The scalar product, also called the dot product, and the vector product, also called the cross product, are
For nonzero vectors, let be their angle. Their Euclidean norms satisfy
The cross product is orthogonal to both vectors, with its orientation determined by the right-hand rule. If either vector is zero, both products vanish, although the angle is undefined.
A real square matrix is an orthogonal matrix when
Here is the transpose and the identity matrix; equivalently, its columns form an orthonormal basis. If this holds, the squared Euclidean norm obeys
so the linear transformation preserves length.
Conversely, suppose for every vector . Put , a symmetric matrix. Then for every vector. Taking , the standard basis vectors, gives . Taking for gives . Thus , proving that the linear transformation preserves length if and only if is an orthogonal matrix.
Choose the first orthonormal basis vector to be . If is not parallel to , choose along ; otherwise choose any unit vector orthogonal to . Complete to an orthonormal basis with . The matrix with rows is an orthogonal matrix, and expressing the three unit vectors in this basis gives
The last two components of have polar coordinates of the displayed form; we may choose . If they vanish, is arbitrary.
An orthogonal transformation preserves dot products. Taking dot products with , and then using the unit Euclidean norms, gives
The remaining dot product gives
An orthogonal matrix has determinant , so it preserves the absolute scalar triple product. In the new coordinates this scalar triple product is . Consequently
Taking the nonnegative square root proves
No division by or was used, so the proof includes parallel vectors. Equivalently, the expression under the square root is the Gram determinant of the three unit vectors.

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