Wedge product

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In mathematics, the **exterior product** or **wedge product** of vectors is an algebraic construction used in geometry to study areas, volumes, and their higher-dimensional analogues. The exterior product of two vectors *u* and *v*, denoted by *u* ∧ *v*, is called a bivector and lives in a space called the *exterior square*, a vector space that is distinct from the original space of vectors. The magnitude of *u* ∧ *v* can be interpreted as the area of the parallelogram with sides *u* and *v*, which in three dimensions can also be computed using the cross product of the two vectors. Like the cross product, the exterior product is anticommutative, meaning that *u* ∧ *v* = −(*v* ∧ *u*) for all vectors *u* and *v*, but, unlike the cross product, the exterior product is associative. One way to visualize a bivector is as a family of parallelograms all lying in the same plane, having the same area, and with the same orientation—a choice of clockwise or counterclockwise.

When regarded in this manner, the exterior product of two vectors is called a 2-blade. More generally, the exterior product of any number *k* of vectors can be defined and is sometimes called a *k*-blade. It lives in a space known as the *k*th exterior power. The magnitude of the resulting *k*-blade is the volume of the *k*-dimensional parallelotope whose edges are the given vectors, just as the magnitude of the scalar triple product of vectors in three dimensions gives the volume of the parallelepiped generated by those vectors.

The **exterior algebra**, or **Grassmann algebra** after Hermann Grassmann, is the algebraic system whose product is the exterior product. The exterior algebra provides an algebraic setting in which to answer geometric questions. For instance, blades have a concrete geometric interpretation, and objects in the exterior algebra can be manipulated according to a set of unambiguous rules. The exterior algebra contains objects that are not only *k*-blades, but sums of *k*-blades; such a sum is called a *k*-vector. The *k*-blades, because they are simple products of vectors, are called the simple elements of the algebra. The *rank* of any *k*-vector is defined to be the smallest number of simple elements of which it is a sum. The exterior product extends to the full exterior algebra, so that it makes sense to multiply any two elements of the algebra. Equipped with this product, the exterior algebra is an associative algebra, which means that *α* ∧ (*β* ∧ *γ*) = (*α* ∧ *β*) ∧ *γ* for any elements *α*, *β*, *γ*. The *k*-vectors have degree *k*, meaning that they are sums of products of *k* vectors. When elements of different degrees are multiplied, the degrees add like multiplication of polynomials. This means that the exterior algebra is a graded algebra.

The definition of the exterior algebra makes sense for spaces not just of geometric vectors, but of other vector-like objects such as vector fields or functions. In full generality, the exterior algebra can be defined for modules over a commutative ring, and for other structures of interest in abstract algebra. It is one of these more general constructions where the exterior algebra finds one of its most important applications, where it appears as the algebra of differential forms that is fundamental in areas that use differential geometry. The exterior algebra also has many algebraic properties that make it a convenient tool in algebra itself. The association of the exterior algebra to a vector space is a type of functor on vector spaces, which means that it is compatible in a certain way with linear transformations of vector spaces. The exterior algebra is one example of a bialgebra, meaning that its dual space also possesses a product, and this dual product is compatible with the exterior product. This dual algebra is precisely the algebra of alternating multilinear forms, and the pairing between the exterior algebra and its dual is given by the interior product.

## Motivating examples

### Areas in the plane

The Cartesian plane **R**2 is a real vector space equipped with a basis consisting of a pair of unit vectors

e

1

=

[

1

0

]

,

e

2

=

[

0

1

]

.

{\displaystyle {\mathbf e}\_1 = \begin{bmatrix}1\\0\end{bmatrix},\quad {\mathbf e}\_2 = \begin{bmatrix}0\\1\end{bmatrix}.}

Suppose that

v

=

[

a

b

]

=
a

e

1

b

e

2

,

w

=

[

c

d

]

=
c

e

1

d

e

2

{\displaystyle {\mathbf v} = \begin{bmatrix}a\\b\end{bmatrix} = a {\mathbf e}\_1 + b {\mathbf e}\_2, \quad {\mathbf w} = \begin{bmatrix}c\\d\end{bmatrix} = c {\mathbf e}\_1 + d {\mathbf e}\_2}

are a pair of given vectors in **R**2, written in components. There is a unique parallelogram having **v** and **w** as two of its sides. The *area* of this parallelogram is given by the standard determinant formula:

# Area

det

[

v

w

]

=

det

[

a

c

b

d

]

=

a
d
−
b
c

.

Consider now the exterior product of **v** and **w**:

v

∧

w

=
(
a

e

1

b

e

2

)
∧
(
c

e

1

d

e

2

)

=
a
c

e

1

∧

e

1

a
d

e

1

∧

e

2

b
c

e

2

∧

e

1

b
d

e

2

∧

e

2

=

(

a
d
−
b
c

)

e

1

∧

e

2

{\displaystyle
\begin{align}
{\mathbf v}\wedge {\mathbf w} & = (a{\mathbf e}\_1 + b{\mathbf e}\_2) \wedge (c{\mathbf e}\_1 + d{\mathbf e}\_2) \\
& = ac{\mathbf e}\_1 \wedge {\mathbf e}\_1+ ad{\mathbf e}\_1 \wedge {\mathbf e}\_2+bc{\mathbf e}\_2 \wedge {\mathbf e}\_1+bd{\mathbf e}\_2 \wedge {\mathbf e}\_2 \\
& = \left ( ad - bc \right ){\mathbf e}\_1 \wedge {\mathbf e}\_2
\end{align}
}

where the first step uses the distributive law for the exterior product, and the last uses the fact that the exterior product is alternating, and in particular **e**2 ∧ **e**1 = −(**e**1 ∧ **e**2). (The fact that the exterior product is alternating also forces

e

1

∧

e

1

=

e

2

∧

e

2

=
0

{\displaystyle \mathbf e\_1 \wedge \mathbf e\_1 = \mathbf e\_2 \wedge \mathbf e\_2 = 0 }

.) Note that the coefficient in this last expression is precisely the determinant of the matrix [**v** **w**]. The fact that this may be positive or negative has the intuitive meaning that **v** and **w** may be oriented in a counterclockwise or clockwise sense as the vertices of the parallelogram they define. Such an area is called the *signed area* of the parallelogram: the absolute value of the signed area is the ordinary area, and the sign determines its orientation.

The fact that this coefficient is the signed area is not an accident. In fact, it is relatively easy to see that the exterior product should be related to the signed area if one tries to axiomatize this area as an algebraic construct. In detail, if A(**v**, **w**) denotes the signed area of the parallelogram of which the pair of vectors **v** and **w** form two adjacent sides, then A must satisfy the following properties:

1. A(*r***v**, *s***w**) = *rs*A(**v**, **w**) for any real numbers *r* and *s*, since rescaling either of the sides rescales the area by the same amount (and reversing the direction of one of the sides reverses the orientation of the parallelogram).
2. A(**v**, **v**) = 0, since the area of the degenerate parallelogram determined by **v** (i.e., a line segment) is zero.
3. A(**w**, **v**) = −A(**v**, **w**), since interchanging the roles of **v** and **w** reverses the orientation of the parallelogram.
4. A(**v** + *r***w**, **w**) = A(**v**, **w**) for any real number *r*, since adding a multiple of **w** to **v** affects neither the base nor the height of the parallelogram and consequently preserves its area.
5. A(**e**1, **e**2) = 1, since the area of the unit square is one.

With the exception of the last property, the exterior product of two vectors satisfies the same properties as the area. In a certain sense, the exterior product generalizes the final property by allowing the area of a parallelogram to be compared to that of any "standard" chosen parallelogram in a parallel plane (here, the one with sides **e**1 and **e**2). In other words, the exterior product provides a *basis-independent* formulation of area.

### Cross and triple products

For vectors in **R**3, or any other 3-dimensional inner product space with a fixed orientation, the exterior algebra is closely related to the cross product and triple product. Using the standard basis (**e**1, **e**2, **e**3), the exterior product of a pair of vectors

u

=

u
1

e

1

u
2

e

2

u
3

e

3

{\displaystyle \mathbf{u} = u\_1 \mathbf{e}\_1 + u\_2 \mathbf{e}\_2 + u\_3 \mathbf{e}\_3 }

and

v

=

v
1

e

1

v
2

e

2

v
3

e

3

{\displaystyle \mathbf{v} = v\_1 \mathbf{e}\_1 + v\_2 \mathbf{e}\_2 + v\_3 \mathbf{e}\_3 }

is

u

∧

v

=
(

u
1

v
2

−

u
2

v
1

)
(

e

1

∧

e

2

)
(

u
2

v
3

−

u
3

v
2

)
(

e

2

∧

e

3

)
(

u
3

v
1

−

u
1

v
3

)
(

e

3

∧

e

1

)

{\displaystyle \mathbf{u} \wedge \mathbf{v} = (u\_1 v\_2 - u\_2 v\_1) (\mathbf{e}\_1 \wedge \mathbf{e}\_2) + (u\_2 v\_3 - u\_3 v\_2) (\mathbf{e}\_2 \wedge \mathbf{e}\_3) + (u\_3 v\_1 - u\_1 v\_3) (\mathbf{e}\_3 \wedge \mathbf{e}\_1) }

where (**e**1 ∧ **e**2, **e**2 ∧ **e**3, **e**3 ∧ **e**1) is a basis for the three-dimensional space Λ2(**R**3). The coefficients above are the same as those in the usual definition of the cross product of vectors in three dimensions with a fixed orientation, the only differences being that the exterior product is not an ordinary vector, but instead is a 2-vector, and that the exterior product does not depend on the choice of orientation.

Bringing in a third vector

w

=

w
1

e

1

w
2

e

2

w
3

e

3

,

{\displaystyle \mathbf{w} = w\_1 \mathbf{e}\_1 + w\_2 \mathbf{e}\_2 + w\_3 \mathbf{e}\_3, }

the exterior product of three vectors is

u

∧

v

∧

w

=
(

u
1

v
2

w
3

u
2

v
3

w
1

u
3

v
1

w
2

−

u
1

v
3

w
2

−

u
2

v
1

w
3

−

u
3

v
2

w
1

)
(

e

1

∧

e

2

∧

e

3

)

{\displaystyle \mathbf{u} \wedge \mathbf{v} \wedge \mathbf{w} = (u\_1 v\_2 w\_3 + u\_2 v\_3 w\_1 + u\_3 v\_1 w\_2 - u\_1 v\_3 w\_2 - u\_2 v\_1 w\_3 - u\_3 v\_2 w\_1) (\mathbf{e}\_1 \wedge \mathbf{e}\_2 \wedge \mathbf{e}\_3) }

where **e**1 ∧ **e**2 ∧ **e**3 is the basis vector for the one-dimensional space Λ3(**R**3). The scalar coefficient is the triple product of the three vectors.

The cross product and triple product in three dimensions each admit both geometric and algebraic interpretations. The cross product **u** × **v** can be interpreted as a vector which is perpendicular to both **u** and **v** and whose magnitude is equal to the area of the parallelogram determined by the two vectors. It can also be interpreted as the vector consisting of the minors of the matrix with columns **u** and **v**. The triple product of **u**, **v**, and **w** is geometrically a (signed) volume. Algebraically, it is the determinant of the matrix with columns **u**, **v**, and **w**. The exterior product in three dimensions allows for similar interpretations: It, too, can be identified with oriented areas or volumes spanned by the two or three vectors involved. In fact, in the presence of a positively oriented orthonormal basis, the exterior product generalizes these geometric notions to higher dimensions.

## Formal definitions and algebraic properties

The exterior algebra Λ(*V*) of a vector space *V* over a field *K* is defined as the quotient algebra of the tensor algebra *T*(*V*) by the two-sided ideal *I* generated by all elements of the form *x* ⊗ *x* for *x* ∈ *V* (i.e. all tensors that can be expressed as the tensor product of a vector in *V* by itself). The ideal *I* contains the ideal *J* generated by elements of the form

x
⊗
y
y
⊗
# x
(
x
y
)
⊗
(
x
y
)
−
x
⊗
x
−
y
⊗
y

{\displaystyle x\otimes y + y \otimes x = (x+y)\otimes (x+y) - x\otimes x - y\otimes y }

 and these ideals coincide if (and only if)

char
⁡
(
K
)
≠
2

{\displaystyle \operatorname{char}(K) \ne 2}

:

I
⊇
J
 with equality iff
char
⁡
(
K
)
≠
2

{\displaystyle I \supseteq J \text{ with equality iff } \operatorname{char}(K) \ne 2}

.
We define

⋀

(
V
# )
T
(
V
)

/

I

{\displaystyle {\textstyle\bigwedge}(V) = T(V)/I }

The exterior product ∧ of two elements of Λ(*V*) is the product induced by the tensor product ⊗ of *T*(*V*). That is, if

π
:
T
(
V
)
→

⋀

(
V
# )
T
(
V
)

/

I

{\displaystyle \pi:T(V)\to {\textstyle\bigwedge}(V) = T(V)/I}

is the canonical surjection, and a and b are in Λ(*V*), then there are

α

{\displaystyle \alpha}

 and

β

{\displaystyle \beta}

 in *T*(*V*) such that

# a
π
(
α
)

{\displaystyle a=\pi(\alpha)}

 and

# b
π
(
β
)
,

{\displaystyle b=\pi(\beta),}

 and

a
∧
# b
π
(
α
⊗
β
)
.

{\displaystyle a\wedge b = \pi(\alpha\otimes\beta).}

It results from the definition of a quotient algebra that the value of

a
∧
b

{\displaystyle a\wedge b}

 does not depend on a particular choice of

α

{\displaystyle \alpha}

 and

β

{\displaystyle \beta}

. We have (in all characteristics)

x
⊗
# y
−
y
⊗
x
mod
I

{\displaystyle x \otimes y = - y \otimes x \bmod I}

.

As *T*0 = *K*, *T*1 = *V*, and

(

T
0

(
V
)
⊕

T
1

(
V
)

)

∩
# I
{
0
}

{\displaystyle \left(T^0(V)\oplus T^1(V)\right)\cap I= \{ 0 \} }

, the inclusions of *K* and *V* in *T*(*V*) induce injections of *K* and *V* into Λ(*V*). These injections are commonly considered as inclusions, and called *natural embeddings*, *natural injections* or *natural inclusions*. The word *canonical* is also commonly used in place of *natural*.

### Alternating product

The exterior product is by construction *alternating* on elements of *V*, which means that *x* ∧ *x* = 0 for all *x* ∈ *V*, by the above construction. It follows that the product is also anticommutative on elements of *V*, for supposing that *x*, *y* ∈ *V*,

# 0
(
x
y
)
∧
(
x
y
# )
x
∧
x
x
∧
y
y
∧
x
y
∧
# y
x
∧
y
y
∧
x

{\displaystyle 0 = (x+y)\wedge (x+y) = x\wedge x + x\wedge y + y\wedge x + y\wedge y = x\wedge y + y\wedge x}

hence

x
∧
# y
−
(
y
∧
x
)
.

{\displaystyle x \wedge y = - ( y \wedge x ) .}

More generally, if *σ* is a permutation of the integers [1, ..., *k*], and *x*1, *x*2, ..., *x**k* are elements of *V*, it follows that

x

σ
(
1
)

∧

x

σ
(
2
)

∧
⋯
∧

x

σ
(
k
)

=
sgn
⁡
(
σ
)

x
1

∧

x
2

∧
⋯
∧

x
k

,

{\displaystyle x\_{\sigma(1)}\wedge x\_{\sigma(2)}\wedge\cdots\wedge x\_{\sigma(k)} = \operatorname{sgn}(\sigma)x\_1\wedge x\_2\wedge\cdots \wedge x\_k,}

where sgn(*σ*) is the signature of the permutation *σ*.

In particular, if *x**i* = *x**j* for some *i* ≠ *j*, then the following generalization of the alternating property also holds:

x

1

∧

x

2

∧
⋯
∧

x

k

=

{\displaystyle x\_{1}\wedge x\_{2}\wedge\cdots\wedge x\_{k} = 0.}

### Exterior power

The *k*th **exterior power** of *V*, denoted Λ*k*(*V*), is the vector subspace of Λ(*V*) spanned by elements of the form

x
1

∧

x
2

∧
⋯
∧

x
k

,

x
i

∈
V
,
# i
1
,
2
,
…
,
k
.

{\displaystyle x\_1\wedge x\_2\wedge\cdots\wedge x\_k,\quad x\_i\in V, i=1,2,\ldots, k.}

If *α* ∈ Λ*k*(*V*), then *α* is said to be a ***k*-vector**. If, furthermore, *α* can be expressed as an exterior product of *k* elements of *V*, then *α* is said to be **decomposable**. Although decomposable *k*-vectors span Λ*k*(*V*), not every element of Λ*k*(*V*) is decomposable. For example, in **R**4, the following 2-vector is not decomposable:

# α

e
1

∧

e
2

e
3

∧

e
4

.

{\displaystyle \alpha = e\_1\wedge e\_2 + e\_3\wedge e\_4.}

(This is a symplectic form, since *α* ∧ *α* ≠ 0.)

#### Basis and dimension

If the dimension of V is n and  { *e*1, ..., *e**n* }  is a basis for V, then the set

{

e

i
1

∧

e

i
2

∧
⋯
∧

e

i
k

# k
1
,
2
,
⋯
n

 and

1
≤

i
1

<

i
2

<
⋯
<

i
k

≤
n

}

{\displaystyle \{\,e\_{i\_1}\wedge e\_{i\_2}\wedge\cdots\wedge e\_{i\_k} ~ \big| ~~ k = 1,2,\cdots n ~~\text{ and }~~ 1 \le i\_1 < i\_2 < \cdots < i\_k \le n \,\}}

is a basis for Λ*k*(*V*). The reason is the following: given any exterior product of the form

v
1

∧
⋯
∧

v
k

,

{\displaystyle v\_1\wedge\cdots\wedge v\_k ,}

every vector vj can be written as a linear combination of the basis vectors ei; using the bilinearity of the exterior product, this can be expanded to a linear combination of exterior products of those basis vectors. Any exterior product in which the same basis vector appears more than once is zero; any exterior product in which the basis vectors do not appear in the proper order can be reordered, changing the sign whenever two basis vectors change places. In general, the resulting coefficients of the basis k-vectors can be computed as the minors of the matrix that describes the vectors vj in terms of the basis ei.

By counting the basis elements, the dimension of Λ*k*(*V*) is equal to a binomial coefficient:

dim
⁡

⋀

k

(
V
# )

(

n
k

)

.

{\displaystyle \dim {\textstyle\bigwedge}^k(V) = \binom{n}{k}\,.}

where n is the dimension of the *vectors*, and k is the number of vectors in the product. The binomial coefficient produces the correct result, even for exceptional cases; in particular, Λ*k*(*V*) = { 0 } for  *k* > *n* .

Any element of the exterior algebra can be written as a sum of k-vectors. Hence, as a vector space the exterior algebra is a direct sum

⋀

(
V
# )

⋀

0

(
V
)
⊕

⋀

1

(
V
)
⊕

⋀

2

(
V
)
⊕
⋯
⊕

⋀

n

(
V
)

{\displaystyle {\textstyle\bigwedge}(V) = {\textstyle\bigwedge}^0(V)\oplus {\textstyle\bigwedge}^1(V) \oplus {\textstyle\bigwedge}^2(V) \oplus \cdots \oplus {\textstyle\bigwedge}^n(V)}

(where by convention  Λ0(*V*) = *K* , the field underlying V, and    Λ1(*V*) = *V* ), and therefore its dimension is equal to the sum of the binomial coefficients, which is 2n .

#### Rank of a *k*-vector

If *α* ∈ Λ*k*(*V*), then it is possible to express *α* as a linear combination of decomposable *k*-vectors:

# α

α

(
1
)

α

(
2
)

⋯

α

(
s
)

{\displaystyle \alpha = \alpha^{(1)} + \alpha^{(2)} + \cdots + \alpha^{(s)}}

where each *α*(*i*) is decomposable, say

α

(
i
)

=

α
1

(
i
)

∧
⋯
∧

α
k

(
i
)

,

# i
1
,
2
,
…
,
s
.

{\displaystyle \alpha^{(i)} = \alpha^{(i)}\_1\wedge\cdots\wedge\alpha^{(i)}\_k,\quad i=1,2,\ldots, s.}

The **rank** of the *k*-vector *α* is the minimal number of decomposable *k*-vectors in such an expansion of *α*. This is similar to the notion of tensor rank.

Rank is particularly important in the study of 2-vectors . The rank of a 2-vector *α* can be identified with half the rank of the matrix of coefficients of *α* in a basis. Thus if *e**i* is a basis for *V*, then *α* can be expressed uniquely as

# α

∑

i
,
j

a

i
j

e
i

∧

e
j

{\displaystyle \alpha = \sum\_{i,j}a\_{ij}e\_i\wedge e\_j}

where *a**ij* = −*a**ji* (the matrix of coefficients is skew-symmetric). The rank of the matrix *a**ij* is therefore even, and is twice the rank of the form *α*.

In characteristic 0, the 2-vector *α* has rank *p* if and only if

α
∧
⋯
∧
α

⏟

p

≠
0

{\displaystyle \underset{p}{\underbrace{\alpha\wedge\cdots\wedge\alpha}} \neq 0 \ }

 and

α
∧
⋯
∧
α

⏟

p
1

=

{\displaystyle \ \underset{p+1}{\underbrace{\alpha\wedge\cdots\wedge\alpha}} = 0.}

### Graded structure

The exterior product of a *k*-vector with a *p*-vector is a (*k* + *p*)-vector, once again invoking bilinearity. As a consequence, the direct sum decomposition of the preceding section

⋀

(
V
# )

⋀

0

(
V
)
⊕

⋀

1

(
V
)
⊕

⋀

2

(
V
)
⊕
⋯
⊕

⋀

n

(
V
)

{\displaystyle {\textstyle\bigwedge}(V) = {\textstyle\bigwedge}^{\!0}(V)\oplus {\textstyle\bigwedge}^{\!1}(V) \oplus {\textstyle\bigwedge}^{\!2}(V) \oplus\cdots\oplus {\textstyle\bigwedge}^{\!n}(V)}

gives the exterior algebra the additional structure of a graded algebra, that is

⋀

k

(
V
)
∧

⋀

p

(
V
)
⊂

⋀

k
p

(
V
)
.

{\displaystyle {\textstyle\bigwedge}^k(V)\wedge{\textstyle\bigwedge}^p(V)\sub {\textstyle\bigwedge}^{k+p}(V).}

Moreover, if *K* is the base field, we have

⋀

0

(
V
# )
K

{\displaystyle {\textstyle\bigwedge}^{\!0}(V) = K}

 and

⋀

1

(
V
# )
V
.

{\displaystyle {\textstyle\bigwedge}^{\!1}(V) = V.}

The exterior product is graded anticommutative, meaning that if *α* ∈ Λ*k*(*V*) and *β* ∈ Λ*p*(*V*), then

α
∧
# β
(
−
1

)

k
p

β
∧
α
.

{\displaystyle \alpha\wedge\beta = (-1)^{kp}\beta\wedge\alpha.}

In addition to studying the graded structure on the exterior algebra, Bourbaki (1989) studies additional graded structures on exterior algebras, such as those on the exterior algebra of a graded module (a module that already carries its own gradation).

### Universal property

Let *V* be a vector space over the field *K*. Informally, multiplication in Λ(*V*) is performed by manipulating symbols and imposing a distributive law, an associative law, and using the identity *v* ∧ *v* = 0 for *v* ∈ *V*. Formally, Λ(*V*) is the "most general" algebra in which these rules hold for the multiplication, in the sense that any unital associative *K*-algebra containing *V* with alternating multiplication on *V* must contain a homomorphic image of Λ(*V*). In other words, the exterior algebra has the following universal property:

Given any unital associative *K*-algebra *A* and any *K*-linear map *j* : *V* → *A* such that *j*(*v*)*j*(*v*) = 0 for every *v* in *V*, then there exists *precisely one* unital algebra homomorphism *f* : Λ(*V*) → *A* such that *j*(*v*) = *f*(*i*(*v*)) for all *v* in *V* (here *i* is the natural inclusion of *V* in Λ(*V*), see above).

To construct the most general algebra that contains *V* and whose multiplication is alternating on *V*, it is natural to start with the most general associative algebra that contains *V*, the tensor algebra *T*(*V*), and then enforce the alternating property by taking a suitable quotient. We thus take the two-sided ideal *I* in *T*(*V*) generated by all elements of the form *v* ⊗ *v* for *v* in *V*, and define Λ(*V*) as the quotient

⋀

(
V
# )
T
(
V
)

/

I

{\displaystyle {\textstyle\bigwedge}(V) = T(V)/I\ }

(and use ∧ as the symbol for multiplication in Λ(*V*)). It is then straightforward to show that Λ(*V*) contains *V* and satisfies the above universal property.

As a consequence of this construction, the operation of assigning to a vector space *V* its exterior algebra Λ(*V*) is a functor from the category of vector spaces to the category of algebras.

Rather than defining Λ(*V*) first and then identifying the exterior powers Λ*k*(*V*) as certain subspaces, one may alternatively define the spaces Λ*k*(*V*) first and then combine them to form the algebra Λ(*V*). This approach is often used in differential geometry and is described in the next section.

### Generalizations

Given a commutative ring *R* and an *R*-module *M*, we can define the exterior algebra Λ(*M*) just as above, as a suitable quotient of the tensor algebra **T**(*M*). It will satisfy the analogous universal property. Many of the properties of Λ(*M*) also require that *M* be a projective module. Where finite dimensionality is used, the properties further require that *M* be finitely generated and projective. Generalizations to the most common situations can be found in Bourbaki (1989).

Exterior algebras of vector bundles are frequently considered in geometry and topology. There are no essential differences between the algebraic properties of the exterior algebra of finite-dimensional vector bundles and those of the exterior algebra of finitely generated projective modules, by the Serre–Swan theorem. More general exterior algebras can be defined for sheaves of modules.

## Duality

### Alternating operators

Given two vector spaces *V* and *X* and a natural number *k*, an **alternating operator** from *V**k* to *X* is a multilinear map

f
:

V
k

→
X

{\displaystyle f\colon V^k \to X}

such that whenever *v*1, ..., *v**k* are linearly dependent vectors in *V*, then

f
(

v
1

,
…
,

v
k

# )

{\displaystyle f(v\_1,\ldots, v\_k) = 0.}

The map

w
:

V
k

→

⋀

k

(
V
)

{\displaystyle w\colon V^k \to {\textstyle\bigwedge}^{\!k}(V)}

which associates to *k* vectors from *V* their exterior product, i.e. their corresponding *k*-vector, is also alternating. In fact, this map is the "most general" alternating operator defined on *V**k*; given any other alternating operator *f* : *V**k* → *X*, there exists a unique linear map *φ* : Λ*k*(*V*) → *X* with *f* = *φ* ∘ *w*. This universal property characterizes the space Λ*k*(*V*) and can serve as its definition.

### Alternating multilinear forms

The above discussion specializes to the case when *X* = *K*, the base field. In this case an alternating multilinear function

f
:

V
k

→
K

{\displaystyle f : V^k \to K\ }

is called an **alternating multilinear form**. The set of all alternating multilinear forms is a vector space, as the sum of two such maps, or the product of such a map with a scalar, is again alternating. By the universal property of the exterior power, the space of alternating forms of degree *k* on *V* is naturally isomorphic with the dual vector space (Λ*k**V*)∗. If *V* is finite-dimensional, then the latter is naturally isomorphic to Λ*k*(*V*∗). In particular, the dimension of the space of alternating maps from *V**k* to *K* is *n* choose *k*.

Under this identification, the exterior product takes a concrete form: it produces a new anti-symmetric map from two given ones. Suppose *ω* : *V**k* → *K* and *η* : *V**m* → *K* are two anti-symmetric maps. As in the case of tensor products of multilinear maps, the number of variables of their exterior product is the sum of the numbers of their variables. It is defined as follows:

ω
∧
# η

(
k
m
)
!

k
!

m
!

Alt
⁡
(
ω
⊗
η
)
,

{\displaystyle \omega\wedge\eta=\frac{(k+m)!}{k!\,m!}\operatorname{Alt}(\omega\otimes\eta),}

where the alternation Alt of a multilinear map is defined to be the average of the sign-adjusted values over all the permutations of its variables:

Alt
⁡
(
ω
)
(

x
1

,
…
,

x
k

# )

1

k
!

∑

σ
∈

S
k

sgn
⁡
(
σ
)

ω
(

x

σ
(
1
)

,
…
,

x

σ
(
k
)

)
.

{\displaystyle \operatorname{Alt}(\omega)(x\_1,\ldots,x\_k)=\frac{1}{k!}\sum\_{\sigma\in S\_k}\operatorname{sgn}(\sigma)\,\omega(x\_{\sigma(1)},\ldots,x\_{\sigma(k)}).}

This definition of the exterior product is well-defined even if the field *K* has finite characteristic, if one considers an equivalent version of the above that does not use factorials or any constants:

ω
∧
η
(

x
1

,
…
,

x

k
m

)

=

∑

σ
∈
S

h

k
,
m

sgn
⁡
(
σ
)

ω
(

x

σ
(
1
)

,
…
,

x

σ
(
k
)

)
η
(

x

σ
(
k
1
)

,
…
,

x

σ
(
k
m
)

)
,

{\displaystyle {\omega \wedge \eta(x\_1,\ldots,x\_{k+m})} = \sum\_{\sigma \in Sh\_{k,m}} \operatorname{sgn}(\sigma)\,\omega(x\_{\sigma(1)}, \ldots, x\_{\sigma(k)}) \eta(x\_{\sigma(k+1)}, \ldots, x\_{\sigma(k+m)}),}

where here Sh*k*,*m* ⊂ *S**k*+*m* is the subset of (*k*,*m*) shuffles: permutations *σ* of the set {1, 2, ..., *k* + *m*} such that *σ*(1) < *σ*(2) < ... < *σ*(*k*), and *σ*(*k* + 1) < *σ*(*k* + 2) < ... < *σ*(*k* + *m*).

### Bialgebra structure

There is a correspondence between the graded dual of the graded algebra Λ(*V*) and alternating multilinear forms on *V*. The exterior algebra (as well as the symmetric algebra) inherits a bialgebra structure, and, indeed, a Hopf algebra structure, from the tensor algebra. See the article on tensor algebras for a detailed treatment of the topic.

The exterior product of multilinear forms defined above is dual to a coproduct defined on Λ(*V*), giving the structure of a coalgebra. The **coproduct** is a linear function Δ : Λ(*V*) → Λ(*V*) ⊗ Λ(*V*) which is given by

Δ
(
v
# )
1
⊗
v
v
⊗
1

{\displaystyle \Delta(v) = 1 \otimes v + v \otimes 1}

on elements *v*∈*V*. The symbol 1 stands for the unit element of the field *K*. Recall that *K* ⊂ Λ(*V*), so that the above really does lie in Λ(*V*) ⊗ Λ(*V*). This definition of the coproduct is extended to the full space Λ(*V*) by (linear) homomorphism.
The correct form of this homomorphism is not what one might naively write, but has to be the one carefully defined in the coalgebra article. In this case, one obtains

Δ
(
v
∧
w
# )
1
⊗
(
v
∧
w
)
v
⊗
w
−
w
⊗
v
(
v
∧
w
)
⊗

{\displaystyle
\Delta(v \wedge w) = 1 \otimes (v \wedge w) + v \otimes w - w \otimes v + (v \wedge w) \otimes 1.
}

Expanding this out in detail, one obtains the following expression on decomposable elements:

Δ
(

x
1

∧
⋯
∧

x
k

# p
0

k

∑

σ
∈
S
h
(
p
1
,
k
−
p
)

sgn
⁡
(
σ
)
(

x

σ
(
0
)

∧
⋯
∧

x

σ
(
p
)

)
⊗
(

x

σ
(
p
1
)

∧
⋯
∧

x

σ
(
k
)

)
.

{\displaystyle \Delta(x\_1\wedge\cdots\wedge x\_k) = \sum\_{p=0}^k \; \sum\_{\sigma\in Sh(p+1,k-p)} \; \operatorname{sgn}(\sigma) (x\_{\sigma(0)}\wedge\cdots\wedge x\_{\sigma(p)})\otimes (x\_{\sigma(p+1)}\wedge\cdots\wedge x\_{\sigma(k)}).}

where the second summation is taken over all (*p*+1, *k*−*p*)-shuffles. The above is written with a notational trick, to keep track of the field element 1: the trick is to write

x
0

=
1

{\displaystyle x\_0=1}

, and this is shuffled into various locations during the expansion of the sum over shuffles. The shuffle follows directly from the first axiom of a co-algebra: the relative order of the elements

x
k

{\displaystyle x\_k}

 is *preserved* in the riffle shuffle: the riffle shuffle merely splits the ordered sequence into two ordered sequences, one on the left, and one on the right.

Observe that the coproduct preserves the grading of the algebra. Extending to the full space Λ(*V*), one has

Δ
:

⋀

k

(
V
)
→

⨁

# p
0

k

⋀

p

(
V
)
⊗

⋀

k
−
p

(
V
)

{\displaystyle \Delta:{\textstyle\bigwedge}^k(V) \to \bigoplus\_{p=0}^k {\textstyle\bigwedge}^p(V) \otimes {\textstyle\bigwedge}^{k-p}(V)}

The tensor symbol ⊗ used in this section should be understood with some caution: it is *not* the same tensor symbol as the one being used in the definition of the alternating product. Intuitively, it is perhaps easiest to think it as just another, but different, tensor product: it is still (bi-)linear, as tensor products should be, but it is the product that is appropriate for the definition of a bialgebra, that is, for creating the object Λ(*V*) ⊗ Λ(*V*). Any lingering doubt can be shaken by pondering the equalities (1 ⊗ *v*) ∧ (1 ⊗ *w*) = 1 ⊗ (*v* ∧ *w*) and (*v* ⊗ 1) ∧ (1 ⊗ *w*) = *v* ⊗ *w*, which follow from the definition of the coalgebra, as opposed to naive manipulations involving the tensor and wedge symbols. This distinction is developed in greater detail in the article on tensor algebras. Here, there is much less of a problem, in that the alternating product Λ clearly corresponds to multiplication in the bialgebra, leaving the symbol ⊗ free for use in the definition of the bialgebra. In practice, this presents no particular problem, as long as one avoids the fatal trap of replacing alternating sums of ⊗ by the wedge symbol, with one exception. One can construct an alternating product from ⊗, with the understanding that it works in a different space. Immediately below, an example is given: the alternating product for the *dual space* can be given in terms of the coproduct. The construction of the bialgebra here parallels the construction in the tensor algebra article almost exactly, except for the need to correctly track the alternating signs for the exterior algebra.

In terms of the coproduct, the exterior product on the dual space is just the graded dual of the coproduct:

(
α
∧
β
)
(

x
1

∧
⋯
∧

x
k

# )
(
α
⊗
β
)

(

Δ
(

x
1

∧
⋯
∧

x
k

)

)

{\displaystyle (\alpha\wedge\beta)(x\_1\wedge\cdots\wedge x\_k) = (\alpha\otimes\beta)\left(\Delta(x\_1\wedge\cdots\wedge x\_k)\right)}

where the tensor product on the right-hand side is of multilinear linear maps (extended by zero on elements of incompatible homogeneous degree: more precisely, *α* ∧ *β* = *ε* ∘ (*α* ⊗ *β*) ∘ Δ, where *ε* is the counit, as defined presently).

The **counit** is the homomorphism *ε* : Λ(*V*) → *K* that returns the 0-graded component of its argument. The coproduct and counit, along with the exterior product, define the structure of a bialgebra on the exterior algebra.

With an **antipode** defined on homogeneous elements by

S
(
x
# )
(
−
1

)

(

deg

x

1

2

)

x

{\displaystyle S(x)=(-1)^{\binom{\text{deg}\, x\, +1}{2}}x}

, the exterior algebra is furthermore a Hopf algebra.

### Interior product

See also: Interior product
Suppose that *V* is finite-dimensional. If *V*∗ denotes the dual space to the vector space *V*, then for each *α* ∈ *V*∗, it is possible to define an antiderivation on the algebra Λ(*V*),

i
α

:

⋀

k

V
→

⋀

k
−
1

V
.

{\displaystyle i\_\alpha:{\textstyle\bigwedge}^k V\rightarrow {\textstyle\bigwedge}^{k-1}V.}

This derivation is called the **interior product** with *α*, or sometimes the **insertion operator**, or **contraction** by *α*.

Suppose that **w** ∈ Λ*k**V*. Then **w** is a multilinear mapping of *V*∗ to *K*, so it is defined by its values on the *k*-fold Cartesian product *V*∗ × *V*∗ × ... × *V*∗. If *u*1, *u*2, ..., *u**k*−1 are *k* − 1 elements of *V*∗, then define

(

i
α

w

)
(

u
1

,

u
2

,
…
,

u

k
−
1

# )

w

(
α
,

u
1

,

u
2

,
…
,

u

k
−
1

)
.

{\displaystyle (i\_\alpha {\mathbf w})(u\_1,u\_2,\ldots,u\_{k-1})={\mathbf w}(\alpha,u\_1,u\_2,\ldots, u\_{k-1}).}

Additionally, let *i**α**f* = 0 whenever *f* is a pure scalar (i.e., belonging to Λ0*V*).

#### Axiomatic characterization and properties

The interior product satisfies the following properties:

1. For each *k* and each *α* ∈ *V*∗,

i
α

:

⋀

k

V
→

⋀

k
−
1

V
.

{\displaystyle i\_\alpha:{\textstyle\bigwedge}^k V\rightarrow {\textstyle\bigwedge}^{k-1}V.}

(By convention, Λ−1*V* = {0}.)
2. If *v* is an element of *V* (= Λ1*V*), then *i**α**v* = *α*(*v*) is the dual pairing between elements of *V* and elements of *V*∗.
3. For each *α* ∈ *V*∗, *i**α* is a graded derivation of degree −1:

i
α

(
a
∧
b
# )
(

i
α

a
)
∧
b
(
−
1

)

deg
⁡
a

a
∧
(

i
α

b
)
.

{\displaystyle i\_\alpha (a\wedge b) = (i\_\alpha a)\wedge b + (-1)^{\deg a}a\wedge (i\_\alpha b).}

These three properties are sufficient to characterize the interior product as well as define it in the general infinite-dimensional case.

Further properties of the interior product include:

* i
α

∘

i
α

=

{\displaystyle i\_\alpha\circ i\_\alpha = 0.}
* i
α

∘

i
β

=
−

i
β

∘

i
α

.

{\displaystyle i\_\alpha\circ i\_\beta = -i\_\beta\circ i\_\alpha.}

### Hodge duality

Main articles: Hodge star operator
Suppose that *V* has finite dimension *n*. Then the interior product induces a canonical isomorphism of vector spaces

⋀

k

(

V
∗

)
⊗

⋀

n

(
V
)
→

⋀

n
−
k

(
V
)

{\displaystyle {\textstyle\bigwedge}^k(V^\*) \otimes {\textstyle\bigwedge}^n(V) \to {\textstyle\bigwedge}^{n-k}(V) }

by the recursive definition

i

α
∧
β

=

i
β

∘

i
α

.

{\displaystyle i\_{\alpha \wedge \beta} = i\_\beta \circ i\_\alpha .}

In the geometrical setting, a non-zero element of the top exterior power Λ*n*(*V*) (which is a one-dimensional vector space) is sometimes called a **volume form** (or **orientation form**, although this term may sometimes lead to ambiguity). The name orientation form comes from the fact that a choice of preferred top element determines an orientation of the whole exterior algebra, since it is tantamount to fixing an ordered basis of the vector space. Relative to the preferred volume form *σ*, the isomorphism between an element

α
∈

∧
k

(

V
∗

)

{\displaystyle \alpha \in \wedge^k(V^\*)}

and its Hodge dual is given explicitly by

⋀

k

(

V
∗

)
→

⋀

n
−
k

(
V
)
:
α
↦

i
α

σ
.

{\displaystyle {\textstyle\bigwedge}^k(V^\*) \to {\textstyle\bigwedge}^{n-k}(V) : \alpha \mapsto i\_\alpha\sigma .}

If, in addition to a volume form, the vector space *V* is equipped with an inner product identifying *V* with *V*∗, then the resulting isomorphism is called the **Hodge star operator**, which maps an element to its **Hodge dual**:

⋆
:

⋀

k

(
V
)
→

⋀

n
−
k

(
V
)
.

{\displaystyle \star : {\textstyle\bigwedge}^k(V) \rightarrow {\textstyle\bigwedge}^{n-k}(V) .}

The composition of

⋆

{\displaystyle \star}

 with itself maps Λ*k*(*V*) → Λ*k*(*V*) and is always a scalar multiple of the identity map. In most applications, the volume form is compatible with the inner product in the sense that it is an exterior product of an orthonormal basis of *V*. In this case,

⋆
∘
⋆
:

⋀

k

(
V
)
→

⋀

k

(
V
# )
(
−
1

)

k
(
n
−
k
)
q

i
d

{\displaystyle \star \circ \star : {\textstyle\bigwedge}^k(V) \to {\textstyle\bigwedge}^k(V) = (-1)^{k(n-k) + q}\mathrm{id}}

where id is the identity mapping, and the inner product has metric signature (*p*, *q*) — *p* pluses and *q* minuses.

### Inner product

For *V* a finite-dimensional space, an inner product on *V* defines an isomorphism of *V* with *V*∗, and so also an isomorphism of Λ*k**V* with (Λ*k**V*)∗. The pairing between these two spaces also takes the form of an inner product. On decomposable *k*-vectors,

⟨

v
1

∧
⋯
∧

v
k

,

w
1

∧
⋯
∧

w
k

⟩

=
det
(
⟨

v
i

,

w
j

⟩
)
,

{\displaystyle \left\langle v\_1\wedge\cdots\wedge v\_k, w\_1\wedge\cdots\wedge w\_k\right\rangle = \det(\langle v\_i,w\_j\rangle),}

the determinant of the matrix of inner products. In the special case *v**i* = *w**i*, the inner product is the square norm of the *k*-vector, given by the determinant of the Gramian matrix (⟨*v**i*, *v**j*⟩). This is then extended bilinearly (or sesquilinearly in the complex case) to a non-degenerate inner product on Λ*k**V*. If *e**i*, *i* = 1, 2, ..., *n*, form an orthonormal basis of *V*, then the vectors of the form

e

i
1

∧
⋯
∧

e

i
k

,

i
1

<
⋯
<

i
k

,

{\displaystyle e\_{i\_1}\wedge\cdots\wedge e\_{i\_k},\quad i\_1 < \cdots < i\_k,}

constitute an orthonormal basis for Λ*k*(*V*).

It is not hard to show that for vectors *v1,v2,...vk in Rn*, *‖v1∧v2∧...∧vk‖* is the volume of the parallelopiped spanned by these vectors.

With respect to the inner product, exterior multiplication and the interior product are mutually adjoint. Specifically, for **v** ∈ Λ*k*−1(*V*), **w** ∈ Λ*k*(*V*), and *x* ∈ *V*,

⟨
x
∧

v

,

w

# ⟩
⟨

v

,

i

x
♭

w

⟩

{\displaystyle \langle x\wedge\mathbf{v}, \mathbf{w}\rangle = \langle \mathbf{v}, i\_{x^\flat}\mathbf{w}\rangle}

where *x*♭ ∈ *V*∗ is the linear functional defined by

x
♭

(
y
# )
⟨
x
,
y
⟩

{\displaystyle x^\flat(y) = \langle x, y\rangle}

for all *y* ∈ *V*. This property completely characterizes the inner product on the exterior algebra.

Indeed, more generally for **v** ∈ Λ*k*−*l*(*V*), **w** ∈ Λ*k*(*V*), and **x** ∈ Λ*l*(*V*), iteration of the above adjoint properties gives

⟨

x

∧

v

,

w

# ⟩
⟨

v

,

i

x

♭

w

⟩

{\displaystyle \langle \mathbf{x} \wedge\mathbf{v}, \mathbf{w}\rangle = \langle \mathbf{v}, i\_{\mathbf{x}^\flat}\mathbf{w}\rangle}

where now **x**♭ ∈ Λ*l*(*V*∗) ≃ (Λ*l*(*V*))∗ is the dual *l*-vector defined by

x

♭

(

y

# )
⟨

x

,

y

⟩

{\displaystyle \mathbf{x}^\flat(\mathbf{y}) = \langle \mathbf{x}, \mathbf{y}\rangle}

for all **y** ∈ Λ*l*(*V*).

## Functoriality

Suppose that *V* and *W* are a pair of vector spaces and *f* : *V* → *W* is a linear map. Then, by the universal property, there exists a unique homomorphism of graded algebras

⋀

(
f
)
:

⋀

(
V
)
→

⋀

(
W
)

{\displaystyle {\textstyle\bigwedge}(f) : {\textstyle\bigwedge}(V)\rightarrow {\textstyle\bigwedge}(W)}

such that

⋀

(
f
)

⋀

1

(
V
)

=
f
:
# V

⋀

1

(
V
)
→
# W

⋀

1

(
W
)
.

{\displaystyle {\textstyle\bigwedge}(f)\left|\_{{\textstyle\bigwedge}^1(V)}\right. = f : V={\textstyle\bigwedge}^1(V)\rightarrow W={\textstyle\bigwedge}^1(W).}

In particular, Λ(*f*) preserves homogeneous degree. The *k*-graded components of Λ(*f*) are given on decomposable elements by

⋀

(
f
)
(

x
1

∧
⋯
∧

x
k

# )
f
(

x
1

)
∧
⋯
∧
f
(

x
k

)
.

{\displaystyle {\textstyle\bigwedge}(f)(x\_1\wedge \cdots \wedge x\_k) = f(x\_1)\wedge\cdots\wedge f(x\_k).}

Let

⋀

k

(
f
# )

⋀

(
f
)

⋀

k

(
V
)

:

⋀

k

(
V
)
→

⋀

k

(
W
)
.

{\displaystyle {\textstyle\bigwedge}^k(f) = {\textstyle\bigwedge} (f)\left|\_{{\textstyle\bigwedge}^k(V)}\right. : {\textstyle\bigwedge}^k(V) \rightarrow {\textstyle\bigwedge}^k(W).}

The components of the transformation Λ*k*(*f*) relative to a basis of *V* and *W* is the matrix of *k* × *k* minors of *f*. In particular, if *V* = *W* and *V* is of finite dimension *n*, then Λ*n*(*f*) is a mapping of a one-dimensional vector space Λ*n**V* to itself, and is therefore given by a scalar: the determinant of *f*.

### Exactness

If

0
→
U
→
V
→
W
→
0

{\displaystyle 0 \to U \to V \to W \to 0}

 is a short exact sequence of vector spaces, then

0
→

⋀

1

(
U
)
∧

⋀

(
V
)
→

⋀

(
V
)
→

⋀

(
W
)
→
0

{\displaystyle 0 \to {\textstyle\bigwedge}^1(U) \wedge {\textstyle\bigwedge}(V) \to {\textstyle\bigwedge}(V) \to {\textstyle\bigwedge}(W) \to 0}

is an exact sequence of graded vector spaces, as is

0
→

⋀

(
U
)
→

⋀

(
V
)
.

{\displaystyle 0 \to {\textstyle\bigwedge}(U) \to {\textstyle\bigwedge}(V).}

### Direct sums

In particular, the exterior algebra of a direct sum is isomorphic to the tensor product of the exterior algebras:

⋀

(
V
⊕
W
)
≅

⋀

(
V
)
⊗

⋀

(
W
)
.

{\displaystyle {\textstyle\bigwedge}(V\oplus W)\cong{\textstyle\bigwedge}(V)\otimes{\textstyle\bigwedge}(W).}

This is a graded isomorphism; i.e.,

⋀

k

(
V
⊕
W
)
≅

⨁

p
# q
k

⋀

p

(
V
)
⊗

⋀

q

(
W
)
.

{\displaystyle {\textstyle\bigwedge}^k(V\oplus W)\cong\bigoplus\_{p+q=k} {\textstyle\bigwedge}^p(V)\otimes{\textstyle\bigwedge}^q(W).}

Slightly more generally, if

0
→
U
→
V
→
W
→
0

{\displaystyle 0 \to U \to V \to W \to 0}

 is a short exact sequence of vector spaces, then Λ*k(V)* has a filtration

# 0

F
0

⊆

F
1

⊆
⋯
⊆

F
k

⊆

F

k
1

=

⋀

k

(
V
)

{\displaystyle 0 = F^0 \subseteq F^1 \subseteq \cdots \subseteq F^k \subseteq F^{k+1} = {\textstyle\bigwedge}^k(V)}

with quotients

F

p
1

/

F
p

=

⋀

k
−
p

(
U
)
⊗

⋀

p

(
W
)
.

{\displaystyle F^{p+1}/F^p = {\textstyle\bigwedge}^{k-p}(U) \otimes {\textstyle\bigwedge}^p(W).}

In particular, if *U* is 1-dimensional then

0
→
U
⊗

⋀

k
−
1

(
W
)
→

⋀

k

(
V
)
→

⋀

k

(
W
)
→
0

{\displaystyle 0 \to U \otimes {\textstyle\bigwedge}^{k-1}(W) \to {\textstyle\bigwedge}^k(V) \to {\textstyle\bigwedge}^k(W) \to 0}

is exact, and if *W* is 1-dimensional then

0
→

⋀

k

(
U
)
→

⋀

k

(
V
)
→

⋀

k
−
1

(
U
)
⊗
W
→
0

{\displaystyle 0 \to {\textstyle\bigwedge}^k(U) \to {\textstyle\bigwedge}^k(V) \to {\textstyle\bigwedge}^{k-1}(U) \otimes W \to 0}

is exact.

## Alternating tensor algebra

If *K* is a field of characteristic 0, then the exterior algebra of a vector space *V* can be canonically identified with the vector subspace of T(*V*) consisting of antisymmetric tensors. Recall that the exterior algebra is the quotient of T(*V*) by the ideal *I* generated by *x* ⊗ *x*.

Let T*r*(*V*) be the space of homogeneous tensors of degree *r*. This is spanned by decomposable tensors

v
1

⊗
⋯
⊗

v
r

,

v
i

∈
V
.

{\displaystyle v\_1\otimes\cdots\otimes v\_r,\quad v\_i\in V.}

The **antisymmetrization** (or sometimes the **skew-symmetrization**) of a decomposable tensor is defined by

Alt
⁡
(

v
1

⊗
⋯
⊗

v
r

# )

1

r
!

∑

σ
∈

S

r

sgn
⁡
(
σ
)

v

σ
(
1
)

⊗
⋯
⊗

v

σ
(
r
)

{\displaystyle \operatorname{Alt}(v\_1\otimes\cdots\otimes v\_r) = \frac{1}{r!}\sum\_{\sigma\in\mathfrak{S}\_r} \operatorname{sgn}(\sigma) v\_{\sigma(1)}\otimes\cdots\otimes v\_{\sigma(r)}}

where the sum is taken over the symmetric group of permutations on the symbols {1, ..., *r*}. This extends by linearity and homogeneity to an operation, also denoted by Alt, on the full tensor algebra T(*V*). The image Alt(T(*V*)) is the **alternating tensor algebra**, denoted A(*V*). This is a vector subspace of T(*V*), and it inherits the structure of a graded vector space from that on T(*V*). It carries an associative graded product

⊗
^

{\displaystyle \widehat{\otimes}}

 defined by

t

⊗
^

# s
Alt
⁡
(
t
⊗
s
)
.

{\displaystyle t~\widehat{\otimes}~s = \operatorname{Alt}(t\otimes s).}

Although this product differs from the tensor product, the kernel of *Alt* is precisely the ideal *I* (again, assuming that *K* has characteristic 0), and there is a canonical isomorphism

A
(
V
)
≅

⋀

(
V
)
.

{\displaystyle A(V)\cong {\textstyle\bigwedge}(V).}

### Index notation

Suppose that *V* has finite dimension *n*, and that a basis **e**1, ..., **e***n* of *V* is given. then any alternating tensor *t* ∈ A*r*(*V*) ⊂ *T**r*(*V*) can be written in index notation as

# t

t

i
1

i
2

⋯

i
r

e

i
1

⊗

e

i
2

⊗
⋯
⊗

e

i
r

,

{\displaystyle t = t^{i\_1i\_2\cdots i\_r}\, {\mathbf e}\_{i\_1}\otimes {\mathbf e}\_{i\_2}\otimes\cdots\otimes {\mathbf e}\_{i\_r},}

where *t**i*1⋅⋅⋅*i**r* is completely antisymmetric in its indices.

The exterior product of two alternating tensors *t* and *s* of ranks *r* and *p* is given by

t

⊗
^

# s

1

(
r
p
)
!

∑

σ
∈

S

r
p

sgn
⁡
(
σ
)

t

i

σ
(
1
)

⋯

i

σ
(
r
)

s

i

σ
(
r
1
)

⋯

i

σ
(
r
p
)

e

i
1

⊗

e

i
2

⊗
⋯
⊗

e

i

r
p

.

{\displaystyle t~\widehat{\otimes}~s = \frac{1}{(r+p)!}\sum\_{\sigma\in {\mathfrak S}\_{r+p}}\operatorname{sgn}(\sigma)t^{i\_{\sigma(1)}\cdots i\_{\sigma(r)}} s^{i\_{\sigma(r+1)} \cdots i\_{\sigma(r+p)}} {\mathbf e}\_{i\_1}\otimes {\mathbf e}\_{i\_2} \otimes \cdots\otimes {\mathbf e}\_{i\_{r+p}}.}

The components of this tensor are precisely the skew part of the components of the tensor product *s* ⊗ *t*, denoted by square brackets on the indices:

(
t

⊗
^

s

)

i
1

⋯

i

r
p

=

t

[

i
1

⋯

i
r

s

i

r
1

⋯

i

r
p

]

.

{\displaystyle (t~\widehat{\otimes}~s)^{i\_1\cdots i\_{r+p}} = t^{[i\_1\cdots i\_r}s^{i\_{r+1}\cdots i\_{r+p}]}.}

The interior product may also be described in index notation as follows. Let

# t

t

i
0

i
1

⋯

i

r
−
1

{\displaystyle t = t^{i\_0i\_1\cdots i\_{r-1}}}

 be an antisymmetric tensor of rank *r*. Then, for *α* ∈ *V*∗, *i**α**t* is an alternating tensor of rank *r* − 1, given by

(

i
α

t

)

i
1

⋯

i

r
−
1

=
r

∑

# j
0

n

α
j

t

j

i
1

⋯

i

r
−
1

.

{\displaystyle (i\_\alpha t)^{i\_1\cdots i\_{r-1}}=r\sum\_{j=0}^n\alpha\_j t^{ji\_1\cdots i\_{r-1}}.}

where *n* is the dimension of *V*.

## Applications

### Linear algebra

In applications to linear algebra, the exterior product provides an abstract algebraic manner for describing the determinant and the minors of a matrix. For instance, it is well known that the magnitude of the determinant of a square matrix is equal to the volume of the parallelotope whose sides are the columns of the matrix. This suggests that the determinant can be *defined* in terms of the exterior product of the column vectors. Likewise, the *k* × *k* minors of a matrix can be defined by looking at the exterior products of column vectors chosen *k* at a time. These ideas can be extended not just to matrices but to linear transformations as well: the magnitude of the determinant of a linear transformation is the factor by which it scales the volume of any given reference parallelotope. So the determinant of a linear transformation can be defined in terms of what the transformation does to the top exterior power. The action of a transformation on the lesser exterior powers gives a basis-independent way to talk about the minors of the transformation.

#### Technical details: Definitions

Let

V

{\displaystyle V}

 be an *n*-dimensional vector space over field

K

{\displaystyle K}

 with basis

{

e
1

,
…
,

e
n

}

{\displaystyle \{e\_1,\ldots,e\_n\}}

.

* For

A
∈
End
⁡
(
V
)

{\displaystyle A \in \operatorname{End}(V)}

, define

⋀

k

A
∈
End
⁡
(

⋀

k

V
)

{\displaystyle {\textstyle\bigwedge}^k A \in \operatorname{End}({\textstyle\bigwedge}^k V) }

 on simple tensors by

⋀

k

A
(

v
1

∧
⋯
∧

v
k

# )
A

v
1

∧
⋯
∧
A

v
k

{\displaystyle {\textstyle\bigwedge}^k A(v\_1 \wedge\cdots\wedge v\_k)=Av\_1 \wedge \cdots \wedge Av\_k }

and expand the definition linearly to all tensors. More generally, we can define

⋀

p

A
k

∈
End
⁡
(

⋀

p

V
)
,
(
p
≥
k
)

{\displaystyle {\textstyle\bigwedge}^p A^k \in \operatorname{End}({\textstyle\bigwedge}^p V), (p \geq k) }

 on simple tensors by

(

⋀

p

A
k

)

(

v
1

∧
⋯
∧

v
p

# )

∑

0
≤

i
1

<
⋯
<

i
k

≤
p

v
1

∧
⋯
∧
A

v

i
1

∧
⋯
∧
A

v

i
k

∧
⋯
∧

v
p

{\displaystyle \left ({\textstyle\bigwedge}^p A^k \right )(v\_1 \wedge \cdots \wedge v\_p)=\sum\_{0 \leq i\_1 < \cdots < i\_k \leq p} v\_1 \wedge \cdots \wedge Av\_{i\_1} \wedge \cdots \wedge Av\_{i\_k} \wedge \cdots \wedge v\_p}

i.e. choose *k* components on which *A* would act, then sum up all results obtained from different choices. If

p
<
k

{\displaystyle p<k}

, define

⋀

p

A
k

=
0

{\displaystyle {\textstyle\bigwedge}^p A^k=0 }

. Since

⋀

n

V

{\displaystyle {\textstyle\bigwedge}^n V }

 is 1-dimensional with basis

e
1

∧
⋯
∧

e
n

{\displaystyle e\_1 \wedge \cdots \wedge e\_n}

, we can identify

⋀

n

A
k

{\displaystyle {\textstyle\bigwedge}^n A^k }

 with the unique number

κ
∈
K

{\displaystyle \kappa \in K }

 satisfying

⋀

n

A
k

(

e
1

∧
⋯
∧

e
n

# )
κ
(

e
1

∧
⋯
∧

e
n

)
.

{\displaystyle {\textstyle\bigwedge}^n A^k (e\_1 \wedge \cdots \wedge e\_n) = \kappa (e\_1 \wedge \cdots \wedge e\_n) .}

* For

φ
∈
End
⁡
(

⋀

p

V
)

{\displaystyle \varphi \in \operatorname{End}({\textstyle\bigwedge}^p V)}

, define the **exterior transpose**

φ

T

∈
End
⁡
(

⋀

n
−
p

V
)

{\displaystyle \varphi^\mathrm{T} \in \operatorname{End}({\textstyle\bigwedge}^{n-p} V)}

 to be the unique operator satisfying

∀

ω
p

∈

⋀

p

V
,

ω

n
−
p

∈

⋀

n
−
p

V
,
(

φ

T

ω

n
−
p

)
∧

ω
p

=

ω

n
−
p

∧
(
φ

ω
p

)

{\displaystyle \forall \omega\_p \in {\textstyle\bigwedge}^p V, \omega\_{n-p} \in {\textstyle\bigwedge}^{n-p}V, (\varphi^\mathrm{T}\omega\_{n-p})\wedge\omega\_p=\omega\_{n-p}\wedge(\varphi \omega\_p)}

* For

A
∈
End
⁡
(
V
)

{\displaystyle A \in \operatorname{End}(V)}

, define

det
# A

⋀

n

A
n

,
Tr
⁡
(
A
# )

⋀

n

A
1

,
adj
⁡
# A
(

⋀

n
−
1

A

n
−
1

)

T

{\displaystyle \det A={\textstyle\bigwedge}^n A^n, \operatorname{Tr}(A)={\textstyle\bigwedge}^n A^1, \operatorname{adj} A=({\textstyle\bigwedge}^{n-1} A^{n-1})^\mathrm{T} }

. These definitions is equivalent to the other versions.

#### Basic Properties

All results obtained from other definitions of the determinant, trace and adjoint can be obtained from this definition (since these definitions are equivalent). Here are some basic properties related to these new definitions:

* (
⋅

)

T

{\displaystyle (\cdot)^\mathrm{T}}

 is

K

{\displaystyle K}

-linear.

* (
A
B

)

T

=

B

T

A

T

.

{\displaystyle (AB)^\mathrm{T} = B^\mathrm{T} A^\mathrm{T}.}

* We have a canonical isomorphism

{

ψ
:
End
⁡
(

⋀

k

V
)
≅
End
⁡
(

⋀

n
−
k

V
)

A
↦

A

T

{\displaystyle \begin{cases}\psi:\operatorname{End}({\textstyle\bigwedge}^k V) \cong \operatorname{End}({\textstyle\bigwedge}^{n-k} V) \\ A \mapsto A^\mathrm{T} \end{cases}}

However, there is no canonical isomorphism between

⋀

k

V

{\displaystyle {\textstyle\bigwedge}^k V}

 and

⋀

n
−
k

V
.

{\displaystyle {\textstyle\bigwedge}^{n-k} V.}

* Tr
⁡

(

⋀

k

A

)

=

⋀

n

A
k

.

{\displaystyle \operatorname{Tr} \left ({\textstyle\bigwedge}^k A \right ) = {\textstyle\bigwedge}^n A^k.}

 The entries of the transposed matrix of

⋀

k

A

{\displaystyle {\textstyle\bigwedge}^k A}

 are

k
×
k

{\displaystyle k \times k}

-minors of

A

{\displaystyle A}

.

* ∀
k
⩽
n
−
1
,
p
⩽
k
,
A
∈
End
⁡
(
V
)
,

{\displaystyle \forall k \leqslant n-1, p \leqslant k, A \in \operatorname{End}(V),}

∑

# q
0

p

(

⋀

n
−
k

A

p
−
q

)

T

(

⋀

k

A
q

)

=

(

⋀

n

A
p

)

Id
∈
End
⁡
(
V
)
.

{\displaystyle \sum\_{q=0}^p \left ({\textstyle\bigwedge}^{n-k} A^{p-q} \right )^\mathrm{T} \left ({\textstyle\bigwedge}^k A^q \right ) = \left ({\textstyle\bigwedge}^n A^p \right ) \operatorname{Id} \in \operatorname{End}(V).}

In particular,

(

⋀

n
−
1

A

p
−
1

)

T

A

(

⋀

n
−
1

A
p

)

T

=

(

⋀

n

A
p

)

Id

{\displaystyle \left ({\textstyle\bigwedge}^{n-1} A^{p-1} \right )^\mathrm{T} A + \left ({\textstyle\bigwedge}^{n-1} A^p \right )^\mathrm{T} = \left ({\textstyle\bigwedge}^n A^p \right ) \operatorname{Id}}

and hence

(
adj
⁡
A
)
# A

(

⋀

n
−
1

A

n
−
1

)

T

# A

(

⋀

n

A
n

)

# Id
(
det
A
)
Id
.

{\displaystyle (\operatorname{adj} A)A = \left ({\textstyle\bigwedge}^{n-1} A^{n-1} \right )^\mathrm{T} A = \left ({\textstyle\bigwedge}^n A^n \right ) \operatorname{Id} =(\det A)\operatorname{Id}.}

* (

⋀

n
−
1

A
p

)

T

=

∑

# q
0

p

(

⋀

n

A

p
−
q

)

(
−
A

)
q

=

∑

# q
0

p

Tr
⁡

(

⋀

p
−
q

A

)

(
−
A

)
q

.

{\displaystyle \left ({\textstyle\bigwedge}^{n-1} A^p \right )^\mathrm{T} = \sum\_{q=0}^p \left ({\textstyle\bigwedge}^n A^{p-q} \right )(-A)^q = \sum\_{q=0}^p \operatorname{Tr} \left ({\textstyle\bigwedge}^{p-q} A \right )(-A)^q.}

In particular,

adj
⁡

# q
0

n
−
1

(

⋀

n

A

n
−
q
−
1

)

(
−
A

)
q

.

{\displaystyle \operatorname{adj} A = \sum\_{q=0}^{n-1} \left ({\textstyle\bigwedge}^n A^{n-q-1} \right )(-A)^q.}

* Tr
⁡

(

⋀

k

adj
⁡
A

)

=

⋀

n

(
adj
⁡
A

)
k

=
(
det
A

)

k
−
1

(

⋀

n

A

n
−
k

)

=
(
det
A

)

k
−
1

Tr
⁡

(

⋀

n
−
k

A

)

.

{\displaystyle \operatorname{Tr} \left ({\textstyle\bigwedge}^k \operatorname{adj} A \right ) = {\textstyle\bigwedge}^n (\operatorname{adj} A)^k = (\det A)^{k-1} \left ({\textstyle\bigwedge}^n A^{n-k} \right ) = (\det A)^{k-1} \operatorname{Tr} \left ({\textstyle\bigwedge}^{n-k} A \right ).}

* Tr
⁡

(

(

⋀

n
−
1

A
k

)

T

)

=
(
n
−
k
)

⋀

n

A
p

=
(
n
−
k
)
Tr
⁡

(

⋀

p

A

)

.

{\displaystyle \operatorname{Tr} \left ( \left ({\textstyle\bigwedge}^{n-1} A^k \right )^\mathrm{T} \right )=(n-k) {\textstyle\bigwedge}^n A^p=(n-k) \operatorname{Tr}\left ({\textstyle\bigwedge}^p A \right ).}

* The characteristic polynomial

ch
A

⁡
(
t
)

{\displaystyle \operatorname{ch}\_A(t)}

 of

A
∈
End
⁡
(
V
)

{\displaystyle A \in \operatorname{End}(V)}

 can be given by

ch
A

⁡
(
t

# k
0

n

Tr
⁡

(

⋀

k

A

)

(
−
t

)

n
−
k

=

∑

# k
0

n

(

⋀

n

A
k

)

(
−
t

)

n
−
k

.

{\displaystyle \operatorname{ch}\_A(t)=\sum\_{k=0}^n \operatorname{Tr} \left ({\textstyle\bigwedge}^k A \right )(-t)^{n-k} = \sum\_{k=0}^n \left ({\textstyle\bigwedge}^n A^k \right )(-t)^{n-k} .}

Similarly,

ch

adj
⁡
A

⁡
(
t

# k
0

n

(

⋀

n

(
adj
⁡
A

)
k

)

(
−
t

)

n
−
k

=

∑

# k
0

n

(
det
A

)

k
−
1

(

⋀

n

A

n
−
k

)

(
−
t

)

n
−
k

{\displaystyle \operatorname{ch}\_{\operatorname{adj} A}(t)=\sum\_{k=0}^n \left ({\textstyle\bigwedge}^n(\operatorname{adj} A)^k \right )(-t)^{n-k} = \sum\_{k=0}^n (\det A)^{k-1} \left ({\textstyle\bigwedge}^n A^{n-k} \right )(-t)^{n-k}}

#### Leverrier's algorithm

See also: Faddeev–LeVerrier algorithm

⋀

n

A
k

{\displaystyle {\textstyle\bigwedge}^n A^k }

 is the coefficient of

(
−
t

)

n
−
k

{\displaystyle (-t)^{n-k}}

 term in the characteristic polynomial. They also appear in the expressions of

(

⋀

n
−
1

A
p

)

T

{\textstyle \left({\textstyle\bigwedge}^{n-1} A^p\right)^\mathrm{T}}

 and

⋀

n

(
adj
⁡
A

)
k

{\displaystyle {\textstyle\bigwedge}^n (\operatorname{adj} A)^k}

. Leverrier's Algorithm is an economical way of computing

⋀

n

A
k

{\displaystyle {\textstyle\bigwedge}^n A^k }

 and

⋀

n
−
1

A
k

{\displaystyle {\textstyle\bigwedge}^{n-1} A^k}

:
Set

⋀

n
−
1

A
0

=
1

{\displaystyle {\textstyle\bigwedge}^{n-1} A^0 = 1}

;
For

# k
n
−
1
,
n
−
2
,
…
,
1
,
0

{\displaystyle k=n-1,n-2,\ldots,1,0}

,

⋀

n

A

n
−
k

=

1

n
−
k

Tr
⁡
(
A
∘

⋀

n
−
1

A

n
−
k
−
1

)
;

{\displaystyle {\textstyle\bigwedge}^n A^{n-k} = \frac{1}{n-k} \operatorname{Tr}(A \circ {\textstyle\bigwedge}^{n-1} A^{n-k-1});}

⋀

n
−
1

A

n
−
k

=

⋀

n

A

n
−
k

⋅
Id
−
A
∘

⋀

n
−
1

A

n
−
k
−
1

.

{\displaystyle {\textstyle\bigwedge}^{n-1} A^{n-k} = {\textstyle\bigwedge}^n A^{n-k} \cdot \operatorname{Id} - A \circ {\textstyle\bigwedge}^{n-1} A^{n-k-1}.}

### Physics

In physics, many quantities are naturally represented by alternating operators. For example, if the motion of a charged particle is described by velocity and acceleration vectors in four-dimensional spacetime, then normalization of the velocity vector requires that the electromagnetic force must be an alternating operator on the velocity. Its six degrees of freedom are identified with the electric and magnetic fields.

### Linear geometry

The decomposable *k*-vectors have geometric interpretations: the bivector *u* ∧ *v* represents the plane spanned by the vectors, "weighted" with a number, given by the area of the oriented parallelogram with sides *u* and *v*. Analogously, the 3-vector *u* ∧ *v* ∧ *w* represents the spanned 3-space weighted by the volume of the oriented parallelepiped with edges *u*, *v*, and *w*.

### Projective geometry

Decomposable *k*-vectors in Λ*k**V* correspond to weighted *k*-dimensional linear subspaces of *V*. In particular, the Grassmannian of *k*-dimensional subspaces of *V*, denoted *Gr**k*(*V*), can be naturally identified with an algebraic subvariety of the projective space **P**(Λ*k**V*). This is called the Plücker embedding.

### Differential geometry

The exterior algebra has notable applications in differential geometry, where it is used to define differential forms. Differential forms are mathematical objects that evaluate the length of vectors, areas of parallelograms, and volumes of higher-dimensional bodies, so they can be integrated over curves, surfaces and higher dimensional manifolds in a way that generalizes the line integrals and surface integrals from calculus. A differential form at a point of a differentiable manifold is an alternating multilinear form on the tangent space at the point. Equivalently, a differential form of degree *k* is a linear functional on the *k*-th exterior power of the tangent space. As a consequence, the exterior product of multilinear forms defines a natural exterior product for differential forms. Differential forms play a major role in diverse areas of differential geometry.

In particular, the exterior derivative gives the exterior algebra of differential forms on a manifold the structure of a differential algebra. The exterior derivative commutes with pullback along smooth mappings between manifolds, and it is therefore a natural differential operator. The exterior algebra of differential forms, equipped with the exterior derivative, is a cochain complex whose cohomology is called the de Rham cohomology of the underlying manifold and plays a vital role in the algebraic topology of differentiable manifolds.

### Representation theory

In representation theory, the exterior algebra is one of the two fundamental Schur functors on the category of vector spaces, the other being the symmetric algebra. Together, these constructions are used to generate the irreducible representations of the general linear group; see fundamental representation.

### Superspace

The exterior algebra over the complex numbers is the archetypal example of a superalgebra, which plays a fundamental role in physical theories pertaining to fermions and supersymmetry. A single element of the exterior algebra is called a **supernumber** or Grassmann number. The exterior algebra itself is then just a one-dimensional superspace: it is just the set of all of the points in the exterior algebra. The topology on this space is essentially the weak topology, the open sets being the cylinder sets. An *n*-dimensional superspace is just the *n*-fold product of exterior algebras.

### Lie algebra homology

Let *L* be a Lie algebra over a field *K*, then it is possible to define the structure of a chain complex on the exterior algebra of *L*. This is a *K*-linear mapping

∂
:

⋀

p
1

L
→

⋀

p

L

{\displaystyle \partial : {\textstyle\bigwedge}^{p+1}L\to{\textstyle\bigwedge}^p L}

defined on decomposable elements by

∂
(

x
1

∧
⋯
∧

x

p
1

# )

1

p
1

∑

j
<
ℓ

(
−
1

)

j
ℓ
1

[

x
j

,

x
ℓ

]
∧

x
1

∧
⋯
∧

x
^

j

∧
⋯
∧

x
^

ℓ

∧
⋯
∧

x

p
1

.

{\displaystyle \partial (x\_1\wedge\cdots\wedge x\_{p+1}) = \frac{1}{p+1}\sum\_{j<\ell}(-1)^{j+\ell+1}[x\_j,x\_\ell]\wedge x\_1\wedge\cdots\wedge \hat{x}\_j\wedge\cdots\wedge\hat{x}\_\ell\wedge\cdots\wedge x\_{p+1}.}

The Jacobi identity holds if and only if ∂∂ = 0, and so this is a necessary and sufficient condition for an anticommutative nonassociative algebra *L* to be a Lie algebra. Moreover, in that case Λ*L* is a chain complex with boundary operator ∂. The homology associated to this complex is the Lie algebra homology.

### Homological algebra

The exterior algebra is the main ingredient in the construction of the Koszul complex, a fundamental object in homological algebra.

## History

The exterior algebra was first introduced by Hermann Grassmann in 1844 under the blanket term of *Ausdehnungslehre*, or *Theory of Extension*.
This referred more generally to an algebraic (or axiomatic) theory of extended quantities and was one of the early precursors to the modern notion of a vector space. Saint-Venant also published similar ideas of exterior calculus for which he claimed priority over Grassmann.

The algebra itself was built from a set of rules, or axioms, capturing the formal aspects of Cayley and Sylvester's theory of multivectors. It was thus a *calculus*, much like the propositional calculus, except focused exclusively on the task of formal reasoning in geometrical terms.
In particular, this new development allowed for an *axiomatic* characterization of dimension, a property that had previously only been examined from the coordinate point of view.

The import of this new theory of vectors and multivectors was lost to mid 19th century mathematicians,
until being thoroughly vetted by Giuseppe Peano in 1888. Peano's work also remained somewhat obscure until the turn of the century, when the subject was unified by members of the French geometry school (notably Henri Poincaré, Élie Cartan, and Gaston Darboux) who applied Grassmann's ideas to the calculus of differential forms.

A short while later, Alfred North Whitehead, borrowing from the ideas of Peano and Grassmann, introduced his universal algebra. This then paved the way for the 20th century developments of abstract algebra by placing the axiomatic notion of an algebraic system on a firm logical footing.