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The outer product or wedge product is a non-closed vector product defined in a vector space
V over a scalar field F. It can be seen as a generalization to n dimensions of the Gibbs vectorial
product or cross product, which can only be defined in vector spaces of 3
or 7 dimensions.
The properties of the outer product "∧" are, for all vectors x, y,
z in Vn, and scalars a, b in F:
- Distributivity over the sum of vectors:
x∧(y + z) = x∧y +
x∧z
- (ax)∧(by) =
(ab)(x∧y)
- Anticommutativity or antisymmetry:
x∧y = −y∧x
- Associativity:
(x∧y)∧z =
x∧(y∧z)
- If x and y are linearly dependent, then x∧y =
0
By virtue of properties (1) and (2), the vector space becomes an algebra, and by
property (4) is also associative. The algebra generated is a
stepped algebra or graded algebra.
k-vectors
If two vectors x and y are linearly independent (LI), the outer product
generates a new entity called bivector. A vector can be seen as a "piece" of a straight line with an
orientation; a bivector is a piece of a plane with an orientation. Geometrically a bivector
x∧y is the sweeping surface generated when the vector x slips along
y in the direction of y. The area of this surface is the magnitude of the bivector,
||x∧y|| = ||x|| ||y|| sin(α), where
α is the angle between x and y. The orientation of the bivector is given by spinning from
x to y. Thus, reverting the order of the operands reverts the sense or orientation of the
bivector, but keeps its magnitude, so behaving exactly as the cross product.
Similarly, the product of a bivector with a third LI vector gives rise to an oriented volume, generated by sliding the
bivector "area" along of the third vector. This oriented volume is called trivector. In general, given
k LI vectors, their outer product generates a k-dimensional volume or k-vector.
If we took our vectors from an n-dimensional vector space, then we cannot get more than n LI vectors; thus,
the outer product of more than n vectors is always 0, and the n-vector is the "highest order" k-vector
that can be generated. Note that this n-vector is a representation of the original vector space
Vn.
The advantages of these new elements are many. A bivector can be used to unambiguously represent a plane embedded in any
n-dimensional space, while the use of the normal vector is only useful in a 3D space. A k-vector thus represents a k-dimensional
space in any n-dimensional space, and this representation does not change when switching to higher dimensional spaces.
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