Proof of the strong maximum principle

In summary, the conversation discusses the proof of the strong maximum principle, which states that if a function satisfies Laplace's equation, is continuous at the boundary, and achieves its maximum at the boundary and a point within the domain, then the function must be a constant. The conversation delves into using the mean value property and Laplace's equation to prove this principle, with some confusion and discussion surrounding the use of a circle with center $x_M$ versus a circle with center at $0$. Ultimately, the conversation concludes with potential ways to continue the proof.
  • #1
mathmari
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Hey! :eek:

I am looking at the proof of the strong maximum principle:
If a function $u$ satisfies the Laplace's equation at the open space $D$ and is continuous at the boundary $\partial{D}$ and achieves its maximum at $\partial{D}$ and at a point of $D$ then the function is a constant.

which is the following:

View attachment 2666

$x_M$ : the point where the function achieves its maximum

$x_M \in D$

$u(x) \leq u(x_M)=M, \forall x \in D$

$u(x)=u(x_M), \forall \text{ choice of circle }$

(Thinking)

I am facing some difficulties understanding this proof.. (Worried)

So, we take a circle with center $x_M$.

Then from the mean value property we have that:
$$u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds$$

We consider that $x_M \in D$ is the point at which $u$ achieves its maximum, so
$$u(x) \leq u(x_M)=M, \ \ \ \forall x \in D$$

So, we have the following:

$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds$$

But since the integral is at the boundary $\partial{D}$, and we have supposed that $M$ is the maximum of all points at $D$, we cannot say that
$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds \leq \frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{M}ds$$
right??

How can I continue then to show that the function is constant?? (Wondering)
 

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  • #2
Hey! (Mmm)

mathmari said:
But since the integral is at the boundary $\partial{D}$, and we have supposed that $M$ is the maximum of all points at $D$, we cannot say that
$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds \leq \frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{M}ds$$
right??

Sure you can, but it doesn't help you. (Wasntme)
How can I continue then to show that the function is constant?? (Wondering)

Do something with Laplace's equation? (Thinking)
 
  • #3
I like Serena said:
Sure you can, but it doesn't help you. (Wasntme)

I thought I could it as followed:

$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds \leq \frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{M}ds = \frac{M}{2 \pi a} \int_{| \overrightarrow{r'}|=a}ds =M$$

So the symbol $\leq$ should be $=$, so $u=M$.

Is this wrong?? (Wondering)

I like Serena said:
Do something with Laplace's equation? (Thinking)

What could I do?? (Wondering)
 
  • #4
mathmari said:
I thought I could it as followed:

$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds \leq \frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{M}ds = \frac{M}{2 \pi a} \int_{| \overrightarrow{r'}|=a}ds =M$$

So the symbol $\leq$ should be $=$, so $u=M$.

Is this wrong?? (Wondering)

It is correct, but you are restating something you already know.
The left hand side is equivalent to the right hand side. (Wasntme)
What could I do?? (Wondering)

Well... you could for instance write down Laplace's equation in polar coordinates, separate the variables, add the boundary condition that the function of angle has period $2\pi$... (Wondering)
 
  • #5
I like Serena said:
Well... you could for instance write down Laplace's equation in polar coordinates, separate the variables, add the boundary condition that the function of angle has period $2\pi$... (Wondering)

$$u_{rr}+\frac{1}{r}u_r+\frac{1}{r^2}u_{\theta \theta}=0 ,\ \ \ 0 \leq \theta \leq 2 \pi, \ \ \ 0 \leq r \leq a$$

Applying the method of separation of variables, the solution is of the form $u(r, \theta)=R(r) \Theta(\theta)$

the boundary condition that the function of angle has period $2\pi$:
$u(a,\theta)=h(\theta), h(\theta)=h(2 \pi + \theta)$

The solution is the following:
$$u(r, \theta)=\sum_{n=0}^{\infty} [A_n \cos{(n \theta)}+B_n \sin{(n \theta)}]r^n \Rightarrow \dots \Rightarrow \\ u(r, \theta)=\frac{a^2-r^2}{2 \pi} \int_0^{2 \pi} \frac{h(\phi)}{a^2+r^2-2ar \cos{(\theta-\phi)}}d \phi$$

Do I have to use the last formula?? (Wondering)
 
  • #6
mathmari said:
$$u_{rr}+\frac{1}{r}u_r+\frac{1}{r^2}u_{\theta \theta}=0 ,\ \ \ 0 \leq \theta \leq 2 \pi, \ \ \ 0 \leq r \leq a$$

Applying the method of separation of variables, the solution is of the form $u(r, \theta)=R(r) \Theta(\theta)$

the boundary condition that the function of angle has period $2\pi$:
$u(a,\theta)=h(\theta), h(\theta)=h(2 \pi + \theta)$

The solution is the following:
$$u(r, \theta)=\sum_{n=0}^{\infty} [A_n \cos{(n \theta)}+B_n \sin{(n \theta)}]r^n \Rightarrow \dots \Rightarrow \\ u(r, \theta)=\frac{a^2-r^2}{2 \pi} \int_0^{2 \pi} \frac{h(\phi)}{a^2+r^2-2ar \cos{(\theta-\phi)}}d \phi$$

Do I have to use the last formula?? (Wondering)

Now that you mentioned it, didn't you have a proof (using that formula) that the average of the boundary is equal to u(0)?
Perhaps you can use that. (Thinking)
 
  • #7
I like Serena said:
Now that you mentioned it, didn't you have a proof (using that formula) that the average of the boundary is equal to u(0)?
Perhaps you can use that. (Thinking)

Yes, when we have a circle with center at $0$.

At the post #1, I took a circle with center at $x_M$, and then the average of the boundary is equal to
$$u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds$$
 
  • #8
Since $u$ achieves its maximum at $\partial{D}$ and at a point of $D$, do we maybe have to suppose that $M$ is the maximum of all points at $D$ and at $\partial{D}$?? (Wondering)

Then it would be as followed:

We take a circle with center $x_M$.

Then from the average of the boundary we have that:
$$u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds$$

We consider that $x_M \in \overline{D}$ is the point at which $u$ achieves its maximum, so
$$u(x) \leq u(x_M)=M, \ \ \ \forall x \in \overline{D}$$

($\overline{D}=D \cup \partial{D}$)

So, we have the following:

$$M=u(x_M)=\frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{u(\overrightarrow{r'})}ds \leq \frac{1}{2 \pi a} \int_{| \overrightarrow{r'}|=a}{M}ds$$

Can we continue from here?? (Worried)
Or should I use the average of the boundary in an other way?? (Thinking)
 
  • #9
Since you can use the proposition that the value at the center is equal to the average at a circular boundary, it follows that all values at any circle around the center must be $M$... (Thinking)
 
  • #10
I like Serena said:
Since you can use the proposition that the value at the center is equal to the average at a circular boundary, it follows that all values at any circle around the center must be $M$... (Thinking)

I got stuck right now... (Worried)
Could you explain me further this implication?? (Thinking)
 
  • #11
mathmari said:
I got stuck right now... (Worried)
Could you explain me further this implication?? (Thinking)

I think it is like this.

Suppose we start with this point $x_M$ and draw a very small circle around it.
Since $x_M$ belongs to the interior of $D$, there must be a radius $r$ such that the circle fall entirely within $D$.

According to the Poisson kernel for the polar Laplace's equation, the value of $u$ at the center is the same as the average value of $u$ on a circle around that center.
Or isn't it? (Thinking)

So the values on our small circle should be sometimes lower than $u(x_M)$ and sometimes higher than $u(x_M)$ in such a way that the differences cancel out on average, giving an average of just $u(x_M)=M$.

However, since $M$ is actually the maximum on $D$, it follows that no value on the circle can be higher than $M$. And since the average has to come out as $M$, no value can be lower than $M$.
Therefore, each value on our small circle must have value $M$.
Or am I wrong? (Thinking)(Thinking)
 
  • #12
I like Serena said:
According to the Poisson kernel for the polar Laplace's equation, the value of $u$ at the center is the same as the average value of $u$ on a circle around that center.
Or isn't it? (Thinking)

Yes, it is like that! (Yes)

I like Serena said:
So the values on our small circle should be sometimes lower than $u(x_M)$ and sometimes higher than $u(x_M)$ in such a way that the differences cancel out on average, giving an average of just $u(x_M)=M$.

However, since $M$ is actually the maximum on $D$, it follows that no value on the circle can be higher than $M$. And since the average has to come out as $M$, no value can be lower than $M$.
Therefore, each value on our small circle must have value $M$.
Or am I wrong? (Thinking)(Thinking)

Ahaa... (Thinking) If there were values that are lower than $M$, would the average be lower than $M$??
 
  • #13
mathmari said:
Ahaa... (Thinking) If there were values that are lower than $M$, would the average be lower than $M$??

Any value lower than $M$ would pull the average down (assuming $u$ is continuous)... (Nod)
 
  • #14
I like Serena said:
Any value lower than $M$ would pull the average down (assuming $u$ is continuous)... (Nod)

Ahaa...Ok! I understand! Thank you very much! (Mmm)
 

1. What is the strong maximum principle?

The strong maximum principle is a mathematical theorem used in the study of partial differential equations. It states that if a function is defined on a bounded domain and satisfies certain conditions, then the maximum value of the function must occur either on the boundary of the domain or at a critical point within the domain.

2. What are the conditions that must be satisfied for the strong maximum principle to hold?

The function must be continuous and differentiable within the domain, and the domain itself must be bounded and connected. In addition, the function must satisfy a specific type of differential inequality, known as the maximum principle inequality.

3. How is the strong maximum principle used in real-world applications?

The strong maximum principle has numerous applications in physics, engineering, and other fields. It is commonly used to analyze and solve problems involving heat transfer, diffusion, and fluid flow. It also has applications in optimal control theory and game theory.

4. Can the strong maximum principle be generalized to higher dimensions?

Yes, the strong maximum principle can be extended to higher dimensions, such as three-dimensional space. In this case, the function must satisfy the maximum principle inequality for each of the three spatial variables.

5. Are there any variations of the strong maximum principle?

Yes, there are several variations of the strong maximum principle, including the weak maximum principle and the parabolic maximum principle. These versions have slightly different conditions and applications, but all are based on the same fundamental theorem.

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