Implicit function
In mathematics, an implicit equation is a relation of the form , where is a function of several variables (often a polynomial). For example, the implicit equation of the unit circle is . An implicit function is a function that is defined by an implicit equation, that relates one of the variables, considered as the value of the function, with the others considered as the arguments. For example, the equation of the unit circle defines as an implicit function of if , and one restricts to nonnegative values. The implicit function theorem provides conditions under which some kinds of relations define  an implicit function, namely relations defined as the indicator function of the zero set of some continuously differentiable multivariate function. Examples. Inverse functions. A common type of implicit function is an inverse function. Not all functions have a unique inverse function. If is a function of that has a unique inverse, then the inverse function of , called , is the unique function giving a solution of the equation for in terms of . This solution can then be written as Defining as the inverse of is an implicit definition. For some functions , can be written out explicitly as a closed-form expression  — for instance, if , then . However, this is often not possible, or only by introducing a new notation (as in the product log example below). Intuitively, an inverse function is obtained from by interchanging the roles of the dependent and independent variables. Example: The product log is an implicit function giving the solution for of the equation . Algebraic functions. An algebraic function is a function that satisfies a polynomial equation whose coefficients are themselves polynomials. For example, an algebraic function in one variable gives a solution for of an equation where the coefficients are polynomial functions of . This algebraic function can  be written as the right side of the solution equation . Written like this, is a multi-valued implicit function. Algebraic functions play an important role in mathematical analysis and algebraic geometry. A simple example of an algebraic function is given by the left side of the unit circle equation: Solving for gives an explicit solution: But even without specifying this explicit solution, it is possible to refer to the implicit solution of the unit circle equation as , where is the multi-valued implicit function. While explicit solutions can be found for equations that are quadratic, cubic, and quartic in , the  same is not in general true for quintic and higher degree equations, such as Nevertheless, one can still refer to the implicit solution involving the multi-valued implicit function . Caveats. Not every equation implies a graph of a single-valued function, the circle equation being one prominent example. Another example is an implicit function given by where is a cubic polynomial having a "hump" in its graph. Thus, for an implicit function to be a "true" (single-valued) function it might be necessary to use just part of the graph. An implicit function can sometimes be successfully defined as a  true function only after "zooming in" on some part of the -axis and "cutting away" some unwanted function branches. Then an equation expressing as an implicit function of the other variables can be written. The defining equation can also have other pathologies. For example, the equation does not imply a function giving solutions for at all; it is a vertical line. In order to avoid a problem like this, various constraints are frequently imposed on the allowable sorts of equations or on the domain. The implicit function theorem provides a uniform way of handling these sorts of pathologies. Implicit differentiation . In calculus, a method called implicit differentiation makes use of the chain rule to differentiate implicitly defined functions. To differentiate an implicit function , defined by an equation , it is not generally possible to solve it explicitly for and then differentiate. Instead, one can totally differentiate with respect to and and then solve the resulting linear equation for to explicitly get the derivative in terms of and . Even when it is possible to explicitly solve the original equation, the formula resulting from total differentiation is, in general, much simpler and easier to use. Examples. Example 1. Consider This equation is easy  to solve for , giving where the right side is the explicit form of the function . Differentiation then gives . Alternatively, one can totally differentiate the original equation: Solving for gives the same answer as obtained previously. Example 2. An example of an implicit function for which implicit differentiation is easier than using explicit differentiation is the function defined by the equation To differentiate this explicitly with respect to , one has first to get and then differentiate this function. This creates two derivatives: one for and another for . It is substantially easier to implicitly differentiate the original equation: giving Example 3. Often , it is difficult or impossible to solve explicitly for , and implicit differentiation is the only feasible method of differentiation. An example is the equation It is impossible to algebraically express explicitly as a function of , and therefore one cannot find by explicit differentiation. Using the implicit method, can be obtained by differentiating the equation to obtain where . Factoring out shows that which yields the result which is defined for General formula for derivative of implicit function. If , the derivative of the implicit function is given by where and indicate the partial derivatives of with respect to and . The above  formula comes from using the generalized chain rule to obtain the total derivative — with respect to — of both sides of : hence which, when solved for , gives the expression above. Implicit function theorem. Let be a differentiable function of two variables, and be a pair of real numbers such that . If , then defines an implicit function that is differentiable in some small enough neighbourhood of ; in other words, there is a differentiable function that is defined and differentiable in some neighbourhood of , such that for in this neighbourhood. The condition means that is a regular point of the implicit curve of  implicit equation where the tangent is not vertical. In a less technical language, implicit functions exist and can be differentiated, if the curve has a non-vertical tangent. In algebraic geometry. Consider a relation of the form , where is a multivariable polynomial. The set of the values of the variables that satisfy this relation is called an implicit curve if and an implicit surface if . The implicit equations are the basis of algebraic geometry, whose basic subjects of study are the simultaneous solutions of several implicit equations whose left-hand sides are polynomials. These sets of simultaneous solutions are called  affine algebraic sets. In differential equations. The solutions of differential equations generally appear expressed by an implicit function. Applications in economics. Marginal rate of substitution. In economics, when the level set is an indifference curve for the quantities and consumed of two goods, the absolute value of the implicit derivative is interpreted as the marginal rate of substitution of the two goods: how much more of one must receive in order to be indifferent to a loss of one unit of . Marginal rate of technical substitution. Similarly, sometimes the level set is an isoquant showing various combinations of utilized quantities  of labor and of physical capital each of which would result in the production of the same given quantity of output of some good. In this case the absolute value of the implicit derivative is interpreted as the marginal rate of technical substitution between the two factors of production: how much more capital the firm must use to produce the same amount of output with one less unit of labor. Optimization. Often in economic theory, some function such as a utility function or a profit function is to be maximized with respect to a choice vector even though the objective  function has not been restricted to any specific functional form. The implicit function theorem guarantees that the first-order conditions of the optimization define an implicit function for each element of the optimal vector of the choice vector . When profit is being maximized, typically the resulting implicit functions are the labor demand function and the supply functions of various goods. When utility is being maximized, typically the resulting implicit functions are the labor supply function and the demand functions for various goods. Moreover, the influence of the problem's parameters on — the partial derivatives of the implicit function — can be  expressed as total derivatives of the system of first-order conditions found using total differentiation.