|
|
| Line 1: |
Line 1: |
| In [[mathematics]], specifically [[differential calculus]], the '''inverse function theorem''' gives sufficient conditions for a [[function (mathematics)|function]] to be [[Invertible function|invertible]] in a [[Neighbourhood (mathematics)|neighborhood]] of a point in its [[domain of a function|domain]]. The theorem also gives a [[formula]] for the [[derivative]] of the [[inverse function]].
| | Anybody who wrote the blog is called Eusebio. South Carolina is its birth place. The best-loved hobby for him and as well his kids is up to fish and he's been for a while doing it for a while. Filing has been his profession although. Go to his website to identify a out more: http://prometeu.net<br><br>Here is my weblog ... [http://prometeu.net Clash Of Clans Hack Download No Survey No Password] |
| | |
| In [[multivariable calculus]], this theorem can be generalized to any [[vector-valued function]] whose [[Jacobian matrix and determinant|Jacobian]] [[determinant]] is nonzero at a point in its domain. In this case, the theorem gives a formula for the Jacobian [[matrix (mathematics)|matrix]] of the inverse. There are also versions of the inverse function theorem for [[complex numbers|complex]] [[holomorphic function]]s, for differentiable maps between [[manifold]]s, for differentiable functions between [[Banach space]]s, and so forth.
| |
| | |
| ==Statement of the theorem==
| |
| For functions of a single [[Variable (mathematics)|variable]], the theorem states that if ƒ is a [[continuously differentiable]] function with nonzero derivative at the point ''a'', then ƒ is invertible in a neighborhood of ''a'', the inverse is continuously differentiable, and
| |
| :<math>\bigl(f^{-1}\bigr)'(b) = \frac{1}{f'(a)}</math>
| |
| where ''b'' = ƒ(''a'').
| |
| | |
| For functions of more than one variable, the theorem states that if the [[total derivative]] of a [[continuously differentiable]] function ''F'' defined from an open set U of '''R'''<sup>''n''</sup> into '''R'''<sup>''n''</sup> is invertible at a point ''p'' (i.e., the [[Jacobian matrix and determinant|Jacobian]] determinant of ''F'' at ''p'' is non-zero), then F is an invertible function near ''p''. That is, an [[inverse function]] to ''F'' exists in some [[neighbourhood (mathematics)|neighborhood]] of ''F''(''p''). Moreover, the inverse function <math>F^{-1}</math> is also continuously differentiable. In the infinite dimensional case it is required that the [[Fréchet derivative]] have a [[bounded linear map|bounded]] inverse at ''p''.
| |
| | |
| Finally, the theorem says that
| |
| | |
| :<math> J_{F^{-1}}(F(p)) = [ J_F(p) ]^{-1}</math>
| |
| | |
| where <math>[\cdot]^{-1}</math> denotes matrix inverse and <math>J_G(q)</math> is the Jacobian matrix of the function ''G'' at
| |
| the point ''q''.
| |
| | |
| This formula can also be derived from the [[chain rule]]. The chain rule states that for functions ''G'' and ''H'' which have total derivatives at ''H(p)'' and ''p'' respectively,
| |
| | |
| :<math>J_{G \circ H} (p) = J_G (H(p)) \cdot J_H (p).</math>
| |
| | |
| Letting ''G'' be ''F''<sup> -1</sup> and ''H'' be ''F'', <math>G \circ H</math> is the identity function, whose Jacobian matrix is also
| |
| the identity. In this special case, the formula above can be solved for <math>J_{F^{-1}}(F(p))</math>.
| |
| Note that the chain rule assumes the existence of total derivative of the inside function ''H'', while
| |
| the inverse function theorem proves that ''F''<sup> -1</sup> has a total derivative at ''p''.
| |
| | |
| The existence of an inverse function to ''F'' is equivalent to saying that the system of ''n'' equations ''y''<sub>''i''</sub> = ''F''<sub>''j''</sub>(''x''<sub>1</sub>,...,''x''<sub>''n''</sub>) can be solved for ''x''<sub>1</sub>,...,''x''<sub>''n''</sub> in terms of ''y''<sub>1</sub>,...,''y''<sub>''n''</sub> if we restrict ''x'' and ''y'' to small enough neighborhoods of ''p'' and ''F(p)'', respectively.
| |
| | |
| ==Example==
| |
| | |
| Consider the [[vector-valued function]] '''F''' from '''R'''<sup>2</sup> to '''R'''<sup>2</sup> defined by
| |
| | |
| :<math>
| |
| \mathbf{F}(x,y)=
| |
| \begin{bmatrix}
| |
| {e^x \cos y}\\
| |
| {e^x \sin y}\\
| |
| \end{bmatrix}.
| |
| </math>
| |
| | |
| Then the Jacobian matrix is
| |
| | |
| :<math>
| |
| J_F(x,y)=
| |
| \begin{bmatrix}
| |
| {e^x \cos y} & {-e^x \sin y}\\
| |
| {e^x \sin y} & {e^x \cos y}\\
| |
| \end{bmatrix}
| |
| </math>
| |
| | |
| and the determinant is
| |
| | |
| :<math>
| |
| \det J_F(x,y)=
| |
| e^{2x} \cos^2 y + e^{2x} \sin^2 y=
| |
| e^{2x}.
| |
| \,\!</math>
| |
| | |
| The determinant e<sup>2x</sup> is nonzero everywhere. By the theorem, for every point ''p'' in '''R'''<sup>2</sup>, there exists a neighborhood about ''p'' over which ''F'' is invertible. Note that this is different than saying ''F'' is invertible over its entire image. In this example, ''F'' is ''not'' invertible because it is not [[injective]] (because <math>f(x,y)=f(x,y+2\pi)</math>.)
| |
| | |
| ==Notes on methods of proof==
| |
| | |
| As an important result, the inverse function theorem has been given numerous proofs. The proof most commonly seen in textbooks relies on the [[contraction mapping]] principle, also known as the [[Banach fixed point theorem]]. (This theorem can also be used as the key step in the proof of [[Picard–Lindelöf theorem|existence and uniqueness]] of solutions to [[ordinary differential equations]].)
| |
| Since this theorem applies in infinite-dimensional (Banach space) settings, it is the tool used in proving the infinite-dimensional version of the inverse function theorem (see "Generalizations", below).
| |
| | |
| An alternate proof (which works only in finite dimensions) instead uses as the key tool the [[extreme value theorem]] for functions on a compact set.<ref name="spivak_manifolds">Michael Spivak, ''Calculus on Manifolds''.</ref>
| |
| | |
| Yet another proof uses [[Newton's method]], which has the advantage of providing an [[effective method|effective version]] of the theorem. That is, given specific bounds on the derivative of the function, an estimate of the size of the neighborhood on which the function is invertible can be obtained.<ref name="hubbard_hubbard">John H. Hubbard and Barbara Burke Hubbard, ''Vector Analysis, Linear Algebra, and Differential Forms: a unified approach'', Matrix Editions, 2001.</ref>
| |
| | |
| ==Generalizations==
| |
| | |
| ===Manifolds===
| |
| | |
| The inverse function theorem can be generalized to differentiable maps between [[differentiable manifold]]s. In this context the theorem states that for a differentiable map ''F'' : ''M'' → ''N'', if the [[pushforward (differential)|derivative]] of ''F'',
| |
| | |
| :(d''F'')<sub>''p''</sub> : T<sub>''p''</sub>''M'' → T<sub>''F''(''p'')</sub>''N'' | |
| | |
| is a [[linear isomorphism]] at a point ''p'' in ''M'' then there exists an open neighborhood ''U'' of ''p'' such that
| |
| | |
| :''F''|<sub>''U''</sub> : ''U'' → ''F''(''U'')
| |
| | |
| is a [[diffeomorphism]]. Note that this implies that ''M'' and ''N'' must have the same dimension at ''p''.
| |
| | |
| If the derivative of ''F'' is an isomorphism at all points ''p'' in ''M'' then the map ''F'' is a [[local diffeomorphism]].
| |
| | |
| ===Banach spaces===
| |
| | |
| The inverse function theorem can also be generalized to differentiable maps between [[Banach space]]s. Let ''X'' and ''Y'' be Banach spaces and ''U'' an open neighbourhood of the origin in ''X''. Let ''F'' : ''U'' → ''Y'' be continuously differentiable and assume that the derivative (d''F'')<sub>0</sub> : ''X'' → ''Y'' of ''F'' at 0 is a [[bounded linear map|bounded]] linear isomorphism of ''X'' onto ''Y''. Then there exists an open neighbourhood ''V'' of ''F''(0) in ''Y'' and a continuously differentiable map ''G'' : ''V'' → ''X'' such that ''F''(''G''(''y'')) = ''y'' for all ''y'' in ''V''. Moreover, ''G''(''y'') is the only sufficiently small solution ''x'' of the equation ''F''(''x'') = ''y''.
| |
| | |
| ===Banach manifolds===
| |
| | |
| These two directions of generalization can be combined in the inverse function theorem for [[Banach manifold]]s.<ref name="lang">Serge Lang, ''Differential and Riemannian Manifolds'', Springer, 1995, ISBN 0-387-94338-2.</ref>
| |
| | |
| ===Constant rank theorem===
| |
| | |
| The inverse function theorem (and the [[implicit function theorem]]) can be seen as a special case of the constant rank theorem, which states that a smooth map with locally constant [[rank (differential topology)|rank]] near a point can be put in a particular normal form near that point.<ref name="boothby">Wiilliam M. Boothby, ''An Introduction to Differentiable Manifolds and Riemannian Geometry'', Academic Press, 2002, ISBN 0-12-116051-3.</ref> When the derivative of ''F'' is invertible at a point ''p'', it is also invertible in a neighborhood of ''p'', and hence the rank of the derivative is constant, so the constant rank theorem applies.
| |
| | |
| ===Holomorphic Functions===
| |
| | |
| If the [[Jacobian matrix and determinant|Jacobian]] (in this context the matrix formed by the [[complex derivative]]s) of a [[Holomorphic function|holomorphic]] function ''F'', defined from an open set U of '''C'''<sup>''n''</sup> into '''C'''<sup>''n''</sup>
| |
| , is invertible at a point ''p'', then F is an invertible function near ''p''. This follows immediately from the theorem above. One can also show, that this inverse is again a holomorphic function.<ref>K. Fritzsche, H. Grauert, [http://books.google.de/books?id=jSeRz36zXIMC&lpg=PP1&dq=fritzsche%20grauert&hl=de&pg=PA33#v=onepage&q&f=false "From Holomorphic Functions to Complex Manifolds"], Springer-Verlag, (2002). Page 33.</ref>
| |
| | |
| ==See also==
| |
| * [[Implicit function theorem]]
| |
| | |
| ==Notes==
| |
| {{reflist}}
| |
| | |
| ==References==
| |
| | |
| * {{cite journal
| |
| | last = Nijenhuis
| |
| | first = Albert
| |
| |authorlink= Albert Nijenhuis
| |
| | title = Strong derivatives and inverse mappings
| |
| | journal = [[The American Mathematical Monthly|Amer. Math. Monthly]]
| |
| | volume = 81
| |
| | year = 1974
| |
| | pages = 969–980
| |
| | doi = 10.2307/2319298
| |
| | issue = 9
| |
| }}
| |
| * {{cite book
| |
| | author = Renardy, Michael and Rogers, Robert C.
| |
| | title = An introduction to partial differential equations
| |
| | series = Texts in Applied Mathematics 13
| |
| | edition = Second
| |
| |publisher = Springer-Verlag
| |
| | location = New York
| |
| | year = 2004
| |
| | pages = 337–338
| |
| | isbn = 0-387-00444-0
| |
| }}
| |
| * {{cite book
| |
| | last = Rudin
| |
| | first = Walter
| |
| |authorlink= Walter Rudin
| |
| | title = Principles of mathematical analysis
| |
| | edition = Third
| |
| | series = International Series in Pure and Applied Mathematics
| |
| |publisher = McGraw-Hill Book Co.
| |
| | location = New York
| |
| | year = 1976
| |
| | pages = 221–223
| |
| }}
| |
| | |
| {{Functional Analysis}}
| |
| | |
| {{DEFAULTSORT:Derivative Rule For Inverses}}
| |
| [[Category:Multivariable calculus]]
| |
| [[Category:Differential topology]]
| |
| [[Category:Inverse functions]]
| |
| [[Category:Theorems in real analysis]]
| |
| [[Category:Theorems in calculus]]
| |
| | |
| [[de:Satz von der impliziten Funktion#Satz von der Umkehrabbildung]]
| |