Grad of a generalised scalar function

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The discussion focuses on proving the relationship between the gradient of a scalar function f(r) and the vector r. The user initially attempts to express the gradient as ∇f = (df/dr) * r/r but realizes a mistake and corrects it to ∇f = (1/r)(df/dr) * r. The application of the chain rule is emphasized to derive the correct form of the gradient. Additionally, the user seeks clarification on proving the Laplacian of f, leading to confusion about the second derivative and its relation to the gradient. The conversation concludes with the realization that the chain rule applies similarly in both cases.
Phyrrus
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Homework Statement



r=xi+yj+zk and r =\sqrt{x^2 + y^2 + z^2} Let f(r) be a C2 scalar function

Prove that \nablaf = \frac{1}{2}\frac{df}{dr}r

Homework Equations



Vector identities?

The Attempt at a Solution



\nablaf = (\frac{df}{dx} , \frac{df}{dy} , \frac{df}{dz})
= df/dr]?
= \frac{df}{dr}\hat{r} (unit vector of r)
= \frac{df}{dr}r\frac{1}{r}?

I'm pretty sure what I've attempted isn't mathematically correct in the slightest, though in my head it seems to make some geometric sense. Am I even close though?
 
Last edited:
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Formally f(r) is the derivative with respect to vector r: f(r)=(df/dr)=(df/dr)˙r/r. To prove the statement in the problem expand f(r) with x, y, z, and see if it is equal to (df/dr)˙r/r, using that r=√(r2)

ehild
 
Last edited:
Sorry, I made a mistake in the OP, it's supposed to be

\nablaf = \frac{1}{r}\frac{df}{dr}r

Thanks for your reply, but I'm not really sure where the r=√(r^2) come into it? How do you arrive at the 1/r out the front? The only thing I can think of is that it's supposed to reduced it to a magnitude of only df/dr?
 
Sorry, I also made a mistake, leaving out 1/r. df/dr is multiplied by the unit vector \hat{\vec r}, so \nabla f=\frac{df}{dr}\vec r /r.

You get it by applying the chain rule: \frac{df(\sqrt{(\vec r)^2})}{d\vec r}=\frac{df}{dr} \frac{d \sqrt{(\vec r)^2}}{d \vec r}=\frac{df}{dr}\left(\frac{1}{2}\frac{1}{\sqrt{( \vec r)^2} }\right)2 \vec r.

ehild
 
Thanks mate, finally got it in the end. Just a little bit stuck on part b of the question though, have to prove that:

\nabla^2f = \frac{2}{r}\frac{df}{dr}+\frac{d^2f}{dr^2}

I've been using the vector identities so that I get:

= \frac{1}{r}\frac{df}{dr}(\nabla\bulletr) +(r\bullet\nabla)\frac{1}{r}\frac{df}{dr}

from here I get down to \frac{3}{r}\frac{df}{dr}+r\bullet(\frac{1}{r}\nabla\frac{df}{dr}+\frac{df}{dr}\nabla\frac{1}{r})

This is where I am confused, what is \nabla\frac{df}{dr} is it just \frac{d^2f}{dr^2}?

And I keep getting \frac{df}{dr}\nabla\frac{1}{r}=\nablaf, which doesn't seem right.
 
Phyrrus said:
from here I get down to \frac{3}{r}\frac{df}{dr}+r\bullet(\frac{1}{r}\nabla\frac{df}{dr}+\frac{df}{dr}\nabla\frac{1}{r})

This is where I am confused, what is \nabla\frac{df}{dr} is it just \frac{d^2f}{dr^2}?

No, it is \frac{d^2f}{dr^2}\frac{\vec r}{r}

ehild
 
Ahhhh yes, got it, it all works out now. Thanks a lot mate.
But just how did you get that? I presume it's quite similar to the first question, chain rule again?
 
Yes, it is the chain rule again.:smile:

ehild
 

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