Verify or refute the function is a solution to a PDE

In summary, the conversation discusses the solution attempt of a PDE problem, where u(x) is defined as half the squared norm of a vector x. It is shown that the function u satisfies the first condition, but not the Neumann boundary conditions. It is also discussed that u is equal to half the norm squared, and the directional derivative is computed using the outward unit normal field on the boundary of a unit ball. Finally, it is concluded that u is a solution to the PDE problem.
  • #1
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Homework Statement
Verify or refute the functions are solutions to a PDE
Relevant Equations
##u(x)=\frac{1}{2}(x_1^2+x_2^2+...+x_n^2)##
Screen Shot 2021-01-24 at 2.12.31 AM.png


Solution attempt:

We first write ##u(x)=\frac{1}{2}||x||^2## as ##u(x)=\frac{1}{2}(x_1^2+x_2^2+...+x_n^2)##

Operating on ##u(x)## with ##\Delta##, we have ##u(x)=\frac{1}{2}(2+2+...+2)## adding 2 to itself ##n## times.

So ##\Delta u(x)=n## and the function satisfies the first condition.

The outward unit normal field on the boundary of unit ball denoted ##\partial B_1(0)## is ##\nu=\left<x_1, x_2,...,x_n\right>##

The derivative of ##u## in the direction ##\nu## is given by ##D_{\nu}u=\frac{1}{2}(2x_1+2x_2+...+2x_n)=(x_1+x_2+...+x_n)##

So the function u does not satisfy the Neumann boundary conditions.

For the condition ##u=1## on the boundary of the unit ball, we consider the euclidian norm to be always equal to 1 by definition.

So the function ##u## satisfies the Dirichlet boundary conditions.
 
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  • #2
For the second one, u isn't equal to the euclidean norm.

For the first one, how do you know that the thing you wrote down doesn't add up to 1? If n=1, I think it does. Edit to add: actually I think you have computed the derivative in part 1 incorrectly.
 
  • #3
Office_Shredder said:
For the second one, u isn't equal to the euclidean norm.

I am not sure why ##u## does not equal the euclidian norm? ##u## is defined as the magnitude of vector ##\left<x_i\right>## squared. The boundary of a unit ball is an ##n## dimensional sphere, defined roughly as collection of points distance 1 from the origin. So every point on the boundary of the unit ball is a vector of length 1.

Office_Shredder said:
For the first one, how do you know that the thing you wrote down doesn't add up to 1? If n=1, I think it does.

I am not sure what you mean.. I added 2 to itself n times because there are n identical terms in the form of ##x_i^2## in ##u(x)## then i factored out ##2## which cancels with ##\frac{1}{2}## leaving n.
Office_Shredder said:
Edit to add: actually I think you have computed the derivative in part 1 incorrectly.

I just used the chain rule. most terms cancel out giving ##(x_1+...+x_n)##
 
  • #4
docnet said:
I am not sure why ##u## does not equal the euclidian norm? ##u## is defined as the magnitude of vector ##\left<x_i\right>## squared. The boundary of a unit ball is an ##n## dimensional sphere, defined roughly as collection of points distance 1 from the origin. So every point on the boundary of the unit ball is a vector of length 1.

But isn't u equal to one half the norm squared?
I am not sure what you mean.. I added 2 to itself n times because there are n identical terms in the form of ##x_i^2## in ##u(x)## then i factored out ##2## which cancels with ##\frac{1}{2}## leaving n.

To compute the directional derivative, you have to compute the total derivative (which depends on the coordinates of the point you are at), and then apply that matrix to the direction you care about.
 
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  • #5
Office_Shredder said:
But isn't u equal to one half the norm squared?

Yes, it is. It just occurred to me I did not account for the factor of ##\frac{1}{2}##. thank you.
Office_Shredder said:
To compute the directional derivative, you have to compute the total derivative (which depends on the coordinates of the point you are at), and then apply that matrix to the direction you care about.

total derivative? i thought it was partial. i computed

##D_{\left<x_1+x_2+...+x_n\right>}(x_1^2+x_2^2+...+x_n^2)=##
##\partial_{x_1}\frac{1}{2}(x_1^2+x_2^2+...+x_n^2)+...+\partial_{x_n}\frac{1}{2}(x_1^2+x_2^2+...+x_n^2)=##
##x_1+...+x_n##
 
  • #6
You have [tex]
\frac{\partial u}{\partial \nu} = \boldsymbol{\nu} \cdot \nabla u
[/tex] where [itex]\boldsymbol{\nu}[/itex] is the outward normal, which here is [itex]\mathbf{x}/\|\mathbf{x}\|[/itex]. Thus [tex]
\frac{\partial u}{\partial \nu} = \sum_{i=1}^n x_i \frac{\partial u}{\partial x_i}[/tex] since [itex]\|\mathbf{x}\| = 1[/itex].
 
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  • #7
pasmith said:
You have [tex]
\frac{\partial u}{\partial \nu} = \boldsymbol{\nu} \cdot \nabla u
[/tex] where [itex]\boldsymbol{\nu}[/itex] is the outward normal, which here is [itex]\mathbf{x}/\|\mathbf{x}\|[/itex]. Thus [tex]
\frac{\partial u}{\partial \nu} = \sum_{i=1}^n x_i \frac{\partial u}{\partial x_i}[/tex] since [itex]\|\mathbf{x}\| = 1[/itex].

Thank you, that makes sense
[tex]
\frac{\partial u}{\partial \nu} = \sum_{i=1}^n x_i \frac{\partial u}{\partial x_i}[/tex]
[tex]
\frac{\partial u}{\partial \nu} = x_1^2+...+x_n^2=1 [/tex]
which makes u a solution of the PDE problem.
 

FAQ: Verify or refute the function is a solution to a PDE

1. What is a PDE?

A PDE, or partial differential equation, is a mathematical equation that involves partial derivatives of an unknown function with respect to multiple independent variables. It is commonly used to model physical phenomena in fields such as physics, engineering, and economics.

2. How do you verify a function as a solution to a PDE?

To verify a function as a solution to a PDE, you must substitute the function into the PDE and check if the resulting equation is satisfied. This means that the function must satisfy the PDE for all values of the independent variables and their corresponding partial derivatives.

3. What does it mean to refute a function as a solution to a PDE?

To refute a function as a solution to a PDE means that the function does not satisfy the PDE for all values of the independent variables and their corresponding partial derivatives. This indicates that the function is not a valid solution to the PDE.

4. Can a function be both a solution and a non-solution to a PDE?

No, a function cannot be both a solution and a non-solution to a PDE. It can only be one or the other. If a function satisfies the PDE, it is a solution. If it does not satisfy the PDE, it is a non-solution.

5. How important is it to verify or refute a function as a solution to a PDE?

It is crucial to verify or refute a function as a solution to a PDE because it ensures the accuracy and validity of the mathematical model being used. If a function is incorrectly identified as a solution to a PDE, it can lead to incorrect predictions and analysis of the physical phenomenon being studied.

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