Is the Chain Rule Applied to Spherical Polar Coordinates Different?

AI Thread Summary
The discussion focuses on the application of the chain rule in spherical polar coordinates, particularly regarding the derivatives of variables. Participants clarify the relationships between the derivatives, noting that the inverse relationship for partial derivatives does not hold in multi-variable contexts. The transformation from Cartesian to spherical coordinates is explored, with emphasis on deriving expressions for r, θ, and φ. The conversation also addresses the complexities of differentiating functions of multiple variables, highlighting the need for careful application of the chain rule. Overall, the thread emphasizes the importance of understanding derivative relationships in different coordinate systems.
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Homework Statement
##x=r sin\theta cos\phi, y=rsin\theta sin\phi, z=rcos\theta##
Find ##\delta f/\delta x##and##\delta r/\delta x## treating r as a function of the cartesian coordinates
Given f is a function of r only, show
##\delta f^2/\delta x = (x/r)(df/dr)##
and
##\delta ^2 *f/\delta x^2 = (1/r)(df/dr) + (x^2/r)(d/dr)(1/r)(df/dr)##
Relevant Equations
?
Ive found ##\delta x/\delta r## as ##sin\theta cos\phi##
##\delta r/\delta x## as ##csc\theta sec\phi##
But unsure how to do the second part? Chain rule seems to give r/x not x/r?
 
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physconomics said:
Ive found ##\partial f\over \partial x## as ##\sin\theta \cos\phi##
You can't mean that. Independent of ##f## ?
 
physconomics said:
Ive found ##\delta f/\delta x## as ##sin\theta cos\phi##
##\delta r/\delta x## as ##csc\theta sec\phi##
But unsure how to do the second part? Chain rule seems to give r/x not x/r?

Please show your actual work, not just your end result.

Also, note that ##\partial## is written \partial in LaTeX.
 
BvU said:
You can't mean that. Independent of ##f## ?
Sorry, I meant ##\frac{\partial x}{\partial r}##
 
physconomics said:
Sorry, I meant ##\frac{\partial x}{\partial r}##
It is not true for partial derivatives that ##\partial x/\partial r = (\partial r/\partial x)^{-1}##
 
Orodruin said:
Please show your actual work, not just your end result.
And then we will try to work our way through this very relevant exercise :smile: .
 
Orodruin said:
It is not true for partial derivatives that ##\partial x/\partial r = (\partial r/\partial x)^{-1}##
Okay, so how else would I get ##\partial x/\partial r##?
 
Invert the transformation
$$x=r \sin\theta \cos\phi, \quad y=r\sin\theta \sin\phi, \quad z=r\cos\theta$$ to $$r = ...(x, y,z),\quad \phi = ...,\quad \theta = ...$$

(advice: use \sin and \cos, \log etc in ##\LaTeX##)
 
BvU said:
Invert the transformation

x=rsinθcosϕ,y=rsinθsinϕ,z=rcosθx=rsin⁡θcos⁡ϕ,y=rsin⁡θsin⁡ϕ,z=rcos⁡θ​

to

r=...(x,y,z),ϕ=...,θ=...r=...(x,y,z),ϕ=...,θ=...​
(advice: use \sin and \cos, \log etc in LATEXLATEX)
Okay so I get
r=√x2+y2+z2r=x2+y2+z2
##\theta = \cos^{-1} (\frac {z} {\sqrt{x^2 + y^2 + z^2})##
ϕ=tan−1(yx)ϕ=tan−1⁡(yx)

Am I right in thinking this makes

∂r∂x=sinθcosϕ∂r∂x=sin⁡θcos⁡ϕ?
 
  • #10
But there are tricks available -- ah you are on a good track. Differentiating ##r^2 = x^2 + y^2 + z^2## is easier to deal with.

Use \sqrt { ...} and always preview to check parentheses are right.
 
  • #11
BvU said:
But there are tricks available -- ah you are on a good track. Differentiating ##r^2 = x^2 + y^2 + z^2## is easier to deal with.

Use \sqrt { ...} and always preview to check parentheses are right.
Oh god of course, thank you.
So ##\frac{\partial r}{\partial x} = \frac{x}{r}##
And then from that I can show
##\frac{\partial f}{\partial x} = \frac{\partial f}{\partial r} \frac{\partial r}{\partial x} = \frac{df}{dr}\frac{x}{r}##
Im guessing I just use the chain rule for the next part?

Sorry for the state of my LaTeX maths
 
  • #12
Good ! Keep going ...

physconomics said:
Sorry for the state of my LaTeX maths
No need. You are obviously eager to learn and we are equally eager to assist.
 
  • #13
BvU said:
Good ! Keep going ...

No need. You are obviously eager to learn and we are equally eager to assist.

Right so I'm a bit stuck, I'm getting ##\frac{\partial^2 f}{\partial x^2} = \frac{\partial}{\partial x}(\frac{df}{dr}\frac{x}{r}) = \frac{\partial}{\partial x}(\frac{df}{dr}) \frac{x}{r} + \frac{df}{dr}\frac{1}{r} ##
where
##\frac{\partial}{\partial x}(\frac{df}{dr}) = \frac{\partial}{\partial x}(\frac{r}{x} \frac{\partial f}{\partial x}) = (\frac{-r}{x^2} \frac{\partial f}{\partial x}) + (\frac{r}{x}\frac{\partial^2 f}{\partial x^2})##
Is this correct? It doesn't lead me to the right answer
 
  • #14
BvU said:
Invert the transformation
$$x=r \sin\theta \cos\phi, \quad y=r\sin\theta \sin\phi, \quad z=r\cos\theta$$ to $$r = ...(x, y,z),\quad \phi = ...,\quad \theta = ...$$

(advice: use \sin and \cos, \log etc in ##\LaTeX##)

It should be noted that you can do this without actually inverting the coordinate relations. The general theory is based on the chain rule. For a function of one parameter only, say ##y(x)##, you would have
$$
1 = \frac{dx}{dx} = \frac{dy}{dx} \frac{dx}{dy}.
$$
This is the reason that ##dx/dy = (dy/dx)^{-1}## in this case (just solve for ##dx/dy##). However, for functions of several variables, say ##y^i(x^1, \ldots, x^n)##, the chain rule would instead give you
$$
\delta^i_j = \frac{\partial y^i}{\partial y^j} = \sum_{k} \frac{\partial y^i}{\partial x^k} \frac{\partial x^k}{\partial y^j}.
$$
Thus, from here you cannot just divide by a factor from the RHS to obtain ##\partial x^k/\partial y^j## since what you have is a sum. However, if you define the matrices ##A## and ##B## defined as
$$
A = \begin{pmatrix}\frac{\partial x^1}{\partial y^1} & \frac{\partial x^1}{\partial y^2} & \ldots \\
\frac{\partial x^2}{\partial y^1} & \frac{\partial x^2}{\partial y^2} & \ldots \\
\vdots & \vdots & \ddots \end{pmatrix}, \qquad
B = \begin{pmatrix}\frac{\partial y^1}{\partial x^1} & \frac{\partial y^1}{\partial x^2} & \ldots \\
\frac{\partial y^2}{\partial x^1} & \frac{\partial y^2}{\partial x^2} & \ldots \\
\vdots & \vdots & \ddots \end{pmatrix},
$$
then the relation can be rewritten
$$
1_n = BA,
$$
where ##1_n## is the ##n \times n## unit matrix. In other words, ##A = B^{-1}##. Thus, if you compute all the derivatives ##\partial y^i/\partial x^j##, you can find ##\partial x^i/\partial y^j## by matrix inversion.

However, if you are unfamiliar with matrices, it is also fine to solve the linear system of equations. For example, in polar coordinates on ##\mathbb R^2##: ##x = r\cos\phi##, ##y = r\sin\phi##, you would find
$$
1 = \frac{\partial x}{\partial x} = \frac{\partial x}{\partial r} \frac{\partial r}{\partial x} + \frac{\partial x}{\partial \phi} \frac{\partial \phi}{\partial x} = \cos\phi \frac{\partial r}{\partial x} - r \sin\phi \frac{\partial \phi}{\partial x}
$$
and
$$
0 = \frac{\partial y}{\partial x} = \frac{\partial y}{\partial r} \frac{\partial r}{\partial x} + \frac{\partial y}{\partial \phi} \frac{\partial \phi}{\partial x} = \sin\phi \frac{\partial r}{\partial x} + r \cos\phi \frac{\partial \phi}{\partial x}
$$
from which you can solve directly for ##\partial r/\partial x## and ##\partial \phi/\partial x##.
 
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  • #15
physconomics said:
Right so I'm a bit stuck, I'm getting ##\frac{\partial^2 f}{\partial x^2} = \frac{\partial}{\partial x}(\frac{df}{dr}\frac{x}{r}) = \frac{\partial}{\partial x}(\frac{df}{dr}) \frac{x}{r} + \frac{df}{dr}\frac{1}{r} ##
where
##\frac{\partial}{\partial x}(\frac{df}{dr}) = \frac{\partial}{\partial x}(\frac{r}{x} \frac{\partial f}{\partial x}) = (\frac{-r}{x^2} \frac{\partial f}{\partial x}) + (\frac{r}{x}\frac{\partial^2 f}{\partial x^2})##
Is this correct? It doesn't lead me to the right answer
Note that
$$
\frac{\partial}{\partial x} \frac{x}{r} \neq \frac 1r
$$
as ##r## depends on ##x##.
 
  • #16
Orodruin said:
Note that
$$
\frac{\partial}{\partial x} \frac{x}{r} \neq \frac 1r
$$
as ##r## depends on ##x##.
Is ##\frac{\partial}{\partial x} \frac{x}{r} = \frac{r - \frac{x^2}{r}}{r^2}##
 
  • #17
physconomics said:
Is ##\frac{\partial}{\partial x} \frac{x}{r} = \frac{r - \frac{x^2}{r}}{r^2}##

Yes, although writing:

##\frac{\partial}{\partial x} \frac{x}{r} = \frac{r^2 - x^2}{r^3}##

seems a bit more logical.
 
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