Using Gauss' Theorem to Show Integral Convergence in Divergence Theorem

In summary, the conversation is about using Gauss' Theorem to show that if the function psi approaches 1/r as r approaches infinity, then the integral of psi times the Laplacian of psi over all space is less than 0. The conversation includes the use of the divergence theorem and taking the gradient in spherical coordinates. The final conclusion rests on the surface normal being radial and the integrand being proportional to 1/r, resulting in the integral being equal to 0 on the boundary of all space.
  • #1
latentcorpse
1,444
0
This may well be the wrong place to post this so apologies for that if it's the case.

Anyway, I'm stuck on this question, any help appreciated

Use Gauss' Theorem to show that:
(i) If [itex] \psi($\mathbf{r}$) ~ \frac{1}{r} [/itex] as [itex] r \rightarrow \infty [/itex],


then,
[itex] \int_V {\psi \nabla^{2} \psi} dV \less 0 [/itex] where the integral is over all space.

Hint: take [itex] \mathbf{V}=\psi \nabla \psi [/itex]

My initial plan of attack was to write the integral as

[itex] \int_V {\nabla \cdot \mathbf{V}} dV [/itex]

which then becomes using the divergence theorem

[itex] \oint_S {\mathbf{V} \cdot \mathbf{n}} dS [/itex]

This probably isn't right because I then have no clue how to show this is less than 0
 
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  • #2
latentcorpse said:
My initial plan of attack was to write the integral as

[itex] \int_V {\nabla \cdot \mathbf{V}} dV [/itex]

Careful;

[tex]\nabla \cdot \mathbf{V}=\nabla \cdot (\psi \nabla \psi)=\psi (\nabla \cdot \nabla \psi)+\nabla\psi \cdot \nabla \psi \neq \psi\nabla^2\psi[/tex]
 
  • #3
Thanks,
ok so could i make it
[itex] \int_V {\psi \nabla^{2} \psi} dV = \int_V {\nabla \cdot \mathbf{V} - \nabla \psi \cdot \nabla \psi} dV = \oint_S {V \cdot \mathbf{n}} dS - \int_V {\nabla \psi \cdot \nabla \psi} dV [/itex]

Now I guess I need to show [itex] \oint_S {V \cdot \mathbf{n}} dS < \int_V {\nabla \psi \cdot \nabla \psi} dV [/itex] in order to prove that [itex] \int_V {\psi \nabla^{2} \psi} dV <0 [/itex]

Any advice on how to do that ...
 
  • #4
latentcorpse said:
Thanks,
ok so could i make it
[itex] \int_V {\psi \nabla^{2} \psi} dV = \int_V {\nabla \cdot \mathbf{V} - \nabla \psi \cdot \nabla \psi} dV = \oint_S {V \cdot \mathbf{n}} dS - \int_V {\nabla \psi \cdot \nabla \psi} dV [/itex]

Now I guess I need to show [itex] \oint_S {V \cdot \mathbf{n}} dS < \int_V {\nabla \psi \cdot \nabla \psi} dV [/itex] in order to prove that [itex] \int_V {\psi \nabla^{2} \psi} dV <0 [/itex]

Any advice on how to do that ...

First note that [itex]\nabla \psi \cdot \nabla \psi=||\nabla \psi||^2\geq 0[/itex]

Then use the fact that your surface integral is at the boundary of all space (i.e. at [itex]r\to\infty[/itex]), where [tex]\psi\sim\frac{1}{r}[/tex] and hence [tex]\nabla\psi\sim\frac{1}{r^2}[/tex]

What does that make your surface integral for [itex]r\to\infty[/itex]?
 
  • #5
ahh ok. how's this then
[itex] \oint_S \mathbf{V} \cdot \mathbf{n} dS = \oint_S (\frac{1}{r} \frac{1}{r^2}) \cdot \mathbf{n} dS =\oint_S \frac{1}{r^3} \cdot \mathbf{n} dS[/itex]

and
[itex] \int_V {|| \nabla \psi ||}^{2} dV=\int_V {\frac{1}{r^4} dV [/itex]

sorry but i still don't see how this is going to show it's less than 0.


Also if [itex] \psi = \frac{1}{r} = (r_j r_j)^{-\frac{1}{2}}[/itex] i get that [itex] \nabla \psi =-\frac{1}{2} (r_j r_j)^{-\frac{3}{2}} 2r_i = -\frac{r_i}{r^3} [/itex] as opposed to [itex] \nabla \psi = \frac{1}{r^2} [/itex]. I assume this has something to do with it being at the boundary of all space. Can you explain this?
 
  • #6
latentcorpse said:
ahh ok. how's this then
[itex] \oint_S \mathbf{V} \cdot \mathbf{n} dS = \oint_S (\frac{1}{r} \frac{1}{r^2}) \cdot \mathbf{n} dS =\oint_S \frac{1}{r^3} \cdot \mathbf{n} dS[/itex]

Sure, and since [itex]dS\sim r^2[/itex], the integrand [itex]\sim \frac{1}{r}[/itex] And since[itex]r\to\infty[/itex] for the entire surface, that means the integrand (and hence the integral) is zero doesn't it?:wink:


and
[itex] \int_V {|| \nabla \psi ||}^{2} dV=\int_V {\frac{1}{r^4} dV [/itex]

All you need to know is that [tex]\int_V {|| \nabla \psi ||}^{2} dV>0[/tex] since the integrand is positive definite.

That gives you zero minus some positive number, which is of course less than zero.
 
  • #7
cheers. could you explain that bit about how you got [itex] \nabla \phi [/itex] to be [itex] \frac{1}{r^2} [/itex] though. still a bit confused there.
 
  • #8
latentcorpse said:
cheers. could you explain that bit about how you got [itex] \nabla \phi [/itex] to be [itex] \frac{1}{r^2} [/itex] though. still a bit confused there.

Another way to write [itex]\psi \sim \frac{1}{r}[/itex] is [itex]\psi=\frac{k}{r}[/itex] for some unknown constant 'k'...then just take the gradient in spherical coordinates: you should end up with [tex]\nabla\psi=\frac{-k}{r^2}\sim\frac{1}{r^2}[/tex].
 
  • #9
in spehrical polars the gradient is [itex] \nabla \chi = (\frac{\partial \chi}{\partial r},\frac{1}{r} \frac{\partial \chi}{\partial \theta}, \frac{1}{\sin{\theta}} \frac{\partial \chi}{\partial \phi}) [/itex]

This doesn't give me what I want when I let [itex] \chi = \frac{1}{r} [/itex]
 
  • #10
latentcorpse said:
in spehrical polars the gradient is [itex] \nabla \chi = (\frac{\partial \chi}{\partial r},\frac{1}{r} \frac{\partial \chi}{\partial \theta}, \frac{1}{\sin{\theta}} \frac{\partial \chi}{\partial \phi}) [/itex]

This doesn't give me what I want when I let [itex] \chi = \frac{1}{r} [/itex]

Why not?

[tex]\frac{\partial}{\partial\theta} \left(\frac{1}{r}\right)=0[/tex]

[tex]\frac{\partial}{\partial\phi} \left(\frac{1}{r}\right)=0[/tex]

and

[tex]\frac{\partial}{\partial r} \left(\frac{1}{r}\right)=\frac{-1}{r^2}[/tex]
 
  • #11
ok so then [itex] \nabla \psi = (-\frac{1}{r^2},0,0) = -\frac{1}{r^2} \vec{e_r} [/itex]
Problems I have with this are threefold:
(i)first of all this is negative and you said it was [itex] \frac{1}{r^2} [/itex] which is positive
(ii)also [itex] \frac{1}{r^2} [/itex] doesn't specify a direction whereas it should be in the [itex] \vec{e_r} [/itex] direction, no?

(iii)furthermore this answer disagrees with the one i got in post 5 in this thread when I took the grad in cartesians - this is the most worrying part!
 
  • #12
latentcorpse said:
ok so then [itex] \nabla \psi = (-\frac{1}{r^2},0,0) = -\frac{1}{r^2} \vec{e_r} [/itex]
Problems I have with this are threefold:
(i)first of all this is negative and you said it was [itex] \frac{1}{r^2} [/itex] which is positive

It doesn't matter whether its positive or negative: [tex]\lim_{r\to \infty} \frac{k}{r}=0[/tex] whether k is positive or negative and that's all the final conclusion rests on.

(ii)also [itex] \frac{1}{r^2} [/itex] doesn't specify a direction whereas it should be in the {latex] \vec{e_r} [/itex] direction, no?

Okay, so to be more accurate you could say that [tex]\nabla \psi \sim \frac{-1}{r^2} \vec{e_r}[/tex] But the surface normal is also radial so you still end up with the integrand being proportional to 1/r, and hence being zero on the boundary of all space.
(iii)furthermore this answer disagrees with the one i got in post 5 in this thread when I took the grad in cartesians - this is the most worrying part!

No it doesn't. Remember,

[tex]\vec{e_r}=\frac{x\vec{e_x}+y\vec{e_y}+z\vec{e_z}}{\sqrt{x^2+y^2+z^2}}=\sum_i \frac{\vec{r_i}}{r}[/tex]

And so,

[tex]\nabla\psi= \frac{-1}{r^2} \vec{e_r}=\sum_i \frac{-\vec{r_i}}{r^3}[/tex]
 
  • #13
thanks a lot mate
 
  • #14
Welcome :smile:
 

What is the Divergence Theorem?

The Divergence Theorem, also known as Gauss's Theorem, is a fundamental theorem in vector calculus that relates the surface integral of a vector field to the volume integral of its divergence over a closed surface in three-dimensional space. It is a powerful tool for solving problems in electromagnetism, fluid mechanics, and other fields that involve vector fields.

What is the formula for the Divergence Theorem?

The formula for the Divergence Theorem is ∫∫∫V (div F) dV = ∫∫S F · dS, where V is a closed volume bounded by a surface S, F is a vector field, div F is the divergence of F, and dV and dS are the volume and surface elements, respectively.

What is the intuition behind the Divergence Theorem?

The Divergence Theorem can be thought of as a generalization of the Fundamental Theorem of Calculus in multiple dimensions. It states that the flux (or flow) of a vector field through a closed surface is equal to the sum of all the sources and sinks of the field within the enclosed volume.

What are some applications of the Divergence Theorem?

The Divergence Theorem has many practical applications in physics and engineering. It is used to calculate electric flux and magnetic flux in electromagnetism, fluid flow through a surface in fluid mechanics, and mass conservation in thermodynamics. It also has applications in computer graphics, where it is used to simulate fluid dynamics and other phenomena.

What are the limitations of the Divergence Theorem?

The Divergence Theorem only applies to closed surfaces, so it cannot be used for open surfaces or surfaces with holes. Additionally, the vector field must be continuous and differentiable within the enclosed volume for the theorem to hold. It also assumes that the surface and volume elements are infinitesimally small, which may not always be the case in practical applications.

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