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Mathematics
LINEAR ALGEBRA · MEASURING WHAT VECTORS ENCLOSE

Determinants: area & volume

A determinant turns a square matrix into a number. Geometrically, it tells us how much signed area or volume the column vectors enclose. Let us first find out why its 2D formula is ad − bc.

01Why ad − bc? Watch the area stay put.

Start both vectors at the origin. Complete their opposite sides to enclose a parallelogram. Read the matrix down its columns: u = (a, c), v = (b, d). Dashed component lines show exactly which horizontal and vertical displacement each letter means.

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xy0bc = 1d = 2u (3, 1)v (1, 2)a = 3c = 1b = 1d = 2
Area throughout5
ad − bc61 = 5

Original matrix and columns

A=(abcd)=(3112)A=\begin{pmatrix}a&b\\c&d\end{pmatrix}=\begin{pmatrix}3&1\\1&2\end{pmatrix}
u=(ac)\mathbf u=\begin{pmatrix}a\\c\end{pmatrix}v=(bd)\mathbf v=\begin{pmatrix}b\\d\end{pmatrix}

Here a, b, c and d are positive, and ad > bc. We start with this simple case so each area can be seen directly.

h=dbcah=d-\frac{bc}{a}
S=ah=a(dbca)=adbcS=ah=a\left(d-\frac{bc}{a}\right)=ad-bc

Both rearrangements are shears: they slide parallel strips without stretching those strips. That is why we can measure the final rectangle instead of the original parallelogram. The small strokes merely make the sliding visible; the map applies to the whole continuous region.

We use columns to match the matrix-transformation lesson. You could instead use the rows (a, b) and (c, d): transposing a matrix leaves its determinant unchanged, so the enclosed area is the same.

02Zero area means one direction was lost.

The determinant is a signed area. Its absolute value is the geometric area; its sign tells the orientation of the ordered pair u, v. Now bring v onto the same line as u. The parallelogram becomes thinner until it has no area.

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xy0u (3, 1)v (1, 2)
det A5
Geometric area |det A|5
A=(3112),detA=5A=\begin{pmatrix}3&1\\1&2\end{pmatrix},\quad\det A=5
Independent vectors open up a 2D area. Approaching the same line reduces the perpendicular height, while the first vector stays fixed.
v=12udetA=0\mathbf v=\tfrac12\mathbf u\quad\Longrightarrow\quad\det A=0

This is linear dependence: one vector can be made by scaling the other. A zero vector also creates dependence. For a nonzero determinant, turning from u to v through the smaller angle is counterclockwise for a positive sign and clockwise for a negative sign. A negative determinant does not mean negative geometric area.

Area=adbc\text{Area}=|ad-bc|

03In three dimensions, area becomes volume.

Use three vectors from the same origin. Their sums give the eight corners of a parallelepiped: a slanted box. These three vectors are the columns of a 3 × 3 matrix. The absolute value of its determinant is the volume of that box. Drag the model to look around it.

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Drag to orbit · x, y, z are fixed reference axes
det A6.12
Geometric volume |det A|6.12
At the endpointPlane
A=(20.50.401.70.4001.8)A=\begin{pmatrix}2&0.5&0.4\\0&1.7&0.4\\0&0&1.8\end{pmatrix}

u · column 1 v · column 2 w · column 3

Keep u and v independent. Bring w into their plane until w = 0.6u + 0.5v. No pair is parallel, yet the set of three is dependent: w contributes no third direction.

Initially the base lies in the xy-plane: base area = 2 × 1.7 = 3.4, perpendicular height = 1.8, and volume = 3.4 × 1.8 = 6.12. A sloping edge is not the perpendicular height.

V=Sbaseh=detAV=S_{\rm base}\,h=|\det A|

Dependence means a missing dimension.

Vectors are linearly dependent if a combination of them equals zero with coefficients that are not all zero. Equivalently, at least one vector can be expressed using the others. In 2D, two dependent vectors lie on a line (or both are zero). In 3D, three dependent vectors lie in a plane, a line, or reduce to the origin.

detA=0columns of A are linearly dependent\det A=0\quad\Longleftrightarrow\quad\text{columns of A are linearly dependent}

For an n × n square matrix, the same idea measures n-dimensional signed volume. If the columns fail to supply all n independent directions, that n-dimensional volume is zero. A nonzero determinant means all n directions are present.

Revisit matrices as transformations →