Apostol's Calculus Vol. II Question on Gradients

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The discussion centers on a calculus problem regarding the gradient of a function f(x,y,z) being parallel to the vector x i + y j + z k. Participants explore various approaches to prove that f assumes equal values at points (0,0,a) and (0,0,-a). One user attempts to use path integrals and the properties of the gradient but expresses uncertainty about the assumptions regarding the function h(t). The conversation reveals confusion over the intended direction of the proof and the nature of the function h, with suggestions to change the path of integration to better understand the problem. The thread highlights the complexities of applying path integrals in this context and the need for further exploration.
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Homework Statement


If \nabla f(x,y,z) is always parallel to x \hat i + y \hat j + z \hat k, show that f must assume equal values at the points (0,0,a) and (0,0,-a).

The Attempt at a Solution


I tried a number of things - inspecting the values arrived at when computing the cross product of the gradient and the position vector, writing r(t)=(0,0,t) and then integrating \nabla f(r(t))\cdot r'(t) from -a to a, nothing is getting me anywhere. I also found this old thread: https://www.physicsforums.com/showthread.php?t=165790 but I don't see what Mathgician is getting at. In particular, f(0,0,a)-f(0,0,-a) is not necessarily equal to -2ak as the poster mentions toward the bottom.
 
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Look at the path integral of grad(f) along a circle connecting (0,0,a) and (0,0,-a).
 
If ##f_x = \lambda x,\ f_y=\lambda y,\ f_z=\lambda z## can't you derive what ##f(x,y,z)## must be by taking anti-partial derivatives?
 
Dick said:
Look at the path integral of grad(f) along a circle connecting (0,0,a) and (0,0,-a).

Unfortunately we have not covered path integrals yet. Thanks though!
 
LCKurtz said:
If ##f_x = \lambda x,\ f_y=\lambda y,\ f_z=\lambda z## can't you derive what ##f(x,y,z)## must be by taking anti-partial derivatives?

I have no reason to think that ##\nabla f(x,y,z)=\lambda(x,y,z)## - although I could solve this if I could assume that. The conditions, as far as I can tell, just say that for some scalar field ##h## we have that ##\nabla f(x,y,z) = [h(x,y,z)](x,y,z)##. In particular, I tried this approach: Let ##r(t)=(0,0,t)##. Then let ##g(t)=f[r(t)]##, so ##g'(t)=\nabla f [r(t)] \cdot r'(t)##. Now consider \int_{-a}^a \nabla f[r(t)]\cdot r'(t) dt. Now since the gradient is parallel to the position we have ##\nabla f (0,0,t) = (0,0,h(t) t)##, and since ##r'(t)=(0,0,1)## our integral is just \int_{-a}^a h(t) t dt. If ##h(t)## is even, the result follows. It may still be possible if ##h(t)## is not even, however note that ##h(t)## cannot be odd (which is an interesting result as well... I think anyway).

I doubt, however, that this was the intended direction for the proof to take... and since I can't prove that there's any other reason to think that ##h(t)## should be even, it's not conclusive. On the other hand, if someone comes up with a way to have ##\nabla f(x,y,z)= [h(x,y,z)](x,y,z)## where the function ##h## is odd with respect to ##z##, that would indicate that I have over-generalized the intended problem, and it probably is only intended to be ##\nabla f(x,y,z) = \lambda (x,y,z)##.
 
Last edited:
process91 said:
I have no reason to think that ##\nabla f(x,y,z)=\lambda(x,y,z)## - although I could solve this if I could assume that.

Oh, OK. I misunderstood the problem. I may have time to look at it some more tomorrow.
 
LCKurtz said:
Oh, OK. I misunderstood the problem. I may have time to look at it some more tomorrow.

Thanks!
 
process91 said:
I have no reason to think that ##\nabla f(x,y,z)=\lambda(x,y,z)## - although I could solve this if I could assume that. The conditions, as far as I can tell, just say that for some scalar field ##h## we have that ##\nabla f(x,y,z) = [h(x,y,z)](x,y,z)##. In particular, I tried this approach: Let ##r(t)=(0,0,t)##. Then let ##g(t)=f[r(t)]##, so ##g'(t)=\nabla f [r(t)] \cdot r'(t)##. Now consider \int_{-a}^a \nabla f[r(t)]\cdot r'(t) dt. Now since the gradient is parallel to the position we have ##\nabla f (0,0,t) = (0,0,h(t) t)##, and since ##r'(t)=(0,0,1)## our integral is just \int_{-a}^a h(t) t dt. If ##h(t)## is even, the result follows. It may still be possible if ##h(t)## is not even, however note that ##h(t)## cannot be odd (which is an interesting result as well... I think anyway).

I doubt, however, that this was the intended direction for the proof to take... and since I can't prove that there's any other reason to think that ##h(t)## should be even, it's not conclusive. On the other hand, if someone comes up with a way to have ##\nabla f(x,y,z)= [h(x,y,z)](x,y,z)## where the function ##h## is odd with respect to ##z##, that would indicate that I have over-generalized the intended problem, and it probably is only intended to be ##\nabla f(x,y,z) = \lambda (x,y,z)##.

That IS a path integral. Now try changing the path to say r(t)=(0,a*sin(t),a*cos(t)) for t in [0,pi].
 
Dick said:
That IS a path integral. Now try changing the path to say r(t)=(0,a*sin(t),a*cos(t)) for t in [0,pi].

Awesome - the book doesn't cover path integrals explicitly for two more chapters, good to know they aren't much different than what I already have covered. Thanks!
 
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