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  2. Higher-order function - Wikipedia

    en.wikipedia.org/wiki/Higher-order_function

    In mathematics higher-order functions are also termed operators or functionals. The differential operator in calculus is a common example, since it maps a function to its derivative, also a function. Higher-order functions should not be confused with other uses of the word "functor" throughout mathematics, see Functor (disambiguation).

  3. Derivative - Wikipedia

    en.wikipedia.org/wiki/Derivative

    The higher order derivatives can be applied in physics; for example, while the first derivative of the position of a moving object with respect to time is the object's velocity, how the position changes as time advances, the second derivative is the object's acceleration, how the velocity changes as time advances.

  4. Ostrogradsky instability - Wikipedia

    en.wikipedia.org/wiki/Ostrogradsky_instability

    The Ostrogradsky instability has been proposed as an explanation as to why no differential equations of higher order than two appear to describe physical phenomena. [1] However, Ostrogradsky's theorem does not imply that all solutions of higher-derivative theories are unstable as many counterexamples are known.

  5. Differential operator - Wikipedia

    en.wikipedia.org/wiki/Differential_operator

    The most common differential operator is the action of taking the derivative. Common notations for taking the first derivative with respect to a variable x include: , , , and . When taking higher, nth order derivatives, the operator may be written:

  6. Product rule - Wikipedia

    en.wikipedia.org/wiki/Product_rule

    In calculus, the product rule (or Leibniz rule [1] or Leibniz product rule) is a formula used to find the derivatives of products of two or more functions.For two functions, it may be stated in Lagrange's notation as () ′ = ′ + ′ or in Leibniz's notation as () = +.

  7. Derivative test - Wikipedia

    en.wikipedia.org/wiki/Derivative_test

    As shown below, the second-derivative test is mathematically identical to the special case of n = 1 in the higher-order derivative test. Let f be a real-valued, sufficiently differentiable function on an interval I ⊂ R {\displaystyle I\subset \mathbb {R} } , let c ∈ I {\displaystyle c\in I} , and let n ≥ 1 {\displaystyle n\geq 1} be a ...

  8. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    Their algorithm is applicable to higher-order derivatives. A method based on numerical inversion of a complex Laplace transform was developed by Abate and Dubner. [21] An algorithm that can be used without requiring knowledge about the method or the character of the function was developed by Fornberg. [4]

  9. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    The above arithmetic can be generalized to calculate second order and higher derivatives of multivariate functions. However, the arithmetic rules quickly grow complicated: complexity is quadratic in the highest derivative degree. Instead, truncated Taylor polynomial algebra can be used. The resulting arithmetic, defined on generalized dual ...