Understanding F = ∇·F: The Relationship Between Scalar and Vector Fields

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In summary, the conversation revolves around the concept of a scalar field being an exact form of a vector field. However, this is not possible because an exact form must be the exterior derivative of a lower degree form, which does not exist for a 0-form. The conversation also discusses analogies between incompressible, solenoidal, and exact forms, but it is important to note that these are just analogies and cannot be used interchangeably with the mathematical definitions. The conversation also mentions identities for Cartan derivatives of k-forms in three-dimensional space, but these are specific cases and do not change the fundamental definitions of closed and exact forms.
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Jhenrique
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A scalar field can be the exact form of a vector field (potential form)? It's make sense?
 
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Nope, doesn't make sense. A divergence is not an exterior derivative. A scalar field is a 0-form. It can't be an exact form because an exact n-form must be the exterior derivative of of a n-1 form. There are no -1 forms, so a 0-form cannot be considered exact.
 
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  • #3
Matterwave said:
Nope, doesn't make sense. A divergence is not an exterior derivative. A scalar field is a 0-form. It can't be an exact form because an exact n-form must be the exterior derivative of of a n-1 form. There are no -1 forms, so a 0-form cannot be considered exact.

You have a lot of knowledge in several areas of science, impressive!
 
  • #4
But the operation ##\vec{\nabla} \cdot \vec{F} = F## exist! But still so ##\vec{F}## isn't a potential form and ##F## isn't an exact form?
 
  • #5
You can't call it that. Those terms you used have very specific meanings. You call ##\vec{F}## the vector field and ##F## its divergence.
 
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Jhenrique said:
I'm speaking this way cause I have this ideia in my mind: http://en.wikipedia.org/wiki/Exact_form#Vector_field_analogies

The analogy this article is talking about is if ##\vec{\nabla}\cdot\vec{F}=0## we call ##\vec{F}## incompressible analogous to closed. If ##\vec{F}=\vec{\nabla}\times\vec{A}## then we call ##\vec{F}## solenoidal analogous to exact. The final analogy is that exact implies closed ##\vec{\nabla}\cdot(\vec{\nabla}\times\vec{A})=0##.

But these are analogies. You can NOT call ##\vec{F}## a (closed or exact) form. A form has a specific mathematical definition.

Give you an example. Say I have a bicycle and a car. If I put a motor on my bicycle, it turns into a motorized vehicle which is somewhat analogous to a car. But I DON'T call my motorized bicycle a car. I call it a motorized bicycle, or a motorcycle. In the same way F above is analogous to a closed or exact form but I CANNOT call F a closed or exact form. I call it an incompressible or solenoidal vector field.
 
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Maybe what OP was asking for is the following identities for the Cartan derivatives ##d## of ##k##-forms in ##\mathbb R ^3## with canonical metric:
$$0) \, d \phi = (\nabla \phi)^T \cdot d \bar x$$
$$1) \, d A = (\nabla \times \bar A)^T \cdot \star d \bar x
\quad, A:= \bar A^T \cdot d \bar x$$
$$2) \, d B = (\nabla \cdot \bar B) \star 1 \quad, B:= \bar B^T \cdot \star d \bar x $$
Here ##{}^T## is the transpose and ##\star## the Hodge-operator.
 
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FAQ: Understanding F = ∇·F: The Relationship Between Scalar and Vector Fields

1. What is the meaning of F = ∇·F?

F = ∇·F represents the relationship between a scalar field and a vector field, where the scalar field is given by F and the vector field is given by ∇·F. This equation is also known as the vector Laplacian operator.

2. How do scalar and vector fields differ?

A scalar field is a mathematical function that assigns a scalar value to every point in space. A vector field, on the other hand, is a mathematical function that assigns a vector to every point in space. Scalar fields have only magnitude, while vector fields have both magnitude and direction.

3. What is the significance of the gradient in F = ∇·F?

The gradient (∇) in F = ∇·F represents the rate of change of the scalar field F. It is a vector operator that points in the direction of the steepest increase of the scalar field at a given point.

4. How is F = ∇·F used in physics and engineering?

F = ∇·F is used in various physical and engineering applications, such as fluid dynamics, electromagnetism, and heat transfer. It helps to understand the behavior of scalar and vector fields, and their interactions with each other.

5. Can you provide an example of F = ∇·F in real life?

One example of F = ∇·F in real life is the flow of water in a river. The scalar field represents the water level at different points along the river, while the vector field represents the direction and speed of the water flow. By understanding the relationship between these two fields, we can predict the movement of water and make informed decisions about flood control and navigation.

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