Cross product
In mathematics, the cross product or vector product (occasionally directed area product, to emphasize its geometric significance) is a binary operation on two vectors in a three-dimensional oriented Euclidean vector space (named here formula_1), and is denoted by the symbol formula_2. Given two linearly independent vectors and , the cross product, (read "a cross b"), is a vector that is perpendicular to both and , and thus normal to the plane containing them. It has many applications in mathematics, physics, engineering, and computer programming. It should not be confused with the dot product (projection product). If two vectors have  the same direction or have the exact opposite direction from each other (that is, they are "not" linearly independent), or if either one has zero length, then their cross product is zero. More generally, the magnitude of the product equals the area of a parallelogram with the vectors for sides; in particular, the magnitude of the product of two perpendicular vectors is the product of their lengths. The cross product is anticommutative (that is, ) and is distributive over addition (that is, ). The space formula_1 together with the cross product is an algebra over the real numbers, which is neither commutative  nor associative, but is a Lie algebra with the cross product being the Lie bracket. Like the dot product, it depends on the metric of Euclidean space, but unlike the dot product, it also depends on a choice of orientation (or "handedness") of the space (it's why an oriented space is needed). In connection with the cross product, the exterior product of vectors can be used in arbitrary dimensions (with a bivector or 2-form result) and is independent of the orientation of the space. The product can be generalized in various ways, using the orientation and metric structure  just as for the traditional 3-dimensional cross product, one can, in dimensions, take the product of vectors to produce a vector perpendicular to all of them. But if the product is limited to non-trivial binary products with vector results, it exists only in three and seven dimensions. (See § Generalizations, below, for other dimensions.) Definition. The cross product of two vectors a and b is defined only in three-dimensional space and is denoted by . In physics and applied mathematics, the wedge notation is often used (in conjunction with the name "vector product"), although in pure mathematics such notation  is usually reserved for just the exterior product, an abstraction of the vector product to dimensions. The cross product is defined as a vector c that is perpendicular (orthogonal) to both a and b, with a direction given by the right-hand rule and a magnitude equal to the area of the parallelogram that the vectors span. The cross product is defined by the formula where: If the vectors a and b are parallel (that is, the angle "θ" between them is either 0° or 180°), by the above formula, the cross product of a and b is  the zero vector 0. Direction. By convention, the direction of the vector n is given by the right-hand rule, where one simply points the forefinger of the right hand in the direction of a and the middle finger in the direction of b. Then, the vector n is coming out of the thumb (see the adjacent picture). Using this rule implies that the cross product is anti-commutative; that is, . By pointing the forefinger toward b first, and then pointing the middle finger toward a, the thumb will be forced in the opposite direction, reversing the sign of the  product vector. As the cross product operator depends on the orientation of the space (as explicit in the definition above), the cross product of two vectors is not a "true" vector, but a "pseudovector". See for more detail. Names. In 1881, Josiah Willard Gibbs, and independently Oliver Heaviside, introduced both the dot product and the cross product using a period () and an "x" (), respectively, to denote them. In 1877, to emphasize the fact that the result of a dot product is a scalar while the result of a cross product is a vector, William Kingdon Clifford coined the alternative names  scalar product and vector product for the two operations. These alternative names are still widely used in the literature. Both the cross notation () and the name cross product were possibly inspired by the fact that each scalar component of is computed by multiplying non-corresponding components of a and b. Conversely, a dot product involves multiplications between corresponding components of a and b. As explained below, the cross product can be expressed in the form of a determinant of a special matrix. According to Sarrus's rule, this involves multiplications between matrix elements identified by crossed diagonals. Computing. Coordinate notation . If (i, j,k) is a positively oriented orthonormal basis, the basis vectors satisfy the following equalities which imply, by the anticommutativity of the cross product, that The anticommutativity of the cross product (and the obvious lack of linear independence) also implies that These equalities, together with the distributivity and linearity of the cross product (though neither follows easily from the definition given above), are sufficient to determine the cross product of any two vectors a and b. Each vector can be defined as the sum of three orthogonal components parallel to the standard basis vectors: Their cross product can  be expanded using distributivity: This can be interpreted as the decomposition of into the sum of nine simpler cross products involving vectors aligned with i, j, or k. Each one of these nine cross products operates on two vectors that are easy to handle as they are either parallel or orthogonal to each other. From this decomposition, by using the above-mentioned equalities and collecting similar terms, we obtain: meaning that the three scalar components of the resulting vector s = "s"i + "s"j + "s"k = are Using column vectors, we can represent the same result as follows: Matrix  notation. The cross product can also be expressed as the formal determinant: This determinant can be computed using Sarrus's rule or cofactor expansion. Using Sarrus's rule, it expands to Using cofactor expansion along the first row instead, it expands to which gives the components of the resulting vector directly. Using Levi-Civita tensors. The latter formula avoids having to change the orientation of the space when we inverse an orthonormal basis. Properties. Geometric meaning. The magnitude of the cross product can be interpreted as the positive area of the parallelogram having a and b as sides (see Figure  1): formula_25 Indeed, one can also compute the volume "V" of a parallelepiped having a, b and c as edges by using a combination of a cross product and a dot product, called scalar triple product (see Figure 2): Since the result of the scalar triple product may be negative, the volume of the parallelepiped is given by its absolute value: Because the magnitude of the cross product goes by the sine of the angle between its arguments, the cross product can be thought of as a measure of "perpendicularity" in the same way that the dot product is a  measure of "parallelism". Given two unit vectors, their cross product has a magnitude of 1 if the two are perpendicular and a magnitude of zero if the two are parallel. The dot product of two unit vectors behaves just oppositely: it is zero when the unit vectors are perpendicular and 1 if the unit vectors are parallel. Unit vectors enable two convenient identities: the dot product of two unit vectors yields the cosine (which may be positive or negative) of the angle between the two unit vectors. The magnitude of the cross product of the two unit vectors yields the  sine (which will always be positive). Algebraic properties. If the cross product of two vectors is the zero vector (that is, ), then either one or both of the inputs is the zero vector, ( or ) or else they are parallel or antiparallel () so that the sine of the angle between them is zero ( or and ). The self cross product of a vector is the zero vector: The cross product is anticommutative, distributive over addition, and compatible with scalar multiplication so that It is not associative, but satisfies the Jacobi identity: Distributivity, linearity and Jacobi identity show that the R vector space  together with vector addition and the cross product forms a Lie algebra, the Lie algebra of the real orthogonal group in 3 dimensions, SO(3). The cross product does not obey the cancellation law; that is, with does not imply , but only that: This can be the case where b and c cancel, but additionally where a and are parallel; that is, they are related by a scale factor "t", leading to: for some scalar "t". If, in addition to and as above, it is the case that then As cannot be simultaneously parallel (for the cross product to be  0) and perpendicular (for the dot product to be 0) to a, it must be the case that b and c cancel: . From the geometrical definition, the cross product is invariant under proper rotations about the axis defined by . In formulae: More generally, the cross product obeys the following identity under matrix transformations: where formula_40 is a 3-by-3 matrix and formula_41 is the transpose of the inverse and formula_42 is the cofactor matrix. It can be readily seen how this formula reduces to the former one if formula_40 is a rotation matrix. The cross product of two vectors lies  in the null space of the matrix with the vectors as rows: For the sum of two cross products, the following identity holds: Differentiation. The product rule of differential calculus applies to any bilinear operation, and therefore also to the cross product: where a and b are vectors that depend on the real variable "t". Triple product expansion. The cross product is used in both forms of the triple product. The scalar triple product of three vectors is defined as It is the signed volume of the parallelepiped with edges a, b and c and as such the vectors can  be used in any order that's an even permutation of the above ordering. The following therefore are equal: The vector triple product is the cross product of a vector with the result of another cross product, and is related to the dot product by the following formula The mnemonic "BAC minus CAB" is used to remember the order of the vectors in the right hand member. This formula is used in physics to simplify vector calculations. A special case, regarding gradients and useful in vector calculus, is where ∇ is the vector Laplacian operator. Other identities relate the cross  product to the scalar triple product: where "I" is the identity matrix. Alternative formulation. The cross product and the dot product are related by: The right-hand side is the Gram determinant of a and b, the square of the area of the parallelogram defined by the vectors. This condition determines the magnitude of the cross product. Namely, since the dot product is defined, in terms of the angle "θ" between the two vectors, as: the above given relationship can be rewritten as follows: Invoking the Pythagorean trigonometric identity one obtains: which is the magnitude of the cross product expressed  in terms of "θ", equal to the area of the parallelogram defined by a and b (see definition above). The combination of this requirement and the property that the cross product be orthogonal to its constituents a and b provides an alternative definition of the cross product. Lagrange's identity. The relation: can be compared with another relation involving the right-hand side, namely Lagrange's identity expressed as: where a and b may be "n"-dimensional vectors. This also shows that the Riemannian volume form for surfaces is exactly the surface element from vector calculus. In the case where , combining  these two equations results in the expression for the magnitude of the cross product in terms of its components: The same result is found directly using the components of the cross product found from: In R, Lagrange's equation is a special case of the multiplicativity of the norm in the quaternion algebra. It is a special case of another formula, also sometimes called Lagrange's identity, which is the three dimensional case of the Binet–Cauchy identity: If and this simplifies to the formula above. Infinitesimal generators of rotations. The cross product conveniently describes the infinitesimal generators of rotations  in R. Specifically, if n is a unit vector in R and "R"("φ", n) denotes a rotation about the axis through the origin specified by n, with angle φ (measured in radians, counterclockwise when viewed from the tip of n), then for every vector x in R. The cross product with n therefore describes the infinitesimal generator of the rotations about n. These infinitesimal generators form the Lie algebra so(3) of the rotation group SO(3), and we obtain the result that the Lie algebra R with cross product is isomorphic to the Lie algebra so(3). Alternative ways to compute. Conversion  to matrix multiplication. The vector cross product also can be expressed as the product of a skew-symmetric matrix and a vector: formula_62 where superscript refers to the transpose operation, and [a] is defined by: formula_63 The columns [a] of the skew-symmetric matrix for a vector a can be also obtained by calculating the cross product with unit vectors. That is, formula_64 or formula_65 where formula_66 is the outer product operator. Also, if a is itself expressed as a cross product: formula_67 then formula_68 This result can be generalized to higher dimensions using geometric algebra. In particular in any  dimension bivectors can be identified with skew-symmetric matrices, so the product between a skew-symmetric matrix and vector is equivalent to the grade-1 part of the product of a bivector and vector. In three dimensions bivectors are dual to vectors so the product is equivalent to the cross product, with the bivector instead of its vector dual. In higher dimensions the product can still be calculated but bivectors have more degrees of freedom and are not equivalent to vectors. This notation is also often much easier to work with, for example, in epipolar geometry. From the general properties of  the cross product follows immediately that formula_69   and   formula_70 and from fact that [a] is skew-symmetric it follows that formula_71 The above-mentioned triple product expansion (bac–cab rule) can be easily proven using this notation. As mentioned above, the Lie algebra R with cross product is isomorphic to the Lie algebra so(3), whose elements can be identified with the 3×3 skew-symmetric matrices. The map a → [a] provides an isomorphism between R and so(3). Under this map, the cross product of 3-vectors corresponds to the commutator of 3x3 skew-symmetric matrices. Index notation for tensors. The  cross product can alternatively be defined in terms of the Levi-Civita tensor "E" and a dot product "η", which are useful in converting vector notation for tensor applications: where the indices formula_73 correspond to vector components. This characterization of the cross product is often expressed more compactly using the Einstein summation convention as in which repeated indices are summed over the values 1 to 3. In a positively-oriented orthonormal basis "η" = δ (the Kronecker delta) and formula_75 (the Levi-Civita symbol). In that case, this representation is another form of the skew-symmetric representation of the cross  product: In classical mechanics: representing the cross product by using the Levi-Civita symbol can cause mechanical symmetries to be obvious when physical systems are isotropic. (An example: consider a particle in a Hooke's Law potential in three-space, free to oscillate in three dimensions; none of these dimensions are "special" in any sense, so symmetries lie in the cross-product-represented angular momentum, which are made clear by the abovementioned Levi-Civita representation). Mnemonic. The word "xyzzy" can be used to remember the definition of the cross product. If where: then: The second and third equations can be  obtained from the first by simply vertically rotating the subscripts, . The problem, of course, is how to remember the first equation, and two options are available for this purpose: either to remember the relevant two diagonals of Sarrus's scheme (those containing i), or to remember the xyzzy sequence. Since the first diagonal in Sarrus's scheme is just the main diagonal of the above-mentioned 3×3 matrix, the first three letters of the word xyzzy can be very easily remembered. Cross visualization. Similarly to the mnemonic device above, a "cross" or X can be visualized between the two vectors  in the equation. This may be helpful for remembering the correct cross product formula. If then: If we want to obtain the formula for formula_84 we simply drop the formula_85 and formula_86 from the formula, and take the next two components down: When doing this for formula_88 the next two elements down should "wrap around" the matrix so that after the z component comes the x component. For clarity, when performing this operation for formula_88, the next two components should be z and x (in that order). While for formula_90 the next two components should be taken as x and  y. For formula_84 then, if we visualize the cross operator as pointing from an element on the left to an element on the right, we can take the first element on the left and simply multiply by the element that the cross points to in the right hand matrix. We then subtract the next element down on the left, multiplied by the element that the cross points to here as well. This results in our formula_84 formula – We can do this in the same way for formula_88 and formula_90 to construct their associated formulas. Applications. The cross product has applications  in various contexts. For example, it is used in computational geometry, physics and engineering. A non-exhaustive list of examples follows. Computational geometry. The cross product appears in the calculation of the distance of two skew lines (lines not in the same plane) from each other in three-dimensional space. The cross product can be used to calculate the normal for a triangle or polygon, an operation frequently performed in computer graphics. For example, the winding of a polygon (clockwise or anticlockwise) about a point within the polygon can be calculated by triangulating the polygon (like spoking a wheel) and  summing the angles (between the spokes) using the cross product to keep track of the sign of each angle. In computational geometry of the plane, the cross product is used to determine the sign of the acute angle defined by three points formula_97 and formula_98. It corresponds to the direction (upward or downward) of the cross product of the two coplanar vectors defined by the two pairs of points formula_99 and formula_100. The sign of the acute angle is the sign of the expression which is the signed length of the cross product of the two vectors. In the "right -handed" coordinate system, if the result is 0, the points are collinear; if it is positive, the three points constitute a positive angle of rotation around formula_102 from formula_103 to formula_104, otherwise a negative angle. From another point of view, the sign of formula_105 tells whether formula_104 lies to the left or to the right of line formula_107 The cross product is used in calculating the volume of a polyhedron such as a tetrahedron or parallelepiped. Angular momentum and torque. The angular momentum of a particle about a given origin is defined as: where is the position vector of the  particle relative to the origin, is the linear momentum of the particle. In the same way, the moment of a force applied at point B around point A is given as: In mechanics the "moment of a force" is also called "torque" and written as formula_110 Since position linear momentum and force are all "true" vectors, both the angular momentum and the moment of a force are "pseudovectors" or "axial vectors". Rigid body. The cross product frequently appears in the description of rigid motions. Two points "P" and "Q" on a rigid body can be related by: where formula_112 is  the point's position, formula_113 is its velocity and formula_114 is the body's angular velocity. Since position formula_112 and velocity formula_113 are "true" vectors, the angular velocity formula_114 is a "pseudovector" or "axial vector". Lorentz force. The cross product is used to describe the Lorentz force experienced by a moving electric charge Since velocity force and electric field are all "true" vectors, the magnetic field is a "pseudovector". Other. In vector calculus, the cross product is used to define the formula for the vector operator curl. The trick of rewriting a cross product in terms of a matrix multiplication  appears frequently in epipolar and multi-view geometry, in particular when deriving matching constraints. As an external product. The cross product can be defined in terms of the exterior product. It can be generalized to an external product in other than three dimensions. This view allows for a natural geometric interpretation of the cross product. In exterior algebra the exterior product of two vectors is a bivector. A bivector is an oriented plane element, in much the same way that a vector is an oriented line element. Given two vectors "a" and "b", one can view the bivector as the  oriented parallelogram spanned by "a" and "b". The cross product is then obtained by taking the Hodge star of the bivector , mapping 2-vectors to vectors: This can be thought of as the oriented multi-dimensional element "perpendicular" to the bivector. Only in three dimensions is the result an oriented one-dimensional element – a vector – whereas, for example, in four dimensions the Hodge dual of a bivector is two-dimensional – a bivector. So, only in three dimensions can a vector cross product of "a" and "b" be defined as the vector dual to the bivector : it is perpendicular to the  bivector, with orientation dependent on the coordinate system's handedness, and has the same magnitude relative to the unit normal vector as has relative to the unit bivector; precisely the properties described above. Handedness. Consistency. When physics laws are written as equations, it is possible to make an arbitrary choice of the coordinate system, including handedness. One should be careful to never write down an equation where the two sides do not behave equally under all transformations that need to be considered. For example, if one side of the equation is a cross product of two polar vectors, one must  take into account that the result is an axial vector. Therefore, for consistency, the other side must also be an axial vector. More generally, the result of a cross product may be either a polar vector or an axial vector, depending on the type of its operands (polar vectors or axial vectors). Namely, polar vectors and axial vectors are interrelated in the following ways under application of the cross product: or symbolically Because the cross product may also be a polar vector, it may not change direction with a mirror image transformation. This happens, according to the above relationships, if  one of the operands is a polar vector and the other one is an axial vector (e.g., the cross product of two polar vectors). For instance, a vector triple product involving three polar vectors is a polar vector. A handedness-free approach is possible using exterior algebra. The paradox of the orthonormal basis. Let (i, j,k) be an orthonormal basis. The vectors i, j and k don't depend on the orientation of the space. They can even be defined in the absence of any orientation. They can not therefore be axial vectors. But if i and j are  polar vectors then k is an axial vector for i × j = k or j × i = k. This is a paradox. "Axial" and "polar" are "physical" qualifiers for "physical" vectors; that is, vectors which represent "physical" quantities such as the velocity or the magnetic field. The vectors i, j and k are mathematical vectors, neither axial nor polar. In mathematics, the cross-product of two vectors is a vector. There is no contradiction. Generalizations. There are several ways to generalize the cross product to higher dimensions. Lie algebra. The cross product can be seen as one of  the simplest Lie products, and is thus generalized by Lie algebras, which are axiomatized as binary products satisfying the axioms of multilinearity, skew-symmetry, and the Jacobi identity. Many Lie algebras exist, and their study is a major field of mathematics, called Lie theory. For example, the Heisenberg algebra gives another Lie algebra structure on formula_120 In the basis formula_121 the product is formula_122 Quaternions. The cross product can also be described in terms of quaternions. In general, if a vector is represented as the quaternion , the cross product of two vectors can be obtained by taking their product as  quaternions and deleting the real part of the result. The real part will be the negative of the dot product of the two vectors. Octonions. A cross product for 7-dimensional vectors can be obtained in the same way by using the octonions instead of the quaternions. The nonexistence of nontrivial vector-valued cross products of two vectors in other dimensions is related to the result from Hurwitz's theorem that the only normed division algebras are the ones with dimension 1, 2, 4, and 8. Exterior product. In general dimension, there is no direct analogue of the binary cross  product that yields specifically a vector. There is however the exterior product, which has similar properties, except that the exterior product of two vectors is now a 2-vector instead of an ordinary vector. As mentioned above, the cross product can be interpreted as the exterior product in three dimensions by using the Hodge star operator to map 2-vectors to vectors. The Hodge dual of the exterior product yields an -vector, which is a natural generalization of the cross product in any number of dimensions. The exterior product and dot product can be combined (through summation) to form the  geometric product in geometric algebra. External product. As mentioned above, the cross product can be interpreted in three dimensions as the Hodge dual of the exterior product. In any finite "n" dimensions, the Hodge dual of the exterior product of vectors is a vector. So, instead of a binary operation, in arbitrary finite dimensions, the cross product is generalized as the Hodge dual of the exterior product of some given vectors. This generalization is called external product. Commutator product. Interpreting the three-dimensional vector space of the algebra as the 2-vector (not the 1-vector) subalgebra of the three -dimensional geometric algebra, where formula_123, formula_124, and formula_125, the cross product corresponds exactly to the commutator product in geometric algebra and both use the same symbol formula_2. The commutator product is defined for 2-vectors formula_127 and formula_128 in geometric algebra as: where formula_130 is the geometric product. The commutator product could be generalised to arbitrary multivectors in three dimensions, which results in a multivector consisting of only elements of grades 1 (1-vectors/true vectors) and 2 (2-vectors/pseudovectors). While the commutator product of two 1-vectors is indeed the same as the exterior product and yields a  2-vector, the commutator of a 1-vector and a 2-vector yields a true vector, corresponding instead to the left and right contractions in geometric algebra. The commutator product of two 2-vectors has no corresponding equivalent product, which is why the commutator product is defined in the first place for 2-vectors. Furthermore, the commutator triple product of three 2-vectors is the same as the vector triple product of the same three pseudovectors in vector algebra. However, the commutator triple product of three 1-vectors in geometric algebra is instead the negative of the vector triple product  of the same three true vectors in vector algebra. Generalizations to higher dimensions is provided by the same commutator product of 2-vectors in higher-dimensional geometric algebras, but the 2-vectors are no longer pseudovectors. Just as the commutator product/cross product of 2-vectors in three dimensions correspond to the simplest Lie algebra, the 2-vector subalgebras of higher dimensional geometric algebra equipped with the commutator product also correspond to the Lie algebras. Also as in three dimensions, the commutator product could be further generalised to arbitrary multivectors. Multilinear algebra. In the context of multilinear algebra, the cross  product can be seen as the (1,2)-tensor (a mixed tensor, specifically a bilinear map) obtained from the 3-dimensional volume form, a (0,3)-tensor, by raising an index. In detail, the 3-dimensional volume form defines a product formula_131 by taking the determinant of the matrix given by these 3 vectors. By duality, this is equivalent to a function formula_132 (fixing any two inputs gives a function formula_133 by evaluating on the third input) and in the presence of an inner product (such as the dot product; more generally, a non-degenerate bilinear form), we have an isomorphism formula_134 and thus  this yields a map formula_135 which is the cross product: a (0,3)-tensor (3 vector inputs, scalar output) has been transformed into a (1,2)-tensor (2 vector inputs, 1 vector output) by "raising an index". Translating the above algebra into geometry, the function "volume of the parallelepiped defined by formula_136" (where the first two vectors are fixed and the last is an input), which defines a function formula_133, can be "represented" uniquely as the dot product with a vector: this vector is the cross product formula_138 From this perspective, the cross product is "defined" by the scalar triple product, formula_139 In the  same way, in higher dimensions one may define generalized cross products by raising indices of the "n"-dimensional volume form, which is a formula_140-tensor. The most direct generalizations of the cross product are to define either: These products are all multilinear and skew-symmetric, and can be defined in terms of the determinant and parity. The formula_143-ary product can be described as follows: given formula_142 vectors formula_148 in formula_149 define their generalized cross product formula_150 as: This is the unique multilinear, alternating product which evaluates to formula_155, formula_156 and so forth for cyclic permutations of indices. In coordinates, one  can give a formula for this formula_143-ary analogue of the cross product in R by: This formula is identical in structure to the determinant formula for the normal cross product in R except that the row of basis vectors is the last row in the determinant rather than the first. The reason for this is to ensure that the ordered vectors (v, ..., v, Λv) have a positive orientation with respect to (e, ..., e). If "n" is odd, this modification leaves the value unchanged, so this convention agrees with the normal definition of the binary product. In the case that  n is even, however, the distinction must be kept. This formula_143-ary form enjoys many of the same properties as the vector cross product: it is alternating and linear in its arguments, it is perpendicular to each argument, and its magnitude gives the hypervolume of the region bounded by the arguments. And just like the vector cross product, it can be defined in a coordinate independent way as the Hodge dual of the wedge product of the arguments. History. In 1773, Joseph-Louis Lagrange introduced the component form of both the dot and cross products in order to study the  tetrahedron in three dimensions. In 1843, William Rowan Hamilton introduced the quaternion product, and with it the terms "vector" and "scalar". Given two quaternions and , where u and v are vectors in R, their quaternion product can be summarized as . James Clerk Maxwell used Hamilton's quaternion tools to develop his famous electromagnetism equations, and for this and other reasons quaternions for a time were an essential part of physics education. In 1878 William Kingdon Clifford published his Elements of Dynamic which was an advanced text for its time. He defined the product of two vectors to have magnitude equal  to the area of the parallelogram of which they are two sides, and direction perpendicular to their plane. Oliver Heaviside and Josiah Willard Gibbs also felt that quaternion methods were too cumbersome, often requiring the scalar or vector part of a result to be extracted. Thus, about forty years after the quaternion product, the dot product and cross product were introduced — to heated opposition. Pivotal to (eventual) acceptance was the efficiency of the new approach, allowing Heaviside to reduce the equations of electromagnetism from Maxwell's original 20 to the four commonly seen today. Largely independent of this development, and  largely unappreciated at the time, Hermann Grassmann created a geometric algebra not tied to dimension two or three, with the exterior product playing a central role. In 1853 Augustin-Louis Cauchy, a contemporary of Grassmann, published a paper on algebraic keys which were used to solve equations and had the same multiplication properties as the cross product. Clifford combined the algebras of Hamilton and Grassmann to produce Clifford algebra, where in the case of three-dimensional vectors the bivector produced from two vectors dualizes to a vector, thus reproducing the cross product. The cross notation and the name "cross product  began with Gibbs. Originally they appeared in privately published notes for his students in 1881 as Elements of Vector Analysis". The utility for mechanics was noted by Aleksandr Kotelnikov. Gibbs's notation and the name "cross product" later reached a wide audience through Vector Analysis, a textbook by Edwin Bidwell Wilson, a former student. Wilson rearranged material from Gibbs's lectures, together with material from publications by Heaviside, Föpps, and Hamilton. He divided vector analysis into three parts: Two main kinds of vector multiplications were defined, and they were called as follows: Several kinds of triple products and products of  more than three vectors were also examined. The above-mentioned triple product expansion was also included.