Gradient of a Vector: Scalar or Vector?

In summary: A scalor.In summary, the gradient of a vector is a rank-2 cartesian tensor, which can be defined as the contraction of the del operator with the vector, or in component notation as the partial derivatives of the vector components. This is different from the gradient of a scalar, which is a vector. However, there are also other ways to define the gradient of a vector, such as the divergence or curl, which can give a scalar or vector result, respectively.
  • #1
hoomanya
90
0
Hi,
Just a simple, quick question:
Does the gradient of a vector give a scalor or a vector?
Thanks!
 
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  • #2
hi hoomanya! :smile:
hoomanya said:
Does the gradient of a vector give a scalor or a vector?

there's no https://www.physicsforums.com/library.php?do=view_item&itemid=11" of a vector

gradients are of scalars

for a scalar f, ∇f is the gradient of f

for a vector V, ∇V has no meaning (but ∇.V is the divergence, and ∇xV is the curl) :wink:
 
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  • #3
Thank you very much for your quick reply. :)
 
  • #4
You can, of course, have
[tex]\nabla\cdot \vec{\phi}(x, y, z)= \frac{\partial f}{\partial x}+ \frac{\partial g}{\partial y}+ \frac{\partial h}{\partial z}[/tex]
the "divergence" of the vector valued function, [itex]\vec{\phi}(x, y, z)[/itex], which is a scalar, or
[tex]\nabla\cdot \vec{\phi}= \left(\frac{\partial g}{\partial z}- \frac{\partial h}{\partial y}\right)\vec{i}+ \left(\frac{\partial f}{\partial z}- \frac{\partial h}{\partial x}\right)\vec{j}+ \left(\frac{\partial g}{\partial x}- \frac{\partial f}{\partial y}\right)\vec{i}[/tex]
the "curl" of the vector valued function, [itex]\vec{\phi}(x, y, z)[/itex], which is a vector.

Perhaps that is what you are thinking of. There are three kinds of vector "multiplication" and so three ways we can attach the "del" operator to a function.
 
  • #5
I'd say there's a perfectly good definition for the gradient of a vector.
it's a rank-2 cartesian tensor.

For the vector [tex]\vec{A} = A_x \hat{i} + A_y \hat{j} + A_z \hat{k}[/tex]

we have the beast [tex]\nabla \vec{A}
=\nabla A_x \hat{i} + \nabla A_y \hat{j} + \nabla A_z \hat{k}[/tex]

such that for any vector [itex] \vec{v}[/itex]
[tex]\vec{v} \cdot \nabla \vec{A}
= (\vec{v} \cdot \nabla A_x) \hat{i} + (\vec{v} \cdot \nabla A_y) \hat{j}
+ (\vec{v} \cdot \nabla A_z) \hat{k}
[/tex]

This is more clear in component notation
[tex]\vec{A} \rightarrow A^i[/tex]
then
[tex] \nabla \vec{A} \rightarrow (\nabla A)^i_j
= \frac{\partial A^i}{\partial x^j}. [/tex]

where the product with the vector [itex]\vec{v}[/itex] above is really
contraction on the second index.
[tex] \vec{v} \cdot \nabla \vec{A} \rightarrow
\sum_j \quad \left( v^j \frac{\partial A^i}{\partial x^j} \right) [/tex]
 

FAQ: Gradient of a Vector: Scalar or Vector?

Is the gradient of a vector a scalar or a vector?

The gradient of a vector is a vector. It is a mathematical operation that produces a vector output.

How is the gradient of a vector calculated?

The gradient of a vector is calculated by taking the partial derivatives of the vector's components with respect to each of the variables in the vector.

3. What is the significance of the gradient of a vector?

The gradient of a vector represents the direction and magnitude of the steepest increase of a scalar field at a given point. It is also used in various mathematical applications, such as optimization and vector calculus.

4. Can the gradient of a vector be zero?

Yes, the gradient of a vector can be zero when the vector is constant or when the vector has a constant slope in all directions.

5. Does the gradient of a vector have a direction?

Yes, the gradient of a vector has a direction. It is perpendicular to the level curves of the scalar field at a given point.

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