How can we improve the estimate?

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In summary, the conversation discussed finding the constants $c_1$ and $c_2$ in the problem $Lu=-1 \text{ in } \Omega, u|_{\partial{\Omega}}=2, (c(x) \leq 0)$, as well as improving the estimate $(1)$ when $c(x) \equiv -1$. The conversation mentioned using a lemma and a theorem to find a sharper estimate, but ultimately found that $u=1$ is the solution for $c(x) \equiv -1$. The conversation also discussed the possibility of a function being equal to $2$ at the boundary when it is smaller or equal to $1$ in the interior. Finally, the conversation
  • #1
evinda
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Hello! (Wave)

Let $u(x)$ be a solution of the problem

$$Lu=-1 \text{ in } \Omega , u|_{\partial{\Omega}}=2, (c(x) \leq 0)$$

I want to determine the constants $c_1,c_2$ such that $c_1 \leq u(x) \leq c_2 (1)$.

Also I want to improve the estimate $(1)$ when it is furthermore given that $c(x) \equiv -1$.

I thought to use the following lemma:

Let $L$ be an elliptic operator in a bounded space $\Omega$ and $u \in C^2(\Omega) \cup C^0(\overline{\Omega})$.
If $Lu \geq 0 (\leq 0) \ \ \ \ \ \ c \leq 0 \text{ in } \Omega$
then $$\sup_{\Omega} u \leq \max \left( \sup_{\partial{\Omega}} u, 0\right) \\ \left( \inf_{\Omega} u \geq \min \{ \inf_{\partial{\Omega}} u, 0\} \right)$$

From this, if we consider that $\Omega$ is bounded , we get that $\inf_{\Omega} u \geq 0$ and so $u \geq 0$.

For the other inequality, I thought to use the following theorem:

Let $Lu=f$ in a bounded space $\Omega$, where $L$ is an elliptic operator and $u \in C^2(\Omega) \cap C^0(\overline{\Omega})$. Then $$\sup_{\overline{\Omega}} |u| \leq \sup_{\partial{\Omega}} |u|+ C \sup \frac{|f|}{\lambda}$$

where $C=e^{\alpha d}-1 $

($d $: $ \Omega \subset \{ 0< x_1< d\}$)

($\alpha \geq \frac{\sup{|\beta_1|}}{\lambda}+1$)

($\beta_1: Lu= \sum_{i,j=1}^n a_{ij} u_{x_i x_j}+ \sum_{i=1}^n \beta_i u_{x_i}+cu $ )

($\lambda: 0< \lambda |\xi|^2 \leq \sum_{i,j=1}^n a_{ij} \xi_i \xi_j \ \ \ \ \xi \in \mathbb{R}^n, x \in \Omega $)

From this get that $ \sup_{\overline{\Omega}} |u| \leq 2+ \frac{C}{\lambda} $, so $u \leq 2+\frac{C}{\lambda}$.

Is it right so far? How can we improve the estimate $0 \leq u(x) \leq 2+ \frac{C}{\lambda} $ when we know furthermore that $c(x) \equiv -1$ ? (Thinking)
 
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  • #2
Hey evinda! (Smile)

Looks right to me.

Btw, didn't we have:
evinda said:
We have the following theorem:

Theorem: We suppose that $u \in C^2(\Omega)$ satisfies in the space $\Omega$ the relation $Lu \geq 0$ ($Lu \leq 0$). We suppose that $\Omega$ satisfies the interior sphere condition.
If $c \leq 0$ then $u(x)$ does not achieve its positive maximum in $\Omega$, i.e. in $\overline{\Omega} \setminus{\partial{\Omega}}$ (negative minimum) if it is not constant.
If $c \equiv 0$ then $u$ does not achieve its maximum in $\Omega$ (minimum) if it is not constant.

Couldn't we find a better estimate with it? (Wondering)
 
  • #3
I like Serena said:
Btw, didn't we have:Couldn't we find a better estimate with it? (Wondering)

I thought that we cannot use it since we have $Lu \leq 0$ and $u|_{\partial{\Omega}}=2$ and so we don't have a negative minimum. Do you agree? (Thinking)
 
  • #4
evinda said:
I thought that we cannot use it since we have $Lu \leq 0$ and $u|_{\partial{\Omega}}=2$ and so we don't have a negative minimum. Do you agree? (Thinking)

Indeed, we can't use it. (Blush)
 
  • #5
I like Serena said:
Indeed, we can't use it. (Blush)

(Smile)

Do you have an idea how we can find a better estimate,when we assume that $c(x) \equiv -1$ ?
 
  • #6
evinda said:
(Smile)

Do you have an idea how we can find a better estimate,when we assume that $c(x) \equiv -1$ ?

Repeating your idea from your previous thread... (Thinking)

Suppose $u$ has a maximum at $x_0 \in \overline\Omega$ (assuming that $\Omega$ is bounded).
Then:
$$Lu(x_0)= \sum_{i,j=1}^n a_{ij} u_{x_i x_j}+cu(x_0) = -1 \quad\Rightarrow\quad c(x_0)u(x_0) \ge -1
\quad\Rightarrow\quad u(x_0) \le \frac{-1}{c(x_0)}$$
For $c(x_0)=-1$ this becomes:
$$u(x) \le u(x_0) \le 1$$
(Happy)
 
  • #7
I like Serena said:
Repeating your idea from your previous thread... (Thinking)

Suppose $u$ has a maximum at $x_0 \in \overline\Omega$ (assuming that $\Omega$ is bounded).
Then:
$$Lu(x_0)= \sum_{i,j=1}^n a_{ij} u_{x_i x_j}+cu(x_0) = -1 \quad\Rightarrow\quad c(x_0)u(x_0) \ge -1
\quad\Rightarrow\quad u(x_0) \le \frac{-1}{c(x_0)}$$
For $c(x_0)=-1$ this becomes:
$$u(x) \le u(x_0) \le 1$$
(Happy)

In the same way, suppose that $u$ has a minimum at $x_1 \in \overline\Omega$ .
Then:

$$Lu(x_1)= \sum_{i,j=1}^n a_{ij}(x_1) u_{x_i x_j}(x_1)+cu(x_1) = -1 \quad\Rightarrow\quad c(x_1)u(x_1) \le -1
\quad\Rightarrow\quad u(x_1) \ge \frac{-1}{c(x_1)}$$
For $c(x_1)=-1$ this becomes:
$$u(x) \ge u(x_1) \ge 1$$

So, when $c \equiv -1$, the solution of the problem is $u=1$, right? (Thinking)
 
  • #8
evinda said:
In the same way, suppose that $u$ has a minimum at $x_1 \in \overline\Omega$ .
Then:

$$Lu(x_1)= \sum_{i,j=1}^n a_{ij}(x_1) u_{x_i x_j}(x_1)+cu(x_1) = -1 \quad\Rightarrow\quad c(x_1)u(x_1) \le -1
\quad\Rightarrow\quad u(x_1) \ge \frac{-1}{c(x_1)}$$
For $c(x_1)=-1$ this becomes:
$$u(x) \ge u(x_1) \ge 1$$

So, when $c \equiv -1$, the solution of the problem is $u=1$, right? (Thinking)

Hmm... suppose we pick... an example! (Wait)
View attachment 6207

I'm not sure if the solution $u=1$ is correct. (Worried)
 

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  • #9
Why was my argumentation with the minimum value wrong? (Thinking)Also can a function that is smaller or equal to $1$ be equal to $2$ at the boundary? (Sweating)
 
  • #10
evinda said:
Why was my argumentation with the minimum value wrong? (Thinking)Also can a function that is smaller or equal to $1$ be equal to $2$ at the boundary? (Sweating)

We assumed that u had a maximum where the derivative was zero. I think we have proven that there is no internal maximum when c=-1. Instead we have the sharper boundary maximum of 2! (Smile)
 
  • #11
I like Serena said:
We assumed that u had a maximum where the derivative was zero. I think we have proven that there is no internal maximum when c=-1. Instead we have the sharper boundary maximum of 2! (Smile)

We have that if $c<0, Lu \leq 0$ or $c \leq 0, Lu<0$ then $u$ does not achieve its negative minimum at the internal points of $\Omega$.

If we have the condition $c <0, Lu \geq 0$ or $c \leq 0, Lu>0$ we can deduce that the positive maximum is not achieved at the internal points of $\Omega$.
 
  • #12
evinda said:
We have that if $c<0, Lu \leq 0$ or $c \leq 0, Lu<0$ then $u$ does not achieve its negative minimum at the internal points of $\Omega$.

If we have the condition $c <0, Lu \geq 0$ or $c \leq 0, Lu>0$ we can deduce that the positive maximum is not achieved at the internal points of $\Omega$.

Yes. And we can apply neither here.

Instead we assumed there was an internal maximum, and found an upper boundary of $1$, which is a contradiction, since we have boundary values of $2$.
Therefore the assumption should be false: there is no internal maximum.
Shouldn't it? (Thinking)
 
  • #13
I like Serena said:
Yes. And we can apply neither here.

Instead we assumed there was an internal maximum, and found an upper boundary of $1$, which is a contradiction, since we have boundary values of $2$.
Therefore the assumption should be false: there is no internal maximum.
Shouldn't it? (Thinking)

Yes, it should. So from this we deduce that the maximum is achieved at the boundary, and so $u(x) \leq 2$, right? (Thinking)
From this:

In the same way, suppose that $u$ has a minimum at $x_1 \in \overline\Omega$ .
Then:

$$Lu(x_1)= \sum_{i,j=1}^n a_{ij}(x_1) u_{x_i x_j}(x_1)+cu(x_1) = -1 \quad\Rightarrow\quad c(x_1)u(x_1) \le -1
\quad\Rightarrow\quad u(x_1) \ge \frac{-1}{c(x_1)}$$
For $c(x_1)=-1$ this becomes:
$$u(x) \ge u(x_1) \ge 1$$

we don't get a contradiction, do we?
The boundary value is $2$ and if the minimum is achieved at an internal point, let $x_1$ , we have that $u(x_1) \geq 1$.

So $1$ is the minimum value of $u$, right?
 
  • #14
evinda said:
Yes, it should. So from this we deduce that the maximum is achieved at the boundary, and so $u(x) \leq 2$, right? (Thinking)

From this:

we don't get a contradiction, do we?
The boundary value is $2$ and if the minimum is achieved at an internal point, let $x_1$ , we have that $u(x_1) \geq 1$.

So $1$ is the minimum value of $u$, right?

Right. (Nod)

I do believe we should assume $x_1 \in \Omega\setminus \partial\Omega$, because we require the derivatives to be zero, which is not necessarily the case if the minimum is on the boundary, but the derivatives have to be zero if it's an internal minimum.
Furthermore, we should also consider that the minimum may be on the boundary, in which case it is $2$.
Since $1$ is less than $2$, we can conclude we have a lower estimate of $1$. (Thinking)
 
  • #15
I like Serena said:
Right. (Nod)

I do believe we should assume $x_1 \in \Omega\setminus \partial\Omega$, because we require the derivatives to be zero, which is not necessarily the case if the minimum is on the boundary, but the derivatives have to be zero if it's an internal minimum.
Furthermore, we should also consider that the minimum may be on the boundary, in which case it is $2$.
Since $1$ is less than $2$, we can conlude we have a lower estimate of $1$. (Thinking)

We should also consider that $x_0 \in \Omega\setminus \partial\Omega$, right?

You mean that if we have the maximum at an internal point $x_0$, then $\frac{\partial{u}}{\partial{v}}(x_0)=0$, but if $x_0$ is on the boundary then it does not necessarily hold that $\frac{\partial{u}}{\partial{v}}(x_0)=0$ ?
 
  • #16
I like Serena said:
Furthermore, we should also consider that the minimum may be on the boundary, in which case it is $2$.
Since $1$ is less than $2$, we can conlude we have a lower estimate of $1$. (Thinking)

Since $c \leq 0$, the function should have a negative minimum, so in this case it cannot be achieved at the boundary. Right? (Thinking)
 
  • #17
evinda said:
We should also consider that $x_0 \in \Omega\setminus \partial\Omega$, right?

You mean that if we have the maximum at an internal point $x_0$, then $\frac{\partial{u}}{\partial{v}}(x_0)=0$, but if $x_0$ is on the boundary then it does not necessarily hold that $\frac{\partial{u}}{\partial{v}}(x_0)=0$ ?

Yes. (Nod)

evinda said:
Since $c \leq 0$, the function should have a negative minimum, so in this case it cannot be achieved at the boundary. Right? (Thinking)

How so? :confused:

We found that the internal minimum, if we have one for c=-1, has to be at least 1.
And indeed, in my example it's between 1 and 2. (Thinking)
 
  • #18
I like Serena said:
How so? :confused:

We found that the internal minimum, if we have one for c=-1, has to be at least 1.
And indeed, in my example it's between 1 and 2. (Thinking)

I thought so because of the following lemma:

If $c<0, Lu \leq 0$ or $c \leq 0, Lu<0$ then $u$ cannot achieve its negative minimum at the internal points of $\Omega$.

So can it be that there is a positive minimum, that is achieved at the internal points of $\Omega$ ? (Thinking)
 
  • #19
evinda said:
I thought so because of the following lemma:

If $c<0, Lu \leq 0$ or $c \leq 0, Lu<0$ then $u$ cannot achieve its negative minimum at the internal points of $\Omega$.

So can it be that there is a positive minimum, that is achieved at the internal points of $\Omega$ ? (Thinking)

Suppose we repeat your reasoning from before for these cases, don't we get that the internal minimum, if there is one, is at least 0? (Wondering)

So indeed, there can be no negative internal minimum, but still one that is at least zero. (Cool)
 
  • #20
I like Serena said:
Suppose we repeat your reasoning from before for these cases, don't we get that the internal minimum, if there is one, is at least 0? (Wondering)

So indeed, there can be no negative internal minimum, but still one that is at least zero. (Cool)

You mean this one, right?

$$\inf_{\Omega} u \geq \min \{ \inf_{\partial{\Omega}} u, 0\}$$
 
  • #21
evinda said:
You mean this one, right?

$$\inf_{\Omega} u \geq \min \{ \inf_{\partial{\Omega}} u, 0\}$$

That sums it up yes. (Mmm)
 
  • #22
Nice... Thanks a lot! (Smirk)
 

FAQ: How can we improve the estimate?

How can we determine the accuracy of our estimate?

The accuracy of an estimate can be determined by comparing it to the actual value or result. This can be done by conducting experiments, collecting data, and analyzing the results. Additionally, statistical methods such as margin of error and confidence intervals can also be used to assess the accuracy of an estimate.

What factors can affect the accuracy of an estimate?

There are several factors that can affect the accuracy of an estimate, such as the quality and quantity of data used, the complexity of the problem, and the assumptions made during the estimation process. Other external factors, such as changes in the environment or unforeseen events, can also impact the accuracy of an estimate.

How can we reduce the uncertainty in our estimate?

One way to reduce uncertainty in an estimate is to use more data and information from multiple sources. This can help to account for any variations or errors in the data. Another approach is to use different estimation techniques and compare their results to identify any potential biases or outliers.

How can we improve the precision of our estimate?

Precision refers to the level of detail and specificity in an estimate. To improve precision, we can use more precise measurement tools, increase the sample size, and reduce any sources of error. It is also important to clearly define the parameters and assumptions used in the estimation process to ensure consistency and accuracy.

How can we communicate the results of an estimate effectively?

Effective communication of the results of an estimate is crucial to ensure that it is understood and used correctly. This can be achieved by presenting the data and findings in a clear and concise manner, using visual aids such as graphs and charts, and providing context and explanations for any assumptions or limitations. It is also important to consider the audience and tailor the communication style accordingly.

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