BvU said:
Agree: F = minus the gradient of U.
yes, U(r0) is a constant. I understand that the next step is the one you don't like:
because it does something you didn't know about:and equation 2 was:
Correct ?
In (B), with which you still agree, you see that ##\vec F## is the gradient of something that depends on ##r = |\vec r|## only.
You apparently don't want to run ahead and use the gradient in spherical coordinates expression, but you were already handed something for the derivative of an integral:
At this point, I don't know what to add unless you can specify a more precise question. From the (later) lecture notes in the picture I gather you are used to gradients in xyz coordinates. Working around a gradient from ##xyz## to ##r\theta\phi## is what the picture does, so no point in repeating.
In case your problem begins a little earlier, namely where ## \vec F = -\vec\nabla U## is written as ## \vec F(\vec r) = -\vec\nabla_{\vec r} U(|\vec r|)## maybe the following helps a little: We've seen that both F and U depend on |r| only. From F (a vector) we've constructed a U (a scalar) by integrating. Now we are going back by taking a gradient, which is differentiating, but in a number of dimensions corresponding to the number of coordinates.
Since there is no ##\theta## or ##\phi## dependence in U, it is clear that differentiating wrt those gives zeros: there is no way to get a ##\theta## or ##\phi## component of ##\vec F##, whatever the multiplying factors (like ##\sin\theta## or r or whatever).
The only change in U occurs when r changes. Therefore the only direction F can point is in the r direction. (perpendicular to the spheres with constant r, if you want).
Perhaps the idea of the chain rule being applied here makes it acceptable for you ?
U is a function of ##r = |\vec r|## only. A gradient is kind of a derivative wrt a vector (artistic liberty, translated as physicists liberty to use shorthand for mathematical operations...)
You have ## \vec F = -\vec\nabla U = \frac {dU}{dr} \ \vec\nabla {r} =\frac {dU}{dr} \ \frac {dr}{d\vec r}##
If I confuse you or talk nonsense, I'd like to be corrected.
Yes, I think my lecturer has used the chain rule without stating it explicitly, which is the source of my confusion.
Using the last line in post #12, ## \vec F = -\vec\nabla U = \frac {dU}{dr} \ \vec\nabla {r} =\frac {dU}{dr} \ \frac {dr}{d\vec r}##
We have:
##\underline{F}(\underline{r})=-\underline{\nabla}_\underline{r}U(r)##
##\underline{F}(\underline{r})=-\frac{dU}{d\underline{r}}##
##\underline{F}(\underline{r})=-\frac{dr}{d\underline{r}}\frac{dU}{dr}##
##\underline{F}(\underline{r})=-(\underline{\nabla}r)(-\left.f(r')\right|_{r'=r})##
##\underline{F}(\underline{r}) = \left.(\underline{\nabla}r)f(r')\right|_{r'=r}##
(Note that this is the exact equation that appears directly before Equation 2, so I think this is probably how my lecturer has done it.)
##\underline{F}(\underline{r})=\underline{\nabla}rf(r)##
##\underline{F}(\underline{r})=f(r)\underline{\nabla}r ##
Which is Equation 2.
However, I don't understand the equation in the last line of post #12. Maybe it is the notation or the gradient function itself that I am having difficulty understanding. Specifically, that equation implies:
##\underline{\nabla}r=\frac{dr}{d\underline{r}}=\frac{d}{d\underline{r}}r##
I don't understand the meaning of this, i.e. how it can be that the vector ##\underline{r}## is written on the bottom of the derivative, and the magnitude of the vector is written on the top, taking into consideration ##\underline{r}=r\hat{r}##.
For example, if we had ##f=2x##, then ##\underline{\nabla}f=\frac{df}{dx}i=2i##. That is, the variable ##x## appears on the bottom of the derivative, and the answer is the derivative of the function with respect to x, multiplied by the unit vector ##i## in the x direction. That is my understanding of the gradient function and how it is denoted.
So, I don't understand the equation ##\underline{\nabla}r=\frac{dr}{d\underline{r}}=\frac{d}{d\underline{r}}r##. The symbol ##r## is just a number and does not have components in the directions of any axes, unlike f. The symbol ##\underline{r}## is the position vector of a point, not a co-ordinate, like x. So, I'm unable to draw any parallels with how I have seen the gradient function used before.
Sorry if this all sounds a bit confusing!