Critical Points in the First Quadrant

In summary, the author is trying to figure out whether a point (x,y) is a local maximum or minimum based on the sign of the partial derivatives of f_x and f_y with respect to x and y, respectively. If M > 0, then the point is a local maximum. If M < 0 and f_xx and f_yy have the same sign, then the point is a local minimum. If M < 0 and f_xx and f_yy have different signs, then the point is a saddle point.
  • #1
jegues
1,097
3

Homework Statement


See figure.


Homework Equations


N/A.


The Attempt at a Solution



Part A:

The volume is,

[tex] xyz = xy(1 - x^{2} - y^{2}) [/tex]

Critical points:
[tex]f_{x} = y-3x^{2}y-y^{3} = 0 [/tex]

[tex]f_{y} = x -x^{3} - 3xy^{2} = 0[/tex]

Part B:

This is where I get confused, how do I find the critical point in the first quadrant assuming x>0 and y>0 ?

NOTE: I haven't gotten to parts C and D yet, I'll update this thread as I go.
 

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  • #2
jegues said:
Critical points:
[tex]f_{x} = y-3x^{2}y-y^{3} = 0 [/tex]

[tex]f_{y} = x -x^{3} - 3xy^{2} = 0[/tex]

Part B:

This is where I get confused, how do I find the critical point in the first quadrant assuming x>0 and y>0 ?

Set [tex] f_x = f_y = 0. [/tex] Since x and y are not zero here, we can divide f_x by y and f_y by x, giving us:

[tex]f_{x} = 0 = 1 - 3x^2 - y^2 = 0 [/tex]

[tex]f_{y} = 0 = 1 - x^2 - 3y^2 = 0 [/tex]

You should be able to find an (x,y) that satisfies these equations easily. [STRIKE]In reality, there are an infinite number of such points that would work.[/STRIKE] Ignore that last bit, idk what I was thinking xD...
 
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  • #3
[tex] x^{2}=y^{2}= \frac{1}{4}[/tex]

Therefore,

[tex] (x,y) = (\frac{1}{2},\frac{1}{2})[/tex]

I'll keep updating this thread as I progress through the other parts.

Thanks again!
 
  • #4
Yep, that works!
 
  • #5
Working on Part C:

I'm a little confused with this part. I took a peak at the solutions and I see the following,

[tex]f_{xx} = -6xy = \frac{-3}{2}[/tex]

[tex] f_{yy} = -6xy = \frac{-3}{2}[/tex]

[tex] f_{xy} = 1 - 3x^{2} - 3y^{2} = \frac{-1}{2} [/tex]

The mechanics of all this (i.e. taking the partial of fx wrt x again) makes sense and so do the results. The part I don't understand is WHY we are doing this to obtain information about the nature of the critical point. (in other words how is this helping us?)

Also they throw in this line at the end,

So,

[tex]f_{xx}f_{yy}-f_{xy}^{2} > 0,[/tex] and [tex]f_{xx} < 0[/tex]

Therefore it is a local maximum.

I'm confused as to how he drew this conclusion? How do all these partial derivatives, and specifically that line above, tell us whether it is a max or a min?

Thanks in advance!
 
  • #6
Let M = [tex] f_{xx}f_{yy}-f_{xy}^{2}. [/tex]

If M > 0, then [tex] f_{xx}f_{yy} > f_{xy}^{2}. [/tex] So f_xx and f_yy must have the same sign (positive or negative) and are sufficiently large enough to offset f_xy (this is a bit more complicated, ignore for now).
If positive, then both the x and y cross sections are concave up, i.e., local min.
Similarly, if negative, then concave down, i.e., local max.

If M < 0 and f_xx and f_yy have different signs, then the x and y cross sections have opposite concavity. Thus, we have a saddle point.

If M < 0 and f_xx and f_yy have the same sign, then things are a tiny bit more complicated. I'm too lazy to type it all out, but the result is that the critical point is a saddle point here.

By the way, all this should be on wikipedia, wolframalpha, etc. Just search "second derivative test in multivariable calculus" in Google.
 
  • #7
Oh, and if M = 0, our test fails :'(!
 

FAQ: Critical Points in the First Quadrant

What is a critical point?

A critical point is a point on a graph where the derivative is equal to zero or the slope is undefined. It is also known as a stationary point.

How do you find critical points?

To find critical points, you must first take the derivative of the function and set it equal to zero. Then solve for the variable to find the x-values of the critical points.

Why are critical points important?

Critical points are important because they can help us determine the maximum or minimum values of a function. They can also help us identify where the slope of the graph changes direction.

What is the difference between a local and global critical point?

A local critical point is a point where the derivative is equal to zero or undefined, and it is surrounded by points with a higher or lower function value. A global critical point is the highest or lowest point on the entire graph.

How do critical points relate to optimization problems?

Critical points are closely related to optimization problems because they help us find the maximum or minimum values of a function. In optimization, we are trying to find the best possible solution, which often involves finding critical points.

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