In general, the term ‘cross product’ is used for any operation denoted by the symbol ‘’, such as cartesian product, direct product, Tychonoff product, or (subsuming all of these) product in a category.
However, there is another completely different context, used in the elementary analysis of vector spaces, and that is what we discuss here. Originally isolated from the multiplication operation in quaternions as a binary operation on , the cross product now has generalisations to other arities, other dimensions, and other ground fields.
This operation is invariant under orthogonal transformations and there is nothing special here about the real numbers, so given any -dimensional oriented inner product space over any field, we have a bilinear cross product
given, upon choosing any oriented basis for , by the formula above.
We have already, trivially, generalized the cross product to other ground fields. One way to generalise it to other dimensions is to identify characteristic features as a bilinear operation and see what operations in other dimensions have these.
such that for all we have
Orthgonality: is orthogonal to both and ; that is, .
Area: if are orthogonal.
From these, we can prove a more general formula for :
(Using the polarization identity to express in terms of , , and , this is the double of Hero’s Formula for the area of a triangle.)
We then have over the real numbers:
These cross products exist over any base field, but as far as I know there may be additional cross products over some. (Of course, the claim that there are uncountably many cross products in dimensions should be generalised and made more precise; the space of these inner products is some algebraic variety.)
Binary cross products are closely related to normed division algebras (NDAs). Given a normed division algebra , the imaginary hyperplane inherits an inner product from and gains a cross product as
Conversely, given an inner product space with a binary cross product, the orthogonal direct sum becomes a NDA as
where is the ground field.
By Hurwitz's theorem?, the only finite-dimensional NDAs over are itself (the real numbers), (the complex numbers), (the quaternions), and (the octonions). Thus the limited possibilities for binary cross products are determined by the limited possibilities for NDA structures.
Given an oriented inner product space of finite dimension , we can define the signed volume of an -tuple of vectors. (See also volume form.) This allows us to characterise a co-unary cross product of vectors as a multilinear operation
always. There is exactly one such cross product on any such (so two if we start with an unoriented inner product space).
In dimensions, this also recovers the classical cross product.
In general, let a vector-valued cross product on any inner product space be a multilinear function
Orthgonality: is orthogonal to each .
Area: if the are mutually orthogonal.
Then for an inner product space over of finite dimension , we have:
The cross product is also called ‘outer product’, and both of these terms are sometimes also used for the exterior product. In its most basic form, the exterior product of two vectors is a bivector . In dimensions, given an inner product and an orientation, we can use the Hodge dual to turn this into a vector, and this is the classical cross product once more. In dimensions, using the same structure, we can turn the bivector into a scalar; this is sometimes called the scalar-valued cross product . Using only the inner product but not the orientation, we get (respectively) a pseudovector? (sometimes called an axial vector) or a pseudoscalar?; this perspective is common in geometric algebra?. (In general in dimension , a bivector becomes an -(pseudo)-vector, but this is not usually an simplification.)
In classical applications of the cross product, often not all of the structure is needed, and the exterior product is really the fundamental concept.
If is a Riemannian manifold, then the tangent space at each point is an inner product space, so it may be possible to smoothly assign a -ary cross product to these spaces. If this is done, then we can take the curl of a -vector field? as follows:
This vector field is the curl of the original -vector field. This justifies the notation for the curl.
When and , there is one smooth choice of cross product for each orientation of , and we recover the classical notion of curl.
When and , we may also consider the scalar-valued curl, using the scalar-valued cross product described above.