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The particular form of the inner product on vectors (e.g., or ) determines a reality structure (up to a factor of -1) by requiring ¯ =, whenever X is a matrix associated to a real vector. Thus K = i C is the reality structure in Euclidean signature , and K = Id is that for signature . With a reality structure in hand, one has the following ...
In mathematics, the dot product or scalar product [note 1] is an algebraic operation that takes two equal-length sequences of numbers (usually coordinate vectors), and returns a single number. In Euclidean geometry, the dot product of the Cartesian coordinates of two vectors is widely used.
Noting that any identity matrix is a rotation matrix, and that matrix multiplication is associative, we may summarize all these properties by saying that the n × n rotation matrices form a group, which for n > 2 is non-abelian, called a special orthogonal group, and denoted by SO(n), SO(n,R), SO n, or SO n (R), the group of n × n rotation ...
The requirement that is a positive-definite inner product then says exactly that this matrix-valued function is a symmetric positive-definite matrix at . In terms of the tensor algebra , the Riemannian metric can be written in terms of the dual basis { d x 1 , … , d x n } {\displaystyle \{dx^{1},\ldots ,dx^{n}\}} of the cotangent bundle as
The following are important identities in vector algebra.Identities that only involve the magnitude of a vector ‖ ‖ and the dot product (scalar product) of two vectors A·B, apply to vectors in any dimension, while identities that use the cross product (vector product) A×B only apply in three dimensions, since the cross product is only defined there.
In Cartesian coordinates, the divergence of a continuously differentiable vector field = + + is the scalar-valued function: = = (, , ) (, , ) = + +.. As the name implies, the divergence is a (local) measure of the degree to which vectors in the field diverge.
Frobenius inner product, the dot product of matrices considered as vectors, or, equivalently the sum of the entries of the Hadamard product; Hadamard product of two matrices of the same size, resulting in a matrix of the same size, which is the product entry-by-entry; Kronecker product or tensor product, the generalization to any size of the ...
The simple product of two triple products (or the square of a triple product), may be expanded in terms of dot products: [1] (()) (()) = [] This restates in vector notation that the product of the determinants of two 3×3 matrices equals the determinant of their matrix product.