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  2. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    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.

  3. Chain rule - Wikipedia

    en.wikipedia.org/wiki/Chain_rule

    In calculus, the chain rule is a formula that expresses the derivative of the composition of two differentiable functions f and g in terms of the derivatives of f and g.More precisely, if = is the function such that () = (()) for every x, then the chain rule is, in Lagrange's notation, ′ = ′ (()) ′ (). or, equivalently, ′ = ′ = (′) ′.

  4. Notation for differentiation - Wikipedia

    en.wikipedia.org/wiki/Notation_for_differentiation

    If f is a function, then its derivative evaluated at x is written ′ (). It first appeared in print in 1749. [3] Higher derivatives are indicated using additional prime marks, as in ″ for the second derivative and ‴ for the third derivative. The use of repeated prime marks eventually becomes unwieldy.

  5. Functional-theoretic algebra - Wikipedia

    en.wikipedia.org/wiki/Functional-theoretic_algebra

    With addition and scalar multiplication defined as this, F X is a vector space over F. Now, fix two elements a, b in X and define a function e from X to F by e(x) = 1 F for all x in X. Define L 1 and L 2 from F X to F by L 1 (f) = f(a) and L 2 (f) = f(b). Then L 1 and L 2 are two linear functionals on F X such that L 1 (e)= L 2 (e)= 1 F For f ...

  6. Del - Wikipedia

    en.wikipedia.org/wiki/Del

    The tensor derivative of a vector field (in three dimensions) is a 9-term second-rank tensor – that is, a 3×3 matrix – but can be denoted simply as , where represents the dyadic product. This quantity is equivalent to the transpose of the Jacobian matrix of the vector field with respect to space.

  7. Inverse function rule - Wikipedia

    en.wikipedia.org/wiki/Inverse_function_rule

    In calculus, the inverse function rule is a formula that expresses the derivative of the inverse of a bijective and differentiable function f in terms of the derivative of f. More precisely, if the inverse of f {\displaystyle f} is denoted as f − 1 {\displaystyle f^{-1}} , where f − 1 ( y ) = x {\displaystyle f^{-1}(y)=x} if and only if f ...

  8. Coercive function - Wikipedia

    en.wikipedia.org/wiki/Coercive_function

    However a norm-coercive mapping f : R n → R n is not necessarily a coercive vector field. For instance the rotation f : R 2 → R 2 , f ( x ) = (− x 2 , x 1 ) by 90° is a norm-coercive mapping which fails to be a coercive vector field since f ( x ) ⋅ x = 0 {\displaystyle f(x)\cdot x=0} for every x ∈ R 2 {\displaystyle x\in \mathbb {R ...

  9. Directional derivative - Wikipedia

    en.wikipedia.org/wiki/Directional_derivative

    In multivariable calculus, the directional derivative measures the rate at which a function changes in a particular direction at a given point. [citation needed]The directional derivative of a multivariable differentiable (scalar) function along a given vector v at a given point x intuitively represents the instantaneous rate of change of the function, moving through x with a direction ...