Gradient (1/r): Homework Equation Solutions

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Homework Help Overview

The discussion revolves around the gradient of the function \(1/r\), exploring its representation in both spherical and Cartesian coordinates. Participants are examining the mathematical properties and implications of this gradient in the context of vector calculus.

Discussion Character

  • Mathematical reasoning, Problem interpretation, Assumption checking

Approaches and Questions Raised

  • Participants discuss the gradient of \(1/r\) and its derivation in different coordinate systems. Questions arise regarding the proof of the gradient's expression and the validity of negative signs in the context of increasing \(r\). There is also exploration of whether the gradient can be expressed in Cartesian coordinates.

Discussion Status

Several participants have provided insights into the gradient's calculation in both spherical and Cartesian coordinates. There is an ongoing examination of the signs in the expressions and the implications of the function's behavior as \(r\) changes. No consensus has been reached, but productive dialogue continues.

Contextual Notes

Some participants note the importance of showing effort in homework questions, and there are discussions about the assumptions underlying the coordinate systems used in the calculations.

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Homework Statement



gradient(1/r) = r(hat) / r^2

Homework Equations


r = (x-x')i + (y-y')j + (z-z')k

[Mentor Note -- Poster was reminded to always show effort on schoolwork questions]
 
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how do you prove that?
 
In spherical coordinates, the gradient of a scalar function f is:
[itex]\vec\nabla f(r, \theta, \phi) = \frac{\partial f}{\partial r}\hat r+ \frac{1}{r}\frac{\partial f}{\partial \theta}\hat\theta+ \frac{1}{r \sin\theta}\frac{\partial f}{\partial \phi}\hat\phi[/itex].
And we have [itex]\frac{d}{dr}\frac 1 r=-\frac{1}{r^2}[/itex].
 
can this be done in cartesian coordinates?
 
Or, in Cartesian coordinates,
[tex]\frac{1}{r}= \frac{1}{x^2+ y^2+ z^2}= (x^2+ y^2+ z^2)^{-1/2}[/tex]

[tex]\left(\frac{1}{r}\right)_x= -\frac{1}{2}(x^2+ y^2+ z^2)^{-3/2}(2x)= -\frac{rcos(\theta)sin(\phi)}{r^3}= -\frac{1}{r^3} (rcos(\theta)sin(\phi))[/tex]

[tex]\left(\frac{1}{r}\right)_y= -\frac{1}{2}(x^2+ y^2+ z^2)^{-3/2}(2y)= -\frac{rsin(\theta)sin(\phi)}{r^3}= -\frac{1}{r^3} (rsin(\theta)sin(\phi)([/tex]

[tex]\left(\frac{1}{r}\right)_z= -\frac{1}{2}(x^2+ y^2+ z^2)^{-3/2}(2z)= -\frac{rcos(\phi)}{r^3}= -\frac{1}{r^3} (rcos(\phi))[/tex]

So that [tex]\nabla \frac{1}{r}= -\frac{1}{r^3}\vec{r}= -\frac{1}{r^2}\frac{\vec{r}}{r}= -\frac{1}{r^2}\hat{r}[/tex]

Where [itex]\hat{r}[/itex] is the unit vector in the direction of [itex]\vec{r}[/itex].
 
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but this negative
 
kunu said:
but this negative
Yes it is. 1/r decreases with increasing r.
 
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Sometimes it's easier to work in Cartesian coordinates. For any function ##\Phi(r)## you have
$$\vec{\nabla} \Phi(r)=\Phi'(r) \vec{\nabla} r.$$
Now
$$\vec{\nabla} r= \begin{pmatrix} \partial_1 \\ \partial_2 \\ \partial_3 \end{pmatrix} \sqrt{x_1^2+x_2^2+x_3^2}.$$
The first component thus reads
$$\partial_1 r=2 x_1 \frac{1}{2 \sqrt{x_1^2+x_2^2+x_3^2}}=\frac{x_1}{r}.$$
In the same way you get the other two components, leading to
$$\vec{\nabla} r= \frac{\vec{r}}{r}=\hat{r}.$$
Thus
$$\vec{\nabla} \frac{1}{r} = -\frac{1}{r^2} \hat{r}.$$
 
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