to Ax=bA\mathbf{x} = \mathbf{b}.


(2)(2) is called the general solution of Ax=bA \mathbf{x} = \mathbf{b}. x0\mathbf{x}_{0} is called the particular solution of Ax=bA \mathbf{x} = \mathbf{b}. Furthermore, c1v1+c2v2++ckvkc_{1}\mathbf{v}_{1} + c_{2}\mathbf{v}_{2} + \cdots + c_{k}\mathbf{v}_{k} is called the general solution of Ax=0A \mathbf{x} = \mathbf{0}.

From these theorems, it can be understood that the general solution of a nonhomogeneous linear system can be represented as the sum of a particular solution and the general solution of the homogeneous linear system.

See Also

Kernel in Abstract Algebra

The null space is written as kerA\ker A and also called the kernel. This is because it is a specialization of the general concept of kernel discussed in abstract algebra, seeing AA as a function.


  1. Howard Anton, Chris Rorres, Anton Kaul, Elementary Linear Algebra: Applications Version(12th Edition). 2019, p263-267 ↩︎