Learning Objectives
- Use partial derivatives to locate critical points for a function of two variables.
For functions of a single variable, we defined critical points as the values of the function when the derivative equals zero or does not exist. For functions of two or more variables, the concept is essentially the same, except for the fact that we are now working with partial derivatives.
Definition
Let [latex]z=f(x, y)[/latex] be a function of two variables that is defined on an open set containing the point [latex](x_0, y_0)[/latex]. The point [latex](x_0, y_0)[/latex] is called a critical point of a function of two variables [latex]f[/latex] if one of the two following conditions holds:
- [latex]f_x=(x_0, y_0)=f_y(x_0, y_0)=0[/latex]
- Either [latex]f_x(x_0, y_0)[/latex] or [latex]f_y(x_0, y_0)[/latex] does not exist.
Example: Finding critical points
Find the critical points of each of the following functions:
a. [latex]f(x,y)=\sqrt{4y^2-9x^2+24y+36x+36}[/latex]
b. [latex]g(x,y)=x^2+2xy-4y^2+4x-6y+4[/latex]
try it
Find the critical point of the function [latex]f(x, y)=x^{3}+2xy-2x-4y[/latex].
Watch the following video to see the worked solution to the above Try It
Definition
Let [latex]z=f(x, y)[/latex] be a function of two variables that is defined and continuous on an open set containing the point [latex](x_0, y_0)[/latex]. Then [latex]f[/latex] has a local maximum at [latex](x_0, y_0)[/latex] if
[latex]f(x_0, y_0)\geq f(x, y)[/latex]
for all points [latex](x, y)[/latex] within some disk centered at [latex](x_0, y_0)[/latex]. The number [latex]f(x_0, y_0)[/latex] is called a local maximum value. If the preceding inequality holds for every point [latex](x, y)[/latex] in the domain of [latex]f[/latex], then [latex]f[/latex] has a global maximum (also called an absolute maximum) at [latex](x_0, y_0)[/latex].
The function [latex]f[/latex] has a local minimum at [latex](x_0, y_0)[/latex] if
[latex]f(x_0, y_0)\leq f(x, y)[/latex]
for all points [latex](x, y)[/latex] within some disk centered at [latex](x_0, y_0)[/latex]. The number [latex]f(x_0, y_0)[/latex] is called a local minimum value. If the preceding inequality holds for every point [latex](x, y)[/latex] in the domain of [latex]f[/latex], then [latex]f[/latex] has a global minimum (also called an absolute minimum) at [latex](x_0, y_0)[/latex].
If [latex]f(x_0, y_0)[/latex] is either a local maximum or local minimum value, then it is called a local extremum (see the following figure).
In Maxima and Minima, we showed that extrema of functions of one variable occur at critical points. The same is true for functions of more than one variable, as stated in the following theorem.
Theorem: Fermat’s theorem for functions of two variables
Let [latex]z=f(x, y)[/latex] be a function of two variables that is defined and continuous on an open set containing the point [latex](x_0, y_0)[/latex]. Suppose [latex]f_x[/latex] and [latex]f_y[/latex] each exists at [latex](x_0, y_0)[/latex]. If [latex]f[/latex] has a local extremum at [latex](x_0, y_0)[/latex], then [latex](x_0, y_0)[/latex] is a critical point of [latex]f[/latex].