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  2. Vector (mathematics and physics) - Wikipedia

    en.wikipedia.org/wiki/Vector_(mathematics_and...

    These operations and associated laws qualify Euclidean vectors as an example of the more generalized concept of vectors defined simply as elements of a vector space. Vectors play an important role in physics: the velocity and acceleration of a moving object and the forces acting on it can all be described with vectors. [7]

  3. Vector calculus - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus

    Vector calculus or vector analysis is a branch of mathematics concerned with the differentiation and integration of vector fields, primarily in three-dimensional Euclidean space, . [1] The term vector calculus is sometimes used as a synonym for the broader subject of multivariable calculus, which spans vector calculus as well as partial differentiation and multiple integration.

  4. Vector field - Wikipedia

    en.wikipedia.org/wiki/Vector_field

    Given a subset S of R n, a vector field is represented by a vector-valued function V: S → R n in standard Cartesian coordinates (x 1, …, x n).If each component of V is continuous, then V is a continuous vector field.

  5. Vector space - Wikipedia

    en.wikipedia.org/wiki/Vector_space

    In this article, vectors are represented in boldface to distinguish them from scalars. [nb 1] [1] A vector space over a field F is a non-empty set V together with a binary operation and a binary function that satisfy the eight axioms listed below. In this context, the elements of V are commonly called vectors, and the elements of F are called ...

  6. Vector algebra - Wikipedia

    en.wikipedia.org/wiki/Vector_algebra

    2. Types of Vectors • Zero Vector (\mathbf{0}): Magnitude is zero. • Unit Vector (\hat{A}): Magnitude is one. • Equal Vectors: Same magnitude and direction. • Negative Vector: Same magnitude but opposite direction. • Collinear Vectors: Parallel or anti-parallel vectors. • Coplanar Vectors: Lie in the same plane. 3. Operations on Vectors

  7. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    If the dot product of two vectors is defined—a scalar-valued product of two vectors—then it is also possible to define a length; the dot product gives a convenient algebraic characterization of both angle (a function of the dot product between any two non-zero vectors) and length (the square root of the dot product of a vector by itself).

  8. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    Consider n-dimensional vectors that are formed as a list of n scalars, such as the three-dimensional vectors = [] = []. These vectors are said to be scalar multiples of each other, or parallel or collinear , if there is a scalar λ such that x = λ y . {\displaystyle \mathbf {x} =\lambda \mathbf {y} .}

  9. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    As the name implies, the divergence is a (local) measure of the degree to which vectors in the field diverge. The divergence of a tensor field T {\displaystyle \mathbf {T} } of non-zero order k is written as div ⁡ ( T ) = ∇ ⋅ T {\displaystyle \operatorname {div} (\mathbf {T} )=\nabla \cdot \mathbf {T} } , a contraction of a tensor field ...