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In
multivariable calculus Multivariable calculus (also known as multivariate calculus) is the extension of calculus in one variable to calculus with functions of several variables: the differentiation and integration of functions involving multiple variables ('' mult ...
, the implicit function theorem is a tool that allows relations to be converted to functions of several real variables. It does so by representing the relation as the
graph of a function In mathematics, the graph of a function f is the set of ordered pairs (x, y), where f(x) = y. In the common case where x and f(x) are real numbers, these pairs are Cartesian coordinates of points in a plane (geometry), plane and often form a P ...
. There may not be a single function whose graph can represent the entire relation, but there may be such a function on a restriction of the domain of the relation. The implicit function theorem gives a sufficient condition to ensure that there is such a function. More precisely, given a system of equations (often abbreviated into ), the theorem states that, under a mild condition on the
partial derivative In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). P ...
s (with respect to each ) at a point, the variables are differentiable functions of the in some
neighborhood A neighbourhood (Commonwealth English) or neighborhood (American English) is a geographically localized community within a larger town, city, suburb or rural area, sometimes consisting of a single street and the buildings lining it. Neigh ...
of the point. As these functions generally cannot be expressed in closed form, they are ''implicitly'' defined by the equations, and this motivated the name of the theorem. In other words, under a mild condition on the partial derivatives, the set of zeros of a system of equations is locally the
graph of a function In mathematics, the graph of a function f is the set of ordered pairs (x, y), where f(x) = y. In the common case where x and f(x) are real numbers, these pairs are Cartesian coordinates of points in a plane (geometry), plane and often form a P ...
.


History

Augustin-Louis Cauchy Baron Augustin-Louis Cauchy ( , , ; ; 21 August 1789 – 23 May 1857) was a French mathematician, engineer, and physicist. He was one of the first to rigorously state and prove the key theorems of calculus (thereby creating real a ...
(1789–1857) is credited with the first rigorous form of the implicit function theorem. Ulisse Dini (1845–1918) generalized the real-variable version of the implicit function theorem to the context of functions of any number of real variables.


Two variables case

Let f:\R^2 \to \R be a continuously differentiable function defining the
implicit equation In mathematics, an implicit equation is a relation of the form R(x_1, \dots, x_n) = 0, where is a function of several variables (often a polynomial). For example, the implicit equation of the unit circle is x^2 + y^2 - 1 = 0. An implicit func ...
of a
curve In mathematics, a curve (also called a curved line in older texts) is an object similar to a line, but that does not have to be straight. Intuitively, a curve may be thought of as the trace left by a moving point. This is the definition that ...
f(x,y) = 0 . Let (x_0, y_0) be a point on the curve, that is, a point such that f(x_0, y_0)=0. In this simple case, the implicit function theorem can be stated as follows: Proof. By differentiating the equation , one gets \frac(x, \varphi(x))+\varphi'(x)\, \frac(x, \varphi(x))=0. and thus \varphi'(x)=-\frac. This gives an
ordinary differential equation In mathematics, an ordinary differential equation (ODE) is a differential equation (DE) dependent on only a single independent variable (mathematics), variable. As with any other DE, its unknown(s) consists of one (or more) Function (mathematic ...
for , with the initial condition . Since \frac (x_0, y_0) \neq 0, the right-hand side of the differential equation is continuous. Hence, the
Peano existence theorem In mathematics, specifically in the study of ordinary differential equations, the Peano existence theorem, Peano theorem or Cauchy–Peano theorem, named after Giuseppe Peano and Augustin-Louis Cauchy, is a fundamental theorem which guarantees th ...
applies so there is a (possibly non-unique) solution. To see why \varphi is unique, note that the function g_x(y)=f(x,y) is strictly monotone in a neighborhood of x_0,y_0 (as \frac (x_0, y_0) \neq 0), thus it is
injective In mathematics, an injective function (also known as injection, or one-to-one function ) is a function that maps distinct elements of its domain to distinct elements of its codomain; that is, implies (equivalently by contraposition, impl ...
. If \varphi,\phi are solutions to the differential equation, then g_x(\varphi(x))=g_x(\phi(x))=0 and by injectivity we get, \varphi(x)=\phi(x) .


First example

If we define the function , then the equation cuts out the
unit circle In mathematics, a unit circle is a circle of unit radius—that is, a radius of 1. Frequently, especially in trigonometry, the unit circle is the circle of radius 1 centered at the origin (0, 0) in the Cartesian coordinate system in the Eucli ...
as the level set . There is no way to represent the unit circle as the graph of a function of one variable because for each choice of , there are two choices of ''y'', namely \pm\sqrt. However, it is possible to represent ''part'' of the circle as the graph of a function of one variable. If we let g_1(x) = \sqrt for , then the graph of provides the upper half of the circle. Similarly, if g_2(x) = -\sqrt, then the graph of gives the lower half of the circle. The purpose of the implicit function theorem is to tell us that functions like and almost always exist, even in situations where we cannot write down explicit formulas. It guarantees that and are differentiable, and it even works in situations where we do not have a formula for .


Definitions

Let f: \R^ \to \R^m be a continuously differentiable function. We think of \R^ as the
Cartesian product In mathematics, specifically set theory, the Cartesian product of two sets and , denoted , is the set of all ordered pairs where is an element of and is an element of . In terms of set-builder notation, that is A\times B = \. A table c ...
\R^n\times\R^m, and we write a point of this product as (\mathbf, \mathbf) = (x_1,\ldots, x_n, y_1, \ldots y_m). Starting from the given function f, our goal is to construct a function g: \R^n \to \R^m whose graph (\textbf, g(\textbf)) is precisely the set of all (\textbf, \textbf) such that f(\textbf, \textbf) = \textbf. As noted above, this may not always be possible. We will therefore fix a point (\textbf, \textbf) = (a_1, \dots, a_n, b_1, \dots, b_m) which satisfies f(\textbf, \textbf) = \textbf, and we will ask for a g that works near the point (\textbf, \textbf). In other words, we want an
open set In mathematics, an open set is a generalization of an Interval (mathematics)#Definitions_and_terminology, open interval in the real line. In a metric space (a Set (mathematics), set with a metric (mathematics), distance defined between every two ...
U \subset \R^n containing \textbf, an open set V \subset \R^m containing \textbf, and a function g : U \to V such that the graph of g satisfies the relation f = \textbf on U\times V, and that no other points within U \times V do so. In symbols, \ = \. To state the implicit function theorem, we need the
Jacobian matrix In vector calculus, the Jacobian matrix (, ) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. If this matrix is square, that is, if the number of variables equals the number of component ...
of f, which is the matrix of the
partial derivative In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). P ...
s of f. Abbreviating (a_1, \dots, a_n, b_1, \dots, b_m) to (\textbf, \textbf), the Jacobian matrix is (Df)(\mathbf,\mathbf) = \left[\begin \frac(\mathbf,\mathbf) & \cdots & \frac(\mathbf,\mathbf) & \frac(\mathbf,\mathbf) & \cdots & \frac(\mathbf,\mathbf) \\ \vdots & \ddots & \vdots & \vdots & \ddots & \vdots \\ \frac(\mathbf,\mathbf) & \cdots & \frac(\mathbf,\mathbf) & \frac(\mathbf,\mathbf) & \cdots & \frac(\mathbf,\mathbf) \end\right] = \left[\begin X & Y \end\right] where X is the matrix of partial derivatives in the variables x_i and Y is the matrix of partial derivatives in the variables y_j. The implicit function theorem says that if Y is an invertible matrix, then there are U, V, and g as desired. Writing all the hypotheses together gives the following statement.


Statement of the theorem

Let f: \R^ \to \R^m be a continuously differentiable function, and let \R^ have coordinates (\textbf, \textbf). Fix a point (\textbf, \textbf) = (a_1,\dots,a_n, b_1,\dots, b_m) with f(\textbf, \textbf) = \mathbf, where \mathbf \in \R^m is the zero vector. If the
Jacobian matrix In vector calculus, the Jacobian matrix (, ) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. If this matrix is square, that is, if the number of variables equals the number of component ...
(this is the right-hand panel of the Jacobian matrix shown in the previous section): J_ (\mathbf, \mathbf) = \left \frac (\mathbf, \mathbf) \right /math> is
invertible In mathematics, the concept of an inverse element generalises the concepts of opposite () and reciprocal () of numbers. Given an operation denoted here , and an identity element denoted , if , one says that is a left inverse of , and that ...
, then there exists an open set U \subset \R^n containing \textbf such that there exists a unique function g: U \to \R^m such that and Moreover, g is continuously differentiable and, denoting the left-hand panel of the Jacobian matrix shown in the previous section as: J_ (\mathbf, \mathbf) = \left \frac (\mathbf, \mathbf) \right the Jacobian matrix of partial derivatives of g in U is given by the matrix product: \left frac (\mathbf)\right =- \left J_(\mathbf, g(\mathbf)) \right ^ \, \left J_(\mathbf, g(\mathbf)) \right For a proof, see Inverse function theorem#Implicit_function_theorem. Here, the two-dimensional case is detailed.


Higher derivatives

If, moreover, f is analytic or continuously differentiable k times in a neighborhood of (\textbf, \textbf), then one may choose U in order that the same holds true for g inside U. In the analytic case, this is called the analytic implicit function theorem.


The circle example

Let us go back to the example of the
unit circle In mathematics, a unit circle is a circle of unit radius—that is, a radius of 1. Frequently, especially in trigonometry, the unit circle is the circle of radius 1 centered at the origin (0, 0) in the Cartesian coordinate system in the Eucli ...
. In this case ''n'' = ''m'' = 1 and f(x,y) = x^2 + y^2 - 1. The matrix of partial derivatives is just a 1 × 2 matrix, given by (Df)(a,b) = \begin \dfrac(a,b) & \dfrac(a,b) \end = \begin 2a & 2b \end Thus, here, the in the statement of the theorem is just the number ; the linear map defined by it is invertible
if and only if In logic and related fields such as mathematics and philosophy, "if and only if" (often shortened as "iff") is paraphrased by the biconditional, a logical connective between statements. The biconditional is true in two cases, where either bo ...
. By the implicit function theorem we see that we can locally write the circle in the form for all points where . For we run into trouble, as noted before. The implicit function theorem may still be applied to these two points, by writing as a function of , that is, x = h(y); now the graph of the function will be \left(h(y), y\right), since where we have , and the conditions to locally express the function in this form are satisfied. The implicit derivative of ''y'' with respect to ''x'', and that of ''x'' with respect to ''y'', can be found by totally differentiating the implicit function x^2+y^2-1 and equating to 0: 2x\, dx+2y\, dy = 0, giving \frac=-\frac and \frac = -\frac.


Application: change of coordinates

Suppose we have an -dimensional space, parametrised by a set of coordinates (x_1,\ldots,x_m) . We can introduce a new coordinate system (x'_1,\ldots,x'_m) by supplying m functions h_1\ldots h_m each being continuously differentiable. These functions allow us to calculate the new coordinates (x'_1,\ldots,x'_m) of a point, given the point's old coordinates (x_1,\ldots,x_m) using x'_1=h_1(x_1,\ldots,x_m), \ldots, x'_m=h_m(x_1,\ldots,x_m) . One might want to verify if the opposite is possible: given coordinates (x'_1,\ldots,x'_m) , can we 'go back' and calculate the same point's original coordinates (x_1,\ldots,x_m) ? The implicit function theorem will provide an answer to this question. The (new and old) coordinates (x'_1,\ldots,x'_m, x_1,\ldots,x_m) are related by ''f'' = 0, with f(x'_1,\ldots,x'_m,x_1,\ldots, x_m)=(h_1(x_1,\ldots, x_m)-x'_1,\ldots , h_m(x_1,\ldots, x_m)-x'_m). Now the Jacobian matrix of ''f'' at a certain point (''a'', ''b'') where a=(x'_1,\ldots,x'_m), b=(x_1,\ldots,x_m) is given by (Df)(a,b) = \left \begin \frac(b) & \cdots & \frac(b)\\ \vdots & \ddots & \vdots\\ \frac(b) & \cdots & \frac(b)\\ \end \right.\right= J where I''m'' denotes the ''m'' × ''m''
identity matrix In linear algebra, the identity matrix of size n is the n\times n square matrix with ones on the main diagonal and zeros elsewhere. It has unique properties, for example when the identity matrix represents a geometric transformation, the obje ...
, and is the matrix of partial derivatives, evaluated at (''a'', ''b''). (In the above, these blocks were denoted by X and Y. As it happens, in this particular application of the theorem, neither matrix depends on ''a''.) The implicit function theorem now states that we can locally express (x_1,\ldots,x_m) as a function of (x'_1,\ldots,x'_m) if ''J'' is invertible. Demanding ''J'' is invertible is equivalent to det ''J'' ≠ 0, thus we see that we can go back from the primed to the unprimed coordinates if the determinant of the Jacobian ''J'' is non-zero. This statement is also known as the inverse function theorem.


Example: polar coordinates

As a simple application of the above, consider the plane, parametrised by
polar coordinates In mathematics, the polar coordinate system specifies a given point (mathematics), point in a plane (mathematics), plane by using a distance and an angle as its two coordinate system, coordinates. These are *the point's distance from a reference ...
. We can go to a new coordinate system (
cartesian coordinates In geometry, a Cartesian coordinate system (, ) in a plane is a coordinate system that specifies each point uniquely by a pair of real numbers called ''coordinates'', which are the signed distances to the point from two fixed perpendicular o ...
) by defining functions and . This makes it possible given any point to find corresponding Cartesian coordinates . When can we go back and convert Cartesian into polar coordinates? By the previous example, it is sufficient to have , with J =\begin \frac & \frac \\ \frac & \frac \\ \end= \begin \cos \theta & -R \sin \theta \\ \sin \theta & R \cos \theta \end. Since , conversion back to polar coordinates is possible if . So it remains to check the case . It is easy to see that in case , our coordinate transformation is not invertible: at the origin, the value of θ is not well-defined.


Generalizations


Banach space version

Based on the inverse function theorem in
Banach space In mathematics, more specifically in functional analysis, a Banach space (, ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vectors and ...
s, it is possible to extend the implicit function theorem to Banach space valued mappings. Let ''X'', ''Y'', ''Z'' be
Banach space In mathematics, more specifically in functional analysis, a Banach space (, ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vectors and ...
s. Let the mapping be continuously Fréchet differentiable. If (x_0,y_0)\in X\times Y, f(x_0,y_0)=0, and y\mapsto Df(x_0,y_0)(0,y) is a Banach space isomorphism from ''Y'' onto ''Z'', then there exist neighbourhoods ''U'' of ''x''0 and ''V'' of ''y''0 and a Fréchet differentiable function ''g'' : ''U'' → ''V'' such that ''f''(''x'', ''g''(''x'')) = 0 and ''f''(''x'', ''y'') = 0 if and only if ''y'' = ''g''(''x''), for all (x,y)\in U\times V.


Implicit functions from non-differentiable functions

Various forms of the implicit function theorem exist for the case when the function ''f'' is not differentiable. It is standard that local strict monotonicity suffices in one dimension. The following more general form was proven by Kumagai based on an observation by Jittorntrum. Consider a continuous function f : \R^n \times \R^m \to \R^n such that f(x_0, y_0) = 0. If there exist open neighbourhoods A \subset \R^n and B \subset \R^m of ''x''0 and ''y''0, respectively, such that, for all ''y'' in ''B'', f(\cdot, y) : A \to \R^n is locally one-to-one, then there exist open neighbourhoods A_0 \subset \R^n and B_0 \subset \R^m of ''x''0 and ''y''0, such that, for all y \in B_0, the equation ''f''(''x'', ''y'') = 0 has a unique solution x = g(y) \in A_0, where ''g'' is a continuous function from ''B''0 into ''A''0.


Collapsing manifolds

Perelman’s collapsing theorem for
3-manifold In mathematics, a 3-manifold is a topological space that locally looks like a three-dimensional Euclidean space. A 3-manifold can be thought of as a possible shape of the universe. Just as a sphere looks like a plane (geometry), plane (a tangent ...
s, the capstone of his proof of Thurston's geometrization conjecture, can be understood as an extension of the implicit function theorem.


See also

* Inverse function theorem * Constant rank theorem: Both the implicit function theorem and the inverse function theorem can be seen as special cases of the constant rank theorem.


Notes


References


Further reading

* * * * {{DEFAULTSORT:Implicit Function Theorem Articles containing proofs Mathematical identities Theorems in calculus Theorems in real analysis