Calculus III: Confused about Critical Points of f(x,y)?

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SUMMARY

The discussion centers on finding and classifying critical points of the function f(x,y) = 5 - 10xy - 4x² + 3y - y⁴ using Mathematica. Participants clarify that critical points are classified as minima, maxima, or saddle points based on the discriminant D, calculated from the second partial derivatives. The formula for D is D = fxx * fyy - (fxy)², where fxx, fyy, and fxy are the second partial derivatives. Understanding this concept is essential for solving calculus problems involving functions of multiple variables.

PREREQUISITES
  • Understanding of partial derivatives in multivariable calculus
  • Familiarity with critical points and their classifications
  • Knowledge of the Hessian matrix and its determinant
  • Basic proficiency in using Mathematica for mathematical computations
NEXT STEPS
  • Study the concept of critical points in multivariable calculus
  • Learn how to compute second partial derivatives for functions of two variables
  • Explore the application of the Hessian matrix in determining the nature of critical points
  • Practice using Mathematica for solving calculus problems involving critical points
USEFUL FOR

Students in Calculus III, educators teaching multivariable calculus, and anyone seeking to understand the classification of critical points in functions of two variables.

Pengwuino
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Ok so i got a mathematica assignment that asks "Find and classify the critical points of f(x,y)= 5-10xy-4x^2+3y-y^4

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!
 
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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 f(x,y) of two real variables with equal mixed second partial derivatives (ie. \frac{\partial^2 f}{\partial x \partial y} = \frac{\partial^2 f}{\partial y \partial x}), the quantity

\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

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

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

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|

Daniel.
 
I would say it means "open your textbook and look up "critical point" (or "critical number")! It's not spring break anymore!
 
It is to me,that's why I'm on PF...:-p

Daniel.
 

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