Understanding Stationary Points: Saddle, Max, or Min?

In summary, the conversation was about finding stationary points and determining whether they are saddle points or max/min points. The person had a question about their solution and asked for someone to go through their work. They provided their working and received a response explaining the correct way to determine saddle points using the determinant of the second derivative matrix. The person also mentioned that their lecturer had stated the opposite in their notes, but upon further research, it was confirmed that the other way around is commonly used in textbooks.
  • #1
ibysaiyan
442
0

Homework Statement


Hi,

I have been given a set of functions for which I need to find the stationary points , and determine whether the points are saddle, or max/min.
I think I may have solved it correctly but I end up with all the points being saddle, surely this can't be right.. I may have gone wrong with my arithmetic. Can anyone go through my working. Appreciate the replies.


Homework Equations






The Attempt at a Solution



[itex] f(x,y) = x^4 +(2x^2)y -4x^2 +3y^2 [/itex]

[itex]F_{x}[/itex] = [itex]4x^3 +4xy-8x [/itex]
[itex]F_{y}[/itex] =[itex]2x^2+6y [/itex]
[itex]F_{xx}[/itex]12x^2 +4y -8
[itex]F_{yy}[/itex]6
[itex]F_{yx}[/itex]4x

The definition which I have used for delta/ determinant is : If Δ > 0 then stationary points are saddle i.e [itex]f_{xy}^2[/itex] - [itex]f_{xx}[/itex] * [itex]f_{yy}[/itex]

The points which I get are the following:
Re arranging (eq.1) and using eq. 2 (2x^2 = -6y)
4x^3 +4xy-8x (eq.1)
=>
x(4x^2 +4y-8) = 0
x[ (2x^2 +2x^2 ]+4y-8 = 0
x[ (-6y-6y) +4y -8] =0
x(-12+4y-8) = 0

x = 0 , -8y = 8 , y=-1
Points are:
(0,0) , (+/√3, -1)

Thanks!
 
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  • #2
ibysaiyan said:

Homework Statement


Hi,

I have been given a set of functions for which I need to find the stationary points , and determine whether the points are saddle, or max/min.
I think I may have solved it correctly but I end up with all the points being saddle, surely this can't be right.. I may have gone wrong with my arithmetic. Can anyone go through my working. Appreciate the replies.


Homework Equations






The Attempt at a Solution



[itex] f(x,y) = x^4 +(2x^2)y -4x^2 +3y^2 [/itex]

[itex]F_{x}[/itex] = [itex]4x^3 +4xy-8x [/itex]
[itex]F_{y}[/itex] =[itex]2x^2+6y [/itex]
[itex]F_{xx}[/itex]12x^2 +4y -8
[itex]F_{yy}[/itex]6
[itex]F_{yx}[/itex]4x

The definition which I have used for delta/ determinant is : If Δ > 0 then stationary points are saddle i.e [itex]f_{xy}^2[/itex] - [itex]f_{xx}[/itex] * [itex]f_{yy}[/itex]
You have this exactly backwards- the stationary points are saddles if Δ< 0.
The point is that [itex]f_{xy}^2- f_{xx}f_{yy}[/itex] is the determinant of the "second derivative matrix"
[tex]\begin{bmatrix}f_{xx}& f_{xy} \\ f_{xy} & f_{yy}\end{bmatrix}[/tex]
of course that determinant is independent of the coordinate system- and since this is a symmetric matrix, there exist a coordinate system in which it is diagonal. That is there exist a coordinate system in which the matrix is
[tex]\begin{bmatrix}f_{xx} & 0 \\ 0 & f_{yy}\end{bmatrix}[/tex]
which means that, locally, it is like [itex]f_{xx}x^2+ f_{yy}y^2[/itex]. If the determinant is negative, one of those coefficients is positive, the other negative, a saddle point. If the determinant is positive, the coefficients are either both positive, a local minimum, or both negative, a local maximum.

The points which I get are the following:
Re arranging (eq.1) and using eq. 2 (2x^2 = -6y)
4x^3 +4xy-8x (eq.1)
=>
x(4x^2 +4y-8) = 0
x[ (2x^2 +2x^2 ]+4y-8 = 0
x[ (-6y-6y) +4y -8] =0
x(-12+4y-8) = 0

x = 0 , -8y = 8 , y=-1
Points are:
(0,0) , (+/√3, -1)

Thanks!
 
Last edited by a moderator:
  • #3
HallsofIvy said:
You have this exactly backwards- the stationary points are saddles if Δ< 0.
The point is that [itex]f_{xy}^2- f_{xx}f_{yy}[/itex] is the determinant of the "second derivative matrix"
[tex]\begin{bmatrix}f_{xx}& f_{xy} \\ f_{xy} & f_{yy}\end{bmatrix}[/tex]
of course that determinant is independent of the coordinate system- and since this is a symmetric matrix, there exist a coordinate system in which it is diagonal. That is there exist a coordinate system in which the matrix is
[tex]\begin{bmatrix}f_{xx} & 0 \\ 0 & f_{yy}\end{bmatrix}[/tex]
which means that, locally, it is like [itex]f_{xx}x^2+ f_{yy}y^2[/itex]. If the determinant is negative, one of those coefficients is positive, the other negative, a saddle point. If the determinant is positive, the coefficients are either both positive, a local minimum, or both negative, a local maximum.

Hi there,
You see on my lecturer's note I can clearly see that he has stated that when a coordinate system has Δ >0 then it's a saddle point , he did mention that " some books use the expression the other way around" , which I have confirmed upon browsing.

Could he be wrong? Also thanks for your in-depth answer ( as always).
 

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