Proving No Local Minimum Exist in Functional J(y) for Given Boundary Conditions

In summary, the conversation discusses the functional J(y) defined by integrating x^4(y'(x))^2 from -1 to 1 and the set S of elements y in C^2[-1,1] satisfying y(-1)=-1 and y(1) = 1. It is proven that J cannot have a local minimum in S without using the Euler-Lagrange equation. The idea is to show that for every e>0, there is an element of S that satisfies J(y)<e, and to do this, a variation of an element y in S is created which decreases J(y). This variation is nonzero near the point where the Euler-Lagrange equation is nonzero for every element of S. However
  • #1
daudaudaudau
302
0

Homework Statement



Consider the functional defined by
[tex]
J(y)=\int_{-1}^1 x^4(y'(x))^2 dx
[/tex]

Without resorting to the Euler-Lagrange equation, prove that J cannot have a local minimum in the set
[tex]
S=\{y\in C^2[-1,1]:\ y(-1)=-1,\ y(1)=1\}.
[/tex]

The Attempt at a Solution


I have thought about this one, but I have no clue how to do it without the Euler-Lagrange equation. Using the EL equation, I can find a solution which satisfies the boundary conditions, but is not continuous at [itex]x=0[/itex]: [itex]y=1/x^3[/itex].
 
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  • #2
Your functional J is nonnegative. And for every element y of S, J(y)>0, right? If you can show for every e>0, there is an element y_e of S that satisfies J(y_e)<e, you would be done.
 
  • #3
So you're saying that J(y) has no lower boundary, and I agree, but how does this exclude that J(y) could have a local minimum somewhere? It has no global minimum for sure.
 
  • #4
daudaudaudau said:
So you're saying that J(y) has no lower boundary, and I agree, but how does this exclude that J(y) could have a local minimum somewhere? It has no global minimum for sure.

Good point. I was thinking of a global minimum. To show there is no local minimum you'll have to think of a way to create a variation of an element y in S which decreases J(y). Any ideas?
 
  • #5
How about

[tex]
\begin{align*}
J(y+a\delta(x))&=\int_{-1}^1 x^4(y'(x)+a\delta'(x))^2dx\\
&=\int_{-1}^1 x^4(y'(x))^2dx+2a\int_{-1}^1x^4y'(x)\delta'(x)dx+a^2\int_{-1}^1x^4(\delta'(x))^2dx
\end{align*}
[/tex]

The second-order term is always positive, so if the first-order term is zero, we have a minimum. But since [itex]\delta(x)[/itex] is arbitrary, and because [itex]y(x)[/itex] is differentiable, this means that [itex]y'(x)=0[/itex], and this solution cannot satisfy the boundary conditions.
 
  • #6
But I might as well perform an integration by parts on the first-order term and obtain the E-L equation which leads to the solution [itex]y=1/x^3[/itex], but this solution is certainly not a stationary point, or continuous.

I should mention that the first part of the question in my book is

a) Show that no extremals in [itex]C^2[-1,1][/itex] exist which satisfy the boundary conditions [itex]y(-1)=-1,\ y(1)=1[/itex].
 
  • #7
daudaudaudau said:
How about

[tex]
\begin{align*}
J(y+a\delta(x))&=\int_{-1}^1 x^4(y'(x)+a\delta'(x))^2dx\\
&=\int_{-1}^1 x^4(y'(x))^2dx+2a\int_{-1}^1x^4y'(x)\delta'(x)dx+a^2\int_{-1}^1x^4(\delta'(x))^2dx
\end{align*}
[/tex]

The second-order term is always positive, so if the first-order term is zero, we have a minimum. But since [itex]\delta(x)[/itex] is arbitrary, and because [itex]y(x)[/itex] is differentiable, this means that [itex]y'(x)=0[/itex], and this solution cannot satisfy the boundary conditions.

Well, you want to ignore the terms that are quadratic in the variation. But, yes, that's the idea. So, yes, then if you integrate by parts, you get the EL equation times the variation. Since you know that nothing in S satisfies the EL equation, it must be nonzero someplace for every element of S. Then choose a variation which is nonzero near that point. This is all fine, but is this really 'without resorting to the Euler-Lagrange equation'?? Offhand, I'm not thinking of any other clever tricks right now.
 
  • #8
So could we just choose the derivative of the variation [itex]\delta'(x)[/itex] to be positive whenever [itex]y'(x)[/itex] is, and zero otherwise?
 
  • #9
Sort of, I guess. Though you would need to make sure the variation has two continuous derivatives. But all of this is really just using the Euler Lagrange procedure in a messy way, and isn't really a new way of showing there is no local minimum. I really wonder if they meant to say 'local minimum' in the question and not 'global minimum'.
 

What is the "Calculus of Variations"?

The Calculus of Variations is a branch of mathematics that deals with finding the optimal path or function that minimizes or maximizes a certain quantity, such as energy or cost.

What is the main goal of the "Calculus of Variations"?

The main goal of the Calculus of Variations is to find the function or path that minimizes or maximizes a specific quantity, also known as the "functional". This can be used to solve optimization problems in various fields, such as physics, engineering, and economics.

What is the difference between the "Calculus of Variations" and traditional calculus?

The Calculus of Variations is different from traditional calculus in that it deals with functions of functions, rather than just functions of variables. It also focuses on finding the function that minimizes or maximizes a certain quantity, rather than just finding the derivatives of a function.

What are some applications of the "Calculus of Variations"?

The Calculus of Variations has many applications in physics, engineering, economics, and other fields. For example, it can be used to find the path that a particle will take to minimize its energy, or to find the shape of a bridge that will minimize its cost while still supporting a certain weight.

What are some common techniques used in the "Calculus of Variations"?

Some common techniques used in the Calculus of Variations include the Euler-Lagrange equation, the method of variations, and the calculus of variations by direct methods. These techniques help to find the optimal solution to a given problem by setting up and solving mathematical equations.

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