TeX loves LATEXDoes F=x2y2-2x-2y have a minimum at the point x=y=1?

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The function F=x²y²-2x-2y does not have a minimum at the point (1,1) because the second derivative test yields a negative determinant of the Hessian matrix, indicating a saddle point. The first derivatives at (1,1) are both zero, confirming it's a critical point. The calculation shows that FxxFyy-Fxy² equals -12, which is less than zero. A detailed quadratic approximation near (1,1) further illustrates that the function behaves differently along various directions, reinforcing the saddle point conclusion. Thus, the analysis concludes that (1,1) is indeed a saddle point, not a minimum.
tatianaiistb
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Homework Statement



Decide whether F=x2y2-2x-2y has a minimum at the point x=y=1 (after showing that the first derivatives are zero at that point).

Homework Equations



FxxFyy-Fxy2

The Attempt at a Solution



So I found that:
Fx=2xy2-2, which at point (1,1) = 0 OK
Fy=2x2y-2, which at point (1,1) = 0 OK
Fxx=2y2
Fyy=2x2
Fxy=4xy

So at point (1,1):
FxxFyy-Fxy2=4-16=-12, which is less than 0.

Does this mean that because it is less than zero, rather than greater, it DOES NOT have a minimum but rather a saddle point? Thanks!
 
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Hi tatianaiistb! :smile:

Yes, the second derivative test says that a negative determinant means it's a saddle point.

Btw, you can easily verify by checking a few points in the neighbourhood, like (1,0) and (-1.1).
 
tatianaiistb said:

Homework Statement



Decide whether F=x2y2-2x-2y has a minimum at the point x=y=1 (after showing that the first derivatives are zero at that point).

Homework Equations



FxxFyy-Fxy2

The Attempt at a Solution



So I found that:
Fx=2xy2-2, which at point (1,1) = 0 OK
Fy=2x2y-2, which at point (1,1) = 0 OK
Fxx=2y2
Fyy=2x2
Fxy=4xy

So at point (1,1):
FxxFyy-Fxy2=4-16=-12, which is less than 0.

Does this mean that because it is less than zero, rather than greater, it DOES NOT have a minimum but rather a saddle point? Thanks!

You get a saddle point. To understand WHY (rather than just citing prescriptions), look at what you get when you use the Hessian matrix to construct a quadratic approximation near (1,1): f ~ 2(x-1)^2 + 2(y-1)^2 -8(x-1)(y-1) = 2[(x-1)-(y-1)]^2-4(x-1)(y-1) = 2(x-y)^2 -4(x-1)(y-1) = 2(u-v)^2-4uv, where u=x-1 and v=y-1. When v=0 we have f ~ 2u^2 > 0 for nonzero u; when u=0 we have f~2v^2 > 0 for nonzero v. But when u=v we have f ~ -4u^2 < 0 for nonzero u (and v), so (u,v) = (0,0) is a min along some direction lines and a max along other direction lines. That is what a saddle point means.

RGV
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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