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Mathematics
LINEAR ALGEBRA · A FIRST LOOK

Matrices that move a plane

A 2 × 2 matrix is four numbers with a geometric meaning. Tell two special vectors where to go, and every other point follows. Start with ordinary coordinates, then watch what changes.

01Two directions are enough to locate every point.

A vector is a directed displacement: (1, 0) means one step right and zero steps up. (0, 1) means zero steps right and one step up. Draw them from the origin of an ordinary Cartesian coordinate system.

THE STANDARD BASIS
e₁ (1, 0)e₂ (0, 1)-2-2-1-11122xy0Faint axes stay fixed · original grid spacing = 1
I =
10\begin{matrix}1\\0\end{matrix}
01\begin{matrix}0\\1\end{matrix}
Column 1e₁Column 2e₂

The standard orthonormal basis

ortho
Perpendicular / orthogonal: the angle between them is 90°.
normal
Normalized: each vector has magnitude (length) 1.
basis
Two independent directions. Scaling and adding them reaches every point, with one unique pair of coefficients.
(xy)=x(10)e1+y(01)e2\begin{pmatrix}x\\y\end{pmatrix}=x\underbrace{\begin{pmatrix}1\\0\end{pmatrix}}_{\mathbf e_1}+y\underbrace{\begin{pmatrix}0\\1\end{pmatrix}}_{\mathbf e_2}

Read down each column of I: the first is e₁, the second is e₂. This is the identity matrix. As a transformation it sends each basis vector back to itself, so every point stays where it was.

I(xy)=(xy)I\begin{pmatrix}x\\y\end{pmatrix}=\begin{pmatrix}x\\y\end{pmatrix}

02Change the columns. Move the whole plane.

In the starting example, the first column tells e₁ to go to u = (2, 1); its second tells e₂ to go to v = (1, 2). The dashed arrows mark those destinations before anything moves. Press play, then watch the two families of grid lines follow their basis vectors.

FIRST, LOCATE THE TWO DESTINATIONS0%
0%
P′ (1, 1)u (1, 0)v (0, 1)-5-4-3-3-2-2-1-111223345xy0Faint axes stay fixed · original grid spacing = 1
Moving point P=(11)P'=\begin{pmatrix}1\\1\end{pmatrix}Shaded area 1

The destination matrix

A =
u=(21)u=\begin{pmatrix}2\\1\end{pmatrix}v=(12)v=\begin{pmatrix}1\\2\end{pmatrix}
u and v are independent, so they form a new basis. But they are not perpendicular and neither has length 1: a basis need not be orthonormal.

Follow one point

x and y count how much of each basis vector to add. Try a negative value: that step goes in the opposite direction.

1
1
A(11)=1(21)+1(12)=(33)A\begin{pmatrix}1\\1\end{pmatrix}=1\,\begin{pmatrix}2\\1\end{pmatrix}+1\,\begin{pmatrix}1\\2\end{pmatrix}=\begin{pmatrix}3\\3\end{pmatrix}

This equation gives the final point. The solid coloured step followed by the dashed coloured step shows the same addition on the moving grid.

What moved, and what did not?

The faint Cartesian axes are our fixed ruler. We actively move the points and the coloured grid; we are not moving that ruler. In the example, P = (1, 1) becomes P′ = (3, 3) on the fixed axes. Relative to the new basis, the image still means “one u plus one v”. Changing the coordinates of an unmoved point would be a different operation.

A=(abcd),A(xy)=x(ac)+y(bd)A=\begin{pmatrix}a&b\\c&d\end{pmatrix},\qquad A\begin{pmatrix}x\\y\end{pmatrix}=x\begin{pmatrix}a\\c\end{pmatrix}+y\begin{pmatrix}b\\d\end{pmatrix}

This is why two columns determine the whole transformation: every vector is a scaled sum of the original basis vectors. A linear transformation preserves those sums and scale factors. Straight lines remain straight (or collapse), parallel grid lines remain parallel or coincide/collapse, and the origin stays put.

Read a matrix by its columns.

A =
21\begin{matrix}2\\1\end{matrix}
12\begin{matrix}1\\2\end{matrix}
Column 1uColumn 2v

The first column is where (1, 0) lands. The second is where (0, 1) lands. Every other point follows by the same scaled addition. If the two destinations are independent, they provide a new grid; if they lie on one line, a whole dimension is lost.

The grid shown is a finite window into an infinite plane. These are linear transformations: they preserve vector addition and scalar multiplication, and fix the origin. A translation is a different kind of transformation.