Multivector

Properties of multivectors can be seen by considering the two dimensional vector space V = R². Let the basis vectors be e₁ and e₂, so u and v are given by

${\displaystyle \mathbf {u} =u_{1}\mathbf {e} _{1}+u_{2}\mathbf {e} _{2},\quad \mathbf {v} =v_{1}\mathbf {e} _{1}+v_{2}\mathbf {e} _{2},}$

and the multivector u ∧ v, also called a bivector, is computed to be

${\displaystyle \mathbf {u} \wedge \mathbf {v} \ =\ {\begin{vmatrix}u_{1}&v_{1}\\u_{2}&v_{2}\end{vmatrix}}\ (\mathbf {e} _{1}\wedge \mathbf {e} _{2}).}$

The vertical bars denote the determinant of the matrix, which is the area of the parallelogram spanned by the vectors u and v. The magnitude of u ∧ v is the area of this parallelogram. Notice that because V has dimension two the basis bivector e₁ ∧ e₂ is the only multivector in ΛV.

The relationship between the magnitude of a multivector and the area or volume spanned by the vectors is an important feature in all dimensions. Furthermore, the linear functional version of a multivector that computes this volume is known as a differential form.

More features of multivectors can be seen by considering the three dimensional vector space V = R³. In this case, let the basis vectors be e₁, e₂, and e₃, so u, v and w are given by

${\displaystyle \mathbf {u} =u_{1}\mathbf {e} _{1}+u_{2}\mathbf {e} _{2}+u_{3}\mathbf {e} _{3},\quad \mathbf {v} =v_{1}\mathbf {e} _{1}+v_{2}\mathbf {e} _{2}+v_{3}\mathbf {e} _{3},\quad \mathbf {w} =w_{1}\mathbf {e} _{1}+w_{2}\mathbf {e} _{2}+w_{3}\mathbf {e} _{3},}$

and the bivector u ∧ v is computed to be

${\displaystyle \mathbf {u} \wedge \mathbf {v} \ =\ {\begin{vmatrix}u_{2}&v_{2}\\u_{3}&v_{3}\end{vmatrix}}\ (\mathbf {e} _{2}\wedge \mathbf {e} _{3})+{\begin{vmatrix}u_{1}&v_{1}\\u_{3}&v_{3}\end{vmatrix}}\ (\mathbf {e} _{1}\wedge \mathbf {e} _{3})+{\begin{vmatrix}u_{1}&v_{1}\\u_{2}&v_{2}\end{vmatrix}}\ (\mathbf {e} _{1}\wedge \mathbf {e} _{2}).}$

The components of this bivector are the same as the components of the cross product. The magnitude of this bivector is the square root of the sum of the squares of its components.

This shows that the magnitude of the bivector u ∧ v is the area of the parallelogram spanned by the vectors u and v as it lies in the three-dimensional space V. The components of the bivector are the projected areas of the parallelogram on each of the three coordinate planes.

Notice that because V has dimension three, there is one basis three-vector in ΛV. Compute the three-vector

${\displaystyle \mathbf {u} \wedge \mathbf {v} \wedge \mathbf {w} \ =\ {\begin{vmatrix}u_{1}&v_{1}&w_{1}\\u_{2}&v_{2}&w_{2}\\u_{3}&v_{3}&w_{3}\end{vmatrix}}\ (\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3}).}$

This shows that the magnitude of the three-vector u ∧ v ∧ w is the volume of the parallelepiped spanned by the three vectors u, v and w.

In higher-dimensional spaces, the component three-vectors are projections of the volume of a parallelepiped onto the coordinate three-spaces, and the magnitude of the three-vector is the volume of the parallelepiped as it sits in the higher-dimensional space.

Points in the affine component E: z = 1 of the projective plane have coordinates x = (x, y, 1). A linear combination of two points p = (p₁, p₂, 1) and q = (q₁, q₂, 1) defines a plane in R³ that intersects E in the line joining p and q. The multivector p ∧ q defines a parallelogram in R³ given by

${\displaystyle \mathbf {p} \wedge \mathbf {q} \ =\ (p_{2}-q_{2})(\mathbf {e} _{2}\wedge \mathbf {e} _{3})+(p_{1}-q_{1})(\mathbf {e} _{1}\wedge \mathbf {e} _{3})+(p_{1}q_{2}-q_{1}p_{2})(\mathbf {e} _{1}\wedge \mathbf {e} _{2}).}$

Notice that substitution of αp + βq for p multiplies this multivector by a constant. Therefore, the components of p ∧ q are homogeneous coordinates for the plane through the origin of R³.

The set of points x = (x, y, 1) on the line through p and q is the intersection of the plane defined by p ∧ q with the plane E: z = 1. These points satisfy x ∧ p ∧ q = 0, that is,

${\displaystyle \mathbf {x} \wedge \mathbf {p} \wedge \mathbf {q} \ =\ (x\mathbf {e} _{1}+y\mathbf {e} _{2}+\mathbf {e} _{3})\wedge {\big (}(p_{2}-q_{2})(\mathbf {e} _{2}\wedge \mathbf {e} _{3})+(p_{1}-q_{1})(\mathbf {e} _{1}\wedge \mathbf {e} _{3})+(p_{1}q_{2}-q_{1}p_{2})(\mathbf {e} _{1}\wedge \mathbf {e} _{2}){\big )}=0,}$

which simplifies to the equation of a line

${\displaystyle \lambda :x(p_{2}-q_{2})+y(p_{1}-q_{1})+(p_{1}q_{2}-q_{1}p_{2})=0.}$

This equation is satisfied by points x = αp + βq for real values of α and β.

The three components of p ∧ q that define the line λ are called the Grassmann coordinates of the line. Because three homogeneous coordinates define both a point and a line, the geometry of points is said to be dual to the geometry of lines in the projective plane. This is called the principle of duality.

Three dimensional projective space, P³ consists of all lines through the origin of R⁴. Let the three dimensional hyperplane, H: w = 1, be the affine component of projective space defined by the points x = (x, y, z, 1). The multivector p ∧ q ∧ r defines a parallelepiped in R⁴ given by

${\displaystyle \mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} ={\begin{vmatrix}p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\1&1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3}.}$

Notice that substitution of αp + βq + γr for p multiplies this multivector by a constant. Therefore, the components of p ∧ q ∧ r are homogeneous coordinates for the 3-space through the origin of R⁴.

A plane in the affine component H: w = 1 is the set of points x = (x, y, z, 1) in the intersection of H with the 3-space defined by p ∧ q ∧ r. These points satisfy x ∧ p ∧ q ∧ r = 0, that is,

${\displaystyle \mathbf {x} \wedge \mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} =(x\mathbf {e} _{1}+y\mathbf {e} _{2}+z\mathbf {e} _{3}+\mathbf {e} _{4})\wedge \mathbf {p} \wedge \mathbf {q} \wedge \mathbf {r} =0,}$

which simplifies to the equation of a plane

${\displaystyle \lambda :x{\begin{vmatrix}p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}+y{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{3}&q_{3}&r_{3}\\1&1&1\end{vmatrix}}+z{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\1&1&1\end{vmatrix}}+{\begin{vmatrix}p_{1}&q_{1}&r_{1}\\p_{2}&q_{2}&r_{2}\\p_{3}&q_{3}&r_{3}\end{vmatrix}}=0.}$

This equation is satisfied by points x = αp + βq + γr for real values of α, β and γ.

The four components of p ∧ q ∧ r that define the plane λ are called the Grassmann coordinates of the plane. Because four homogeneous coordinates define both a point and a plane in projective space, the geometry of points is dual to the geometry of planes.

A line as the join of two points: In projective space the line λ through two points p and q can be viewed as the intersection of the affine space H: w = 1 with the plane x = αp + βq in R⁴. The multivector p ∧ q provides homogeneous coordinates for the line

${\displaystyle \lambda$ :\mathbf {p} \wedge \mathbf {q} =(p_{1}\mathbf {e} _{1}+p_{2}\mathbf {e} _{2}+p_{3}\mathbf {e} _{3}+\mathbf {e} _{4})\wedge (q_{1}\mathbf {e} _{1}+q_{2}\mathbf {e} _{2}+q_{3}\mathbf {e} _{3}+\mathbf {e} _{4}),}

${\displaystyle \qquad ={\begin{vmatrix}p_{1}&q_{1}\\1&1\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{2}&q_{2}\\1&1\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{3}&q_{3}\\1&1\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}p_{2}&q_{2}\\p_{3}&q_{3}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}+{\begin{vmatrix}p_{3}&q_{3}\\p_{1}&q_{1}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{1}+{\begin{vmatrix}p_{1}&q_{1}\\p_{2}&q_{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.}$

These are known as the Plücker coordinates of the line, though they are also an example of Grassmann coordinates.

A line as the intersection of two planes: A line μ in projective space can also be defined as the set of points x that form the intersection of two planes π and ρ defined by grade three multivectors, so the points x are the solutions to the linear equations

${\displaystyle \mu$ :\mathbf {x} \wedge \pi =0,\mathbf {x} \wedge \rho =0.}

In order to obtain the Plucker coordinates of the line μ, map the multivectors π and ρ to their dual point coordinates using the Hodge star operator,[2]

${\displaystyle \mathbf {e} _{1}={\star }(\mathbf {e} _{2}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}),-\mathbf {e} _{2}={\star }(\mathbf {e} _{1}\wedge \mathbf {e} _{3}\wedge \mathbf {e} _{4}),\mathbf {e} _{3}={\star }(\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{4}),-\mathbf {e} _{4}={\star }(\mathbf {e} _{1}\wedge \mathbf {e} _{2}\wedge \mathbf {e} _{3}),}$

then

${\displaystyle {\star }\pi =\pi _{1}\mathbf {e} _{1}+\pi _{2}\mathbf {e} _{2}+\pi _{3}\mathbf {e} _{3}+\pi _{4}\mathbf {e} _{4},\quad {\star }\rho =\rho _{1}\mathbf {e} _{1}+\rho _{2}\mathbf {e} _{2}+\rho _{3}\mathbf {e} _{3}+\rho _{4}\mathbf {e} _{4}.}$

So, the Plücker coordinates of the line μ are given by

${\displaystyle \mu$ :({\star }\pi )\wedge ({\star }\rho )={\begin{vmatrix}\pi _{1}&\rho _{1}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{2}&\rho _{2}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{3}&\rho _{3}\\\pi _{4}&\rho _{4}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{4}+{\begin{vmatrix}\pi _{2}&\rho _{2}\\\pi _{3}&\rho _{3}\end{vmatrix}}\mathbf {e} _{2}\wedge \mathbf {e} _{3}+{\begin{vmatrix}\pi _{3}&\rho _{3}\\\pi _{1}&\rho _{1}\end{vmatrix}}\mathbf {e} _{3}\wedge \mathbf {e} _{1}+{\begin{vmatrix}\pi _{1}&\rho _{1}\\\pi _{2}&\rho _{2}\end{vmatrix}}\mathbf {e} _{1}\wedge \mathbf {e} _{2}.}

Because the six homogeneous coordinates of a line can be obtained from the join of two points or the intersection of two planes, the line is said to be self dual in projective space.

Orientation defined by an ordered set of vectors.

Reversed orientation corresponds to negating the exterior product.

Geometric interpretation of grade n elements in a real exterior algebra for n = 0 (signed point), 1 (directed line segment, or vector), 2 (oriented plane element), 3 (oriented volume). The exterior product of n vectors can be visualized as any n-dimensional shape (e.g. n-parallelotope, n-ellipsoid); with magnitude (hypervolume), and orientation defined by that on its (n − 1)-dimensional boundary and on which side the interior is.[19][20]

• 0-vectors are scalars;
• 1-vectors are vectors;
• 2-vectors are bivectors;
• (n − 1)-vectors are pseudovectors;
• n-vectors are pseudoscalars.

In the presence of a volume form (such as given an inner product and an orientation), pseudovectors and pseudoscalars can be identified with vectors and scalars, which is routine in vector calculus, but without a volume form this cannot be done without making an arbitrary choice.

In the algebra of physical space (the geometric algebra of Euclidean 3-space, used as a model of (3+1)-spacetime), a sum of a scalar and a vector is called a paravector, and represents a point in spacetime (the vector the space, the scalar the time).

A bivector is an element of the antisymmetric tensor product of a tangent space with itself.

In geometric algebra, also, a bivector is a grade 2 element (a 2-vector) resulting from the wedge product of two vectors, and so it is geometrically an oriented area, in the same way a vector is an oriented line segment. If a and b are two vectors, the bivector a ∧ b has

• a norm which is its area, given by

  ${\displaystyle \left\|\mathbf {a} \wedge \mathbf {b} \right\|=\left\|\mathbf {a} \right\|\,\left\|\mathbf {b} \right\|\,\sin(\phi _{a,b})}$

• a direction: the plane where that area lies on, i.e., the plane determined by a and b, as long as they are linearly independent;
• an orientation (out of two), determined by the order in which the originating vectors are multiplied.

Bivectors are connected to pseudovectors, and are used to represent rotations in geometric algebra.

As bivectors are elements of a vector space Λ²V (where V is a finite-dimensional vector space with dim V = n), it makes sense to define an inner product on this vector space as follows. First, write any element F ∈ Λ²V in terms of a basis (e_i ∧ e_j)_{1 ≤ i < j ≤ n} of Λ²V as

${\displaystyle F=F^{ab}\mathbf {e} _{a}\wedge \mathbf {e} _{b}\quad (1\leq a<b\leq n),}$

where the Einstein summation convention is being used.

Now define a map G : Λ²V × Λ²V → R by insisting that

${\displaystyle G(F,H):=G_{abcd}F^{ab}H^{cd},}$

where ${\displaystyle G_{abcd}}$ are a set of numbers.