Stationary points and chain rule

In summary, the conversation discusses finding the nature of a stationary point at (x,y) = (pi,pi) for the function f(x,y) = sin(x) + sin(y) + sin(x+y). The Hessian matrix and determinant are both zero, making the "second derivatives test" inconclusive. The question also involves proving a conjecture using the chain rule, and the speaker is unsure of how the chain rule has been implemented in the given solution.
  • #1
Benny
584
0
Hi, I would like some help verifying the nature of a stationary point of the following function of two variables.

[tex]
f\left( {x,y} \right) = \sin \left( x \right) + \sin \left( y \right) + \sin \left( {x + y} \right)
[/tex]

Ok so I equated grad(f) to zero and solved for x and y. I got three points, in particular I found (x,y) = (pi,pi). As I found it, the Hessian matrix is the zero matrix so the determinant is also zero. So in terms of the "second derivatives test" the test is inconclusive for the point (pi,pi). I would like to know if there are any other ways of determining the nature (max, min, saddle) of the stationary point at (x,y) = (pi,pi).

My other question relates to the chain rule. I have been looking through a solution to a problem.

...conjectures that [tex]\mathop x\limits^ \to \bullet \nabla f\left( {\mathop x\limits^ \to } \right) = \nu f\left( {\mathop x\limits^ \to } \right)[/tex] for [tex]f:U \subset R^n \to R[/tex] provided that [tex]f\left( {a\mathop x\limits^ \to } \right) = a^\nu f\left( {\mathop x\limits^ \to } \right),a > 0[/tex].

The question is to prove the conjecture. As part of the solution there is a step which goes along the lines of let [tex]g\left( a \right) = f\left( {a\mathop x\limits^ \to } \right)[/tex] then [tex]g'\left( a \right) = \nabla f\left( {a\mathop x\limits^ \to } \right) \bullet \mathop x\limits^ \to [/tex].

I'm not sure how the chain rule has been implemented here. The LHS (g'(a)) is just the usual single variable derivative whereas the RHS involves the gradient and hence partial derivatives. The only time when I've seen a LHS with a derivative with respect to a single variable while the RHS involves partial and/or 'usual' derivatives is when I've had something like g = g(x,y) where x = x(t) and y = y(t) in which case I have:

[tex]
\frac{{dg}}{{dt}} = \frac{{\partial g}}{{\partial x}}\frac{{dx}}{{dt}} + \frac{{\partial g}}{{\partial y}}\frac{{dy}}{{dt}}
[/tex]

However in the above example I'm at a loss as to how the chain rule has been used. Can someone help me out with either of my questions? Thanks.
 
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  • #2
Try writing the gradient as a Taylor's series and keep only the first twp non-zero terms. Since [itex]sin(\pi)= 0[itex], sin'(x)= cos(x), [itex]sin'(\pi)= -1[/itex], sin"(x)= -sin(x) so [itex]sin"(\pi)= 0[/itex], and sin"'(x)= -cos(x) so [itex]sin"'(\pi)= 1, the third degree Taylor's polynomial for sin(x)+ sin(y)+ sin(x+y) about [itex](\pi,\pi)[/itex] is [itex](-x+ \frac{1}{3}x^3)+ (-y+ /frac{1}{3}y^3)+ (x+ y- /frac{1}{3}(x+y)^3[/itex] (the Taylor's Polynomial about [itex]\pi[/itex] in x+y is the Taylor's polynomial for x about [itex]2\pi[/itex] with x+y substituted for x). Multiply that out and see what it looks like close to [itex](\pi,\pi)[/itex].
 
  • #3
Thanks HallsofIvy, I'll try a Taylor series and see where that leads.

I'm also still working on the chain rule problem.:biggrin:
 

FAQ: Stationary points and chain rule

What is a stationary point?

A stationary point is a point on a graph where the gradient is zero, meaning that the slope of the tangent line at that point is flat. This can occur at local maximum or minimum points, as well as points of inflection.

How do you find stationary points?

To find stationary points, you can take the derivative of the function and set it equal to zero. Then, solve for the variable to determine the x-coordinate of the stationary point. You can also use the second derivative test to confirm whether the point is a local maximum or minimum.

What is the chain rule?

The chain rule is a rule used to find the derivative of a composite function. It states that the derivative of a composite function is equal to the derivative of the outer function multiplied by the derivative of the inner function.

When is the chain rule used?

The chain rule is used when finding the derivative of a function that is composed of multiple functions. For example, if you have a function inside another function, the chain rule would be used to find the derivative of the outer function with respect to the inner function.

How do you apply the chain rule?

To apply the chain rule, you must first identify the outer function and the inner function. Then, take the derivative of the outer function, leaving the inner function unchanged. Next, take the derivative of the inner function and multiply it by the derivative of the outer function. This will give you the overall derivative of the composite function.

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