Inverse function theorem

In mathematics, specifically differential calculus, the inverse function theorem gives a sufficient condition for a function to be invertible in a neighborhood of a point in its domain: namely, that its derivative is continuous and non-zero at the point. The theorem also gives a formula for the derivative of the inverse function. In multivariable calculus, this theorem can be generalized to any continuously differentiable, vector-valued function whose Jacobian determinant is nonzero at a point in its domain, giving a formula for the Jacobian matrix of the inverse. There are also versions of the inverse function theorem for complex holomorphic functions, for differentiable maps between manifolds, for differentiable functions between Banach spaces, and so forth. The theorem was first established by Picard and Goursat using an iterative scheme: the basic idea is to prove a fixed point theorem using the contraction mapping theorem. For functions of a single variable, the theorem states that if is a continuously differentiable function with nonzero derivative at the point ; then is injective (or bijective onto the image) in a neighborhood of , the inverse is continuously differentiable near , and the derivative of the inverse function at is the reciprocal of the derivative of at : It can happen that a function may be injective near a point while . An example is . In fact, for such a function, the inverse cannot be differentiable at , since if were differentiable at , then, by the chain rule, , which implies . (The situation is different for holomorphic functions; see #Holomorphic inverse function theorem below.) For functions of more than one variable, the theorem states that if f is a continuously differentiable function from an open subset of into , and the derivative is invertible at a point a (that is, the determinant of the Jacobian matrix of f at a is non-zero), then there exist neighborhoods of in and of such that and is bijective. Writing , this means that the system of n equations has a unique solution for in terms of when .