Integrating Vector Derivatives

In summary: Note that this requires the first partial derivatives of \vec{F} to be continuous, not just the second partials.) So in this case, since we know that curl F = G, we can write F = \nabla{f} + \vec{F_o}, where \vec{F_o} is a particular solution to curl F = G. So every solution to curl F = G must be of the form F = \nabla{f} + \vec{F_o}.
  • #1
kingwinner
1,270
0
Q: Given that G(x,y,z)=(6xz+x3, 3x2y+y2, 4x+2yz-3z2). Find F such that curl F = G.

Solution:
...
A particular solution is
Fo=(-3x2yz-y2z, 2x2-3xz3-x3z)

And then my textbook says that the general solution is F=Fo + grad f where f is an arbitrary C1 function.
===============================

Now my questions:

If f is C1 function, why must F=Fo+gradf be a solution to curl F=G?
I believe that curl(grad f)=0 for f a C2 (not C1) function. Why does C1 work as well?

Secondly, why can we be sure that F=Fo+gradf is the general solution to curl F=G? (i.e. why is every solution contained in it?)


I would really appreciate if someone could explain.
 
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  • #2
Just to give some background, here we're trying to find the "vector potential function"

Can somebody help?
 
  • #3
kingwinner said:
If f is C1 function, why must F=Fo+gradf be a solution to curl F=G?
I believe that curl(grad f)=0 for f a C2 (not C1) function. Why does C1 work as well?

I think you've actually found an error here. You do in fact need the second partials to be continuous, as that's the only way you are guaranteed to be able to switch the order of second mixed partials. Check it out with your prof to make sure we're not missing something subtle here.

Secondly, why can we be sure that F=Fo+gradf is the general solution to curl F=G? (i.e. why is every solution contained in it?)

It's because you haven't specified the f. It's just like saying that the general antiderivative of [itex]x[/itex] is [itex]\frac{1}{2}x^2+C[/itex]. Since you haven't committed to a particular C, the family of functions is still as general as possible.
 
  • #4
Tom Mattson said:
I think you've actually found an error here. You do in fact need the second partials to be continuous, as that's the only way you are guaranteed to be able to switch the order of second mixed partials. Check it out with your prof to make sure we're not missing something subtle here.
Yes, I think it has to be C2.
But it is written in my textbook as C1, it must be a typo or something...

Just one more question:
We can add an arbitrary function f of class C2, is it because that
curl(Fo+gradf) = curl(Fo) + curl(gradf) = curl(Fo) + 0 = curl(Fo) ?
I am not too sure about the first equal sign. In general, is it true that curl(H1+H2) = curl(H1) + curl(H2)


It's because you haven't specified the f. It's just like saying that the general antiderivative of [itex]x[/itex] is [itex]\frac{1}{2}x^2+C[/itex]. Since you haven't committed to a particular C, the family of functions is still as general as possible.
For f a C2 function,
I can see that every vector field of the form F=Fo+gradf is a solution to curl F=G.
But is every solution to curl F=G of the form F=Fo+gradf? Can there exist a solution not of this form? How do you know?


Thanks!
 
  • #5
kingwinner said:
Just one more question:
We can add an arbitrary function f of class C2, is it because that
curl(Fo+gradf) = curl(Fo) + curl(gradf) = curl(Fo) + 0 = curl(Fo) ?
I am not too sure about the first equal sign. In general, is it true that curl(H1+H2) = curl(H1) + curl(H2)

Yes, certainly. The curl is just a formal linear combination of partial derivatives (with unit vector coefficients). Since differentiation is itself linear, the whole shebang is linear.

For f a C2 function,
I can see that every vector field of the form F=Fo+gradf is a solution to curl F=G.
But is every solution to curl F=G of the form F=Fo+gradf? Can there exist a solution not of this form? How do you know?

There's a basic theorem from vector calculus (can't recall the name) that states that the curl of a vector field [itex]\vec{F}[/itex] vanishes if and only if [itex]\vec{F}=\nabla{f}[/itex] for some scalar function [itex]f[/itex].
 

1. What are vector derivatives?

Vector derivatives are mathematical operators used to describe the rate of change of a vector quantity with respect to another variable. They are used to find the direction and magnitude of change in a vector field.

2. How are vector derivatives integrated?

Vector derivatives are integrated using the same techniques as single-variable derivatives, such as the chain rule and product rule. However, it is important to consider both the magnitude and direction of the vector when integrating.

3. What is the difference between scalar and vector derivatives?

Scalar derivatives only consider the magnitude of a quantity, while vector derivatives also take into account the direction of change. This means that vector derivatives have both a magnitude and direction, while scalar derivatives only have a single numerical value.

4. What are some real-world applications of integrating vector derivatives?

Integrating vector derivatives is used in many fields, such as physics, engineering, and economics. It can be used to model and predict the behavior of complex systems, such as fluid flow, electric fields, and stock market trends.

5. What are some common techniques for solving vector derivative problems?

Some common techniques for solving vector derivative problems include using vector identities, integrating by parts, and utilizing vector calculus theorems such as the divergence theorem and Stokes' theorem. It is also important to have a strong understanding of basic vector operations and properties.

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