Gradients of harmonic functions

In summary, the conversation discusses the relationship between the gradient of a harmonic function and the divergence and curl of that function. Part (a) and (b) are completed and the focus is now on understanding the gradient of a harmonic function and how to compute its divergence and curl. Part (c) asks for the computation of these values, assuming that \mathbf{F} is the gradient of a harmonic function. Part (d) provides an example of a harmonic function and asks for the flux of \mathbf{F} through a closed surface.
  • #1
musicmar
100
0

Homework Statement


a. show that delφ=div(gradφ) for any function φ.
b. show that φ is harmonic if and only if div(gradφ)=o.
c. Show that if F is the gradient of a harmonic function, then curl(F)=0 and div(F)=0.
d. Show F=<xz,-yz,1/2(x2-y2)> is the gradient of a harmonic function. What is the flux of F through a closed surface?


The Attempt at a Solution


I did parts (a) and (b), but am now stuck on (c) (and thus (d)). Can someone explain to me what the gradient of a harmonic function is and how you find one? Thanks.
 
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  • #2
"[tex]\mathbf{F}[/tex] is the gradient of a harmonic function" just means that there exists a harmonic function [tex]\varphi[/tex] ([tex]\nabla^2\varphi = 0[/tex]) such that [tex]\mathbf{F} = \nabla \varphi[/tex]. For part (c), you just need to compute [tex]\nabla \times \mathbf{F}[/tex] and [tex]\nabla \cdot \mathbf{F}[/tex] based on this assumption. For part (d), you need to find a suitable harmonic function [tex]\varphi[/tex].
 
  • #3
Why do I need to compute ∇xF and ∇·F? I'm sorry; I'm still confused about what this will tell me and how this relates to φ.
 
  • #4
Part (c) asks you: if [tex]\mathbf{F}[/tex] is the gradient of a harmonic function, what are [tex]\nabla\times\mathbf{F}[/tex] and [tex]\nabla\cdot\mathbf{F}[/tex]? This means your hypothesis is that there exists some harmonic function [tex]\varphi[/tex] such that [tex]\mathbf{F} = \nabla\varphi[/tex]. You don't know, or need to know, anything about [tex]\varphi[/tex] other than those two facts: that it is harmonic, and that its gradient is [tex]\mathbf{F}[/tex]. From these facts you can draw the conclusions you need, by rewriting [tex]\nabla\times\mathbf{F}[/tex] and [tex]\nabla\cdot\mathbf{F}[/tex] in terms of [tex]\varphi[/tex].
 

Related to Gradients of harmonic functions

1. What are gradients of harmonic functions?

Gradients of harmonic functions refer to the rate of change or slope of a harmonic function at a specific point. They are used to determine the direction and magnitude of the steepest ascent or descent of the function.

2. How are gradients of harmonic functions calculated?

Gradients of harmonic functions are calculated using the partial derivatives of the function with respect to each of its variables. The gradient vector is then formed by combining these partial derivatives.

3. What is the significance of gradients of harmonic functions?

Gradients of harmonic functions are significant because they can help us identify critical points, such as local maxima and minima, on a function. They are also used in optimization problems to find the most efficient path or direction.

4. Can gradients of harmonic functions be negative?

Yes, gradients of harmonic functions can be negative. A negative gradient indicates a decreasing rate of change in the function, while a positive gradient indicates an increasing rate of change.

5. How are gradients of harmonic functions used in the real world?

Gradients of harmonic functions have various applications in the real world, such as in physics, engineering, and economics. They are used to model and analyze various natural and man-made phenomena, such as heat flow, fluid dynamics, and financial markets.

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