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Matrices and Vectors

Cross Product and Geometry in Space

Mathematics I 341 words Free to read

Multiplying Vectors into a Vector

In three dimensions there is a second product, the cross product u×vu \times v, which — unlike the dot product — returns a vector. Its two defining geometric features:

So the cross product answers geometric questions the dot product cannot: it produces a normal direction and measures area. Note the sine (versus the dot product's cosine): the cross product is largest when the vectors are perpendicular and zero when they are parallel — parallel vectors span no area. This gives a parallelism test: u×v=0u \times v = \mathbf{0} exactly when uu and vv are parallel (the mirror of the dot product's orthogonality test).

The cross product is anticommutative: u×v=(v×u)u \times v = -(v \times u) — swapping the order reverses the resulting vector. This is unlike ordinary multiplication and unlike the dot product (which is symmetric), and it reflects the two possible perpendicular directions.

A related quantity, the scalar triple product u(v×w)u \cdot (v \times w), gives the signed volume of the parallelepiped spanned by three vectors; it is zero exactly when the three vectors are coplanar (lie in a common plane), a clean test for whether three directions are independent in space.

Common pitfall: expecting the cross product to be commutative, or confusing it with the dot product. u×v=(v×u)u \times v = -(v \times u) — order matters and flips the direction (anticommutative), whereas the dot product is symmetric. And the cross product returns a vector perpendicular to both inputs (magnitude uvsinθ\|u\|\|v\|\sin\theta), while the dot product returns a scalar (uvcosθ\|u\|\|v\|\cos\theta) — different outputs, different geometry.

Two vectors spanning a parallelogram, the accent cross-product vector rising perpendicular from the plane and the shaded area labeled |u||v|sin(theta) — direction and area together.

u×v=uvsinθ\|u \times v\| = \|u\|\,\|v\|\sin\theta

Cross Product and Geometry in Space

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