How do you find and classify critical points of f(x,y)?

Join the discussion
Registration is free. Start your own thread to ask a follow-up.
4 replies · 6K views
Pengwuino
Gold Member
Messages
5,112
Reaction score
20
Ok so i got a mathematica assignment that asks "Find and classify the critical points of [tex]f(x,y)= 5-10xy-4x^2+3y-y^4[/tex]

What does this mean lol. The assignment was from 3 weeks ago and i just had spring break so my brain is completely outa wack. Does this mean classify the points as concave up and down or what? This is calculus III by the way. If someone can just lol, tell me what I am being asked that would be great.

In the exercise before it we found fxx and fyy and fxy of a similar equation and then we found fxx*fyy - (fxy)^2. I am so lost lol. What is this partial derivative thing. Whats the fxx partial derivative * fxy - (fxy)^2 all about? I feel so dumb, my high school calculus teacher would be so dissappointed!
 
Physics news on Phys.org
Classify the critical points as minima, maxima, or saddle points.

A partial derivative is a derivative of a function of multiple variables taken as if all but one of the variables are held constant (well, in some cases it's slightly more complicated. But just slightly!).

For a differentiable function [itex]f(x,y)[/itex] of two real variables with equal mixed second partial derivatives (ie. [tex]\frac{\partial^2 f}{\partial x \partial y} = \frac{\partial^2 f}{\partial y \partial x}[/tex]), the quantity

[tex]\frac{\partial^2 f}{\partial x^2}\frac{\partial^2 f}{\partial y^2} - \left(\frac{\partial^2 f}{\partial x \partial y}\right)^2 = D[/tex]

is called the discriminant of [itex]f[/itex]. If [itex]P = (x_0, y_0)[/itex] is a critical point of [itex]f[/itex], then [itex]P[/itex] is a minimum or maximum if [itex]D>0[/itex] and a saddle point if [itex]D<0[/itex], where [itex]D[/itex] is evaluated at [itex]P[/itex]. If [itex]D=0[/itex] then it tells you nothing. These facts can be proved using from the Taylor expansion of [itex]f[/itex] for analytic functions.
 
Relative minima,maxima & saddle points.

And that "D" is actually the functions's hessian.It's a determinant

[tex]D=\left|\begin{array}{cc}\frac{\partial^{2}f}{\partial x\partial x}&\frac{\partial^{2}f}{\partial x\partial y}\\ \frac{\partial^{2}f}{\partial y\partial x}&\frac{\partial^{2}f}{\partial y\partial y}\end{array}\right|[/tex]

Daniel.
 
I would say it means "open your textbook and look up "critical point" (or "critical number")! It's not spring break anymore!