Inverse function theorem
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In mathematics, the inverse function theorem gives sufficient conditions for a vector-valued function to be invertible on an open region containing a point in its domain.
The theorem states that if the total derivative of a function F : Rn → Rn is invertible at a point p (i.e., the Jacobian determinant of F at p is nonzero), and F is continuously differentiable near p, then it is an invertible function near p. That is, an inverse function to F exists in some neighborhood of F(p).
The Jacobian matrix of F−1 at F(p) is then the inverse of the Jacobian of F, evaluated at p. This can be understood as a special case of the chain rule, which states that for linear transformations F and G,
- [J_ (p) = J_G (F(p)) \cdot J_F (p)]
Assume that the inverse function theorem holds at F(p). Let [G(p) = F^(p)].
- [J_ \circ F} (p) = J_} (F(p)) \cdot J_F (p)]
- [J_ (p) \cdot (J_F (p))^ = J_} (F(p)) \cdot J_F (p) \cdot (J_F (p))^]
- [I \cdot (J_F (p))^ = J_} (F(p)) \cdot I]
- [(J_F (p))^ = J_} (F(p))]
- [f'(x) = .]
The inverse function theorem can be generalized to differentiable maps between differentiable manifolds. In this context the theorem states that for a differentiable map F : M → N, if the derivative of F,
- (DF)p : TpM → TF(p)N
- F|U : U → F(U)
If the derivative of F is an isomorphism at all points p in M then the map F is a local diffeomorphism.
Examples
Several functions exist for which differentiating the inverse is much easier than differentiating the function itself. Using the inverse function theorem, a derivative of a function's inverse indicates the derivative of the original function. Perhaps the most well-known example is the method used to compute the derivative of the natural logarithm, whose inverse is the exponential function. Let [u = \ln x] and restrict the domain to x > 0. Then
- [\frac\ln x = = = } = .]
A similar approach can be used to differentiate an inverse trigonometric function. Let [u = \arctan x.] Then
- [\frac\arctan x = = \cos^2 = \cos^2 = \left(}\right)^2 = .]
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