[Math] How would you find and classify ALL of the critical points of a function of 2 variables

multivariable-calculus

Suppose you had the function $f(x,y)=x^{3}-y^{3}+9xy$.
The critical points of this function would be the values of $(x,y)$, such that $f_{x}=f_{y}=0$.

We have $f_{x}=3x^{2}+9y$ and $f_{y}=-3y^{2}+9x$
So, to find the stationary points we need to solve We have $3x^{2}+9y=0$ and $-3y^{2}+9x=0$ simultaneously.

How would you solve these equations in a way that ensures that no solutions are lost?

Also, once you've found all of the critical points, how would you classify them?

Best Answer

To find the critical points, solve the simultaneous equations

$$f_x=3x^2+9y \tag{1}$$ $$f_y=-3y^2+9x \tag{2}$$

From (2), without introducing additional solutions or losing any, we get $x=\tfrac{1}{3}y^2$, so by substituting into (1):

$$\tfrac{1}{3}y^4+9y=0 \iff \tfrac{1}{3}y(y+3)(y^2-3y+9)=0$$

The quadratic term has no real roots, so the only solutions are $y=0,-3$, so solutions are:

$$(x,y)\in\{(0,0),(3,-3)\}$$

To find the nature of the critical points, you will need the partial derivatives of $f(x,y)$. These are:

$$\begin{align} f_{xx} &= \frac{\partial}{\partial x}f_x&=6x \\[2ex] f_{yy} &= \frac{\partial}{\partial y}f_y&=-6y \\[2ex] f_{xy} &= \frac{\partial}{\partial x}f_y&=9 \end{align}$$

Then conduct the second partial derivative test - as uniquesolution has commented, this involves the Hessian. In short, the sign of the determinant $D(x,y)$ and the sign of either $f_{xx}$ or $f_{yy}$ (your choice) determines the nature of the critical point. Wikipedia is a good source for this.

Now

$$D(x,y)=f_{xx}f_{yy}-(f_{xy})^2=-36xy-81$$

So for the two critical points:

  1. $(0,0)$: $D(0,0)=-81$ which is negative, so $(0,0)$ is a saddle point.
  2. $(3,-3)$: $D(3,-3)=(-36)(-9)-81=243$ which is positive, so look at the sign of $f_{xx}$ at $(3,-3)$ which is $6(3)=18$ and positive, so this point is a local maximum.

Addendum: Other Cases

A. $D(x,y)=0$

Many of the ideas in this section (and the first two examples) are taken from https://www3.nd.edu/~eburkard/Teaching/20550%20F13/Second%20Derivatives%20Test.pdf.

When the determinant is zero, the Hessian matrix is said to be degenerate. I know of no higher-order (third derivatives or higher) test that can determine the nature of the critical points. Several examples will show that behaviour can vary markedly in cases where $f_x=f_y=D(x,y)=0$ at a critical point:

  1. $f(x,y)=-(x-y)^2$. Here there is a line of critical points $y=x$ along which $f(x,y)=0$. This is the maximum possible value of $f$.
  2. $f(x,y)=x^3+y^3$. In every nbhd of $(0,0)$ there are points where $f>0$ (wherever $(x,y)\text{ s.t. }x+y>0$) and points where $f<0$ (wherever $(x,y)\text{ s.t. }x+y<0$) so this is not a local min or max. It's not really a saddle point either.
  3. $f(x,y)=x^4+y^4$. It is clear that $(0,0)$ is a local minimum in this case.

B. $D(x,y)>0\text{ and }f_{xx}=0$

When $f_{xx}=0$ we have $D(x,y)=f_{xx}f_{yy}-(f_{xy})^2=0-(f_{xy})^2\le 0$, so this case is not possible.

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