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  2. Vector projection - Wikipedia

    en.wikipedia.org/wiki/Vector_projection

    Thus, the vector is parallel to , the vector is orthogonal to , and = +. The projection of a onto b can be decomposed into a direction and a scalar magnitude by writing it as a 1 = a 1 b ^ {\displaystyle \mathbf {a} _{1}=a_{1}\mathbf {\hat {b}} } where a 1 {\displaystyle a_{1}} is a scalar, called the scalar projection of a onto b , and b̂ is ...

  3. Distance from a point to a line - Wikipedia

    en.wikipedia.org/wiki/Distance_from_a_point_to_a...

    Also, let Q = (x 1, y 1) be any point on this line and n the vector (a, b) starting at point Q. The vector n is perpendicular to the line, and the distance d from point P to the line is equal to the length of the orthogonal projection of on n. The length of this projection is given by:

  4. Curl (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Curl_(mathematics)

    In 3 dimensions the curl of a vector field is a vector field as is familiar (in 1 and 0 dimensions the curl of a vector field is 0, because there are no non-trivial 2-vectors), while in 4 dimensions the curl of a vector field is, geometrically, at each point an element of the 6-dimensional Lie algebra ().

  5. Orthogonal coordinates - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_coordinates

    A conformal map acting on a rectangular grid. Note that the orthogonality of the curved grid is retained. While vector operations and physical laws are normally easiest to derive in Cartesian coordinates, non-Cartesian orthogonal coordinates are often used instead for the solution of various problems, especially boundary value problems, such as those arising in field theories of quantum ...

  6. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    Another method of deriving vector and tensor derivative identities is to replace all occurrences of a vector in an algebraic identity by the del operator, provided that no variable occurs both inside and outside the scope of an operator or both inside the scope of one operator in a term and outside the scope of another operator in the same term ...

  7. Orthogonality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Orthogonality_(mathematics)

    In Euclidean space, two vectors are orthogonal if and only if their dot product is zero, i.e. they make an angle of 90° (radians), or one of the vectors is zero. [4] Hence orthogonality of vectors is an extension of the concept of perpendicular vectors to spaces of any dimension.

  8. Curvilinear coordinates - Wikipedia

    en.wikipedia.org/wiki/Curvilinear_coordinates

    A vector v (red) represented by • a vector basis (yellow, left: e 1, e 2, e 3), tangent vectors to coordinate curves (black) and • a covector basis or cobasis (blue, right: e 1, e 2, e 3), normal vectors to coordinate surfaces (grey) in general (not necessarily orthogonal) curvilinear coordinates (q 1, q 2, q 3). The basis and cobasis do ...

  9. Orthogonal basis - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_basis

    The concept of orthogonality may be extended to a vector space over any field of characteristic not 2 equipped with a quadratic form ⁠ ⁠.Starting from the observation that, when the characteristic of the underlying field is not 2, the associated symmetric bilinear form , = ((+) ()) allows vectors and to be defined as being orthogonal with respect to when ⁠ (+) () = ⁠.