Finding the Curl of a Vector Equation Using the Gradient Operator

  • Thread starter Thread starter Mashell
  • Start date Start date
Click For Summary

Homework Help Overview

The discussion revolves around evaluating the curl of a vector equation involving the gradient operator and a constant vector in three-dimensional space. The original poster expresses confusion regarding the concept of a constant vector and its implications in the context of vector calculus.

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the definition of a constant vector and its properties, particularly in relation to the gradient operator. Questions arise about the implications of crossing a constant vector with a position vector and the resulting values. There is also discussion about vector identities relevant to the curl operation.

Discussion Status

Participants are actively engaging with the concepts, questioning assumptions about constant vectors and their derivatives. Some guidance has been provided regarding vector identities, and there is a productive exchange of ideas about the implications of these identities in the context of the original problem.

Contextual Notes

There is an ongoing examination of the definitions and properties of vector operations, particularly in relation to the gradient operator and the nature of constant vectors. The discussion includes clarifications on the differences between various vector operations and their outcomes.

Mashell
Messages
4
Reaction score
0
If r is the position vector in three dimensions, a is a constant vector and [tex]\nabla[/tex] is the gradient operator, evaluate

[tex]\nabla[/tex] x (a x r).

I don't understand what a constant vector is, it can't be the same as a scalar function. I've searched for a while and couldn't find anything that made sense, so any help would be vey much appreciated.
 
Physics news on Phys.org
A constant vector is a vector whose length and direction do not depend on position.

For example; v=i+2j+687k qualifies as a constant vector. Its components are not functions of position.

In contrast, the vector v=3x2j is not a constant vector since its lentgh depends on position (specifically where you are along the x-axis)

Since constant vectors do not vary with position, their curl, divergence and gradient are all zero.
 
but if the constant vector is first "crossed" with the position vector... shouldn't it give me some values...
 
ohhhh but they cancel out... ahhh i see. Your right. Thank you gabbagabbahey :)
 
Careful...

[tex]\vec{\nabla}\times\vec{a}=\vec{\nabla}\cdot\vec{a}=\vec{\nabla}(\vec{a})=0[/tex]

But that doesn't necessarily mean

[tex]\vec{\nabla}\times(\vec{a}\times\vec{r})=0[/tex]

You should find the following vector identity useful:

[tex]\vec{\nabla}\times(\vec{A}\times\vec{B})=(\vec{B}\cdot\vec{\nabla})\vec{A}-(\vec{A}\cdot\vec{\nabla})\vec{B}+\vec{A}(\vec{\nabla}\cdot\vec{B})-\vec{B}(\vec{\nabla}\cdot\vec{A})[/tex]
 
hmmm okay, if A is a constant vector and div A is equal to 0 then the above formula reduces to

[tex]\vec{\nabla}\times(\vec{A}\times\vec{B})=(2(\vec{B}\ \cdot \vec{\nabla})\vec{A})[/tex]

right?

is

[tex](\vec{B}\ \cdot \vec{\nabla}) = (\vec{\nabla}\ \cdot\vec{B})[/tex]
 
Mashell said:
hmmm okay, if A is a constant vector and div A is equal to 0 then the above formula reduces to

[tex]\vec{\nabla}\times(\vec{A}\times\vec{B})=(2(\vec{B}\ \cdot \vec{\nabla})\vec{A})[/tex]

right?

is

[tex](\vec{B}\ \cdot \vec{\nabla}) = (\vec{\nabla}\ \cdot\vec{B})[/tex]

No,

[tex](\vec{B}\ \cdot \vec{\nabla}) \neq (\vec{\nabla}\ \cdot\vec{B})[/tex]

In Cartesian coordinates,

[tex](\vec{B}\ \cdot \vec{\nabla})= B_x\frac{\partial}{\partial x}+B_y\frac{\partial}{\partial y}+B_z\frac{\partial}{\partial z}[/tex]

which is a differential operator that operates on whatever vector is on the right of the operator.

Of course, any differential operator that operates on a constant vector will be taking some derivative of some constant and therefor gives a result of zero.

Therefor, [tex](\vec{r}\cdot \vec{\nabla})\vec{a}=0[/tex]

And

[tex]\vec{\nabla}\times(\vec{a}\times\vec{r})=-(\vec{a}\cdot \vec{\nabla})\vec{r}+\vec{a}(\vec{\nabla}\cdot\vec{r})[/tex]
 
You can then use the fact that [tex]\vec{r}=x\hat{x}+y\hat{y}+z\hat{z}[/tex] to simplify further.
 

Similar threads

  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
Replies
7
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 13 ·
Replies
13
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K