Multivariable calculus
Part of a series of articles about  
Calculus  







Specialized 

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, rather than just one.^{[1]}
Typical operations
Limits and continuity
A study of limits and continuity in multivariable calculus yields many counterintuitive results not demonstrated by singlevariable functions.^{[1]}^{:19–22} For example, there are scalar functions of two variables with points in their domain which give different limits when approached along different paths. E.g., the function
approaches zero, whenever the point (0,0) is approached along lines through the origin (y = kx). However, when the origin is approached along a parabola , the function value has a limit of . Since taking different paths toward the same point yields different limit values, a general limit does not exist there.
Continuity in each argument not being sufficient for multivariate continuity can also be seen from the following example.^{[1]}^{:17–19} In particular, for a realvalued function with two realvalued parameters, , continuity of in for fixed and continuity of in for fixed does not imply continuity of .
Consider
It is easy to verify that this function is zero by definition on the boundary and outside of the quadrangle . Furthermore, the functions defined for constant x and y and by
 and
are continuous. Specifically,
 for all x and y.
However, the sequence (for natural ) converges to , rendering the function as discontinuous at Approaching the origin not along parallels to the x and yaxis reveals this discontinuity.
Partial differentiation
The partial derivative generalizes the notion of the derivative to higher dimensions. A partial derivative of a multivariable function is a derivative with respect to one variable with all other variables held constant.^{[1]}^{:26ff}
Partial derivatives may be combined in interesting ways to create more complicated expressions of the derivative. In vector calculus, the del operator ( ) is used to define the concepts of gradient, divergence, and curl in terms of partial derivatives. A matrix of partial derivatives, the Jacobian matrix, may be used to represent the derivative of a function between two spaces of arbitrary dimension. The derivative can thus be understood as a linear transformation which directly varies from point to point in the domain of the function.
Differential equations containing partial derivatives are called partial differential equations or PDEs. These equations are generally more difficult to solve than ordinary differential equations, which contain derivatives with respect to only one variable.^{[1]}^{:654ff}
Multiple integration
The multiple integral expands the concept of the integral to functions of any number of variables. Double and triple integrals may be used to calculate areas and volumes of regions in the plane and in space. Fubini's theorem guarantees that a multiple integral may be evaluated as a repeated integral or iterated integral as long as the integrand is continuous throughout the domain of integration.^{[1]}^{:367ff}
The surface integral and the line integral are used to integrate over curved manifolds such as surfaces and curves.
Fundamental theorem of calculus in multiple dimensions
In singlevariable calculus, the fundamental theorem of calculus establishes a link between the derivative and the integral. The link between the derivative and the integral in multivariable calculus is embodied by the integral theorems of vector calculus:^{[1]}^{:543ff}
In a more advanced study of multivariable calculus, it is seen that these four theorems are specific incarnations of a more general theorem, the generalized Stokes' theorem, which applies to the integration of differential forms over manifolds.^{[2]}
Applications and uses
Techniques of multivariable calculus are used to study many objects of interest in the material world. In particular,
Type of functions  Applicable techniques  

Curves 
for  Lengths of curves, line integrals, and curvature.  
Surfaces 
for  Areas of surfaces, surface integrals, flux through surfaces, and curvature.  
Scalar fields  Maxima and minima, Lagrange multipliers, directional derivatives, level sets.  
Vector fields  Any of the operations of vector calculus including gradient, divergence, and curl. 
Multivariable calculus can be applied to analyze deterministic systems that have multiple degrees of freedom. Functions with independent variables corresponding to each of the degrees of freedom are often used to model these systems, and multivariable calculus provides tools for characterizing the system dynamics.
Multivariate calculus is used in the optimal control of continuous time dynamic systems. It is used in regression analysis to derive formulas for estimating relationships among various sets of empirical data.
Multivariable calculus is used in many fields of natural and social science and engineering to model and study highdimensional systems that exhibit deterministic behavior. In economics, for example, consumer choice over a variety of goods, and producer choice over various inputs to use and outputs to produce, are modeled with multivariate calculus. Quantitative analysts in finance also often use multivariate calculus to predict future trends in the stock market.
Nondeterministic, or stochastic systems can be studied using a different kind of mathematics, such as stochastic calculus.
See also
Wikimedia Commons has media related to Multivariate calculus. 
References
External links
 UC Berkeley video lectures on Multivariable Calculus, Fall 2009, Professor Edward Frenkel
 MIT video lectures on Multivariable Calculus, Fall 2007
 Multivariable Calculus: A free online textbook by George Cain and James Herod
 Multivariable Calculus Online: A free online textbook by Jeff Knisley
 Multivariable Calculus – A Very Quick Review, Prof Blair Perot, University of Massachusetts Amherst