Gradient transforms under axes rotation

In summary, the gradient of the function f is a vector that transforms as a rotation of axes. The chain rule is used to find the derivative of the function with respect to the variables y and z. The gradient is not in the form of A, but is closer to switching between the axes.
  • #1
Karol
1,380
22

Homework Statement


[itex]f[/itex] is a function of two variables: y, z. I want to show that the gradient:

[tex]\nabla f=\frac{\partial f}{\partial y}\hat y + \frac{\partial f}{\partial z}\hat z[/tex]
Transforms as a vector under rotation of axes.

Homework Equations


The rotation of axes:
[tex]A \left\{\begin{array}{l}\bar {y} = y \cdot \cos \phi + z \cdot \sin \phi \\ \bar {z} = -y \cdot \sin + z \cdot \cos \end{array}\right.[/tex]

The Attempt at a Solution


I use the chain rule:
[tex]\frac{\partial f}{\partial \bar {y}}=\frac{\partial f}{\partial y}\frac{\partial y}{\partial \bar {y}}+\frac{\partial f}{\partial z}\frac{\partial z}{\partial \bar {y}}[/tex]
And the similar for [itex]\frac{\partial f}{\partial \bar {z}}[/itex]. In order to find [itex]\frac{\partial y}{\partial \bar {y}}[/itex] and [itex]\frac{\partial z}{\partial \bar {z}}[/itex] i solve A for y and z and get:

[tex]\left\{\begin{matrix} y= \bar {y}\cdot \cos \phi - \bar {z}\cdot \sin \phi \\ z= \bar {y}\cdot \sin \phi +\bar {z}\cdot \cos \phi\end{matrix}\right.[/tex]

Now i get:
[tex]\left\{\begin{array}{l}\frac{\partial f}{\partial \bar {y}}=\frac{\partial f}{\partial y}(-\sin \phi)+\frac{\partial f}{\partial z}\cos \phi \\ \frac{\partial f}{\partial \bar {z}}=\frac{\partial f}{\partial y}(-\cos \phi)+\frac{\partial f}{\partial z}(-\sin \phi)\end{array}\right.[/tex]
Not as i expected, in the form of A.
It is closer to switching between the axes, but that's all i understand from this result.
 
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  • #2
How did you get ##\partial y/\partial \bar{y} = -\sin \phi##? That's what your final results imply. Similar questions for the other derivatives.
 
  • #3
For [itex]\partial y/\partial \bar{y}[/itex] I differentiated the formula i derived earlier:
[tex]y= \bar {y}\cdot \cos \phi - \bar {z}\cdot \sin \phi[/tex]
 
  • #4
Which doesn't give you ##\partial y/\partial \bar{y} = -\sin \phi##. That's why I'm asking where did you get that from.
 
  • #5
You mean i have a mistake in differentiating [itex]y= \bar {y}\cdot \cos \phi - \bar {z}\cdot \sin \phi[/itex]? how come?
The derivative of [itex]\cos[/itex] is [itex]-\sin[/itex], and i ignore the second member [itex] \bar {z}\cdot \sin \phi[/itex] because it doesn't contain [itex]\bar {y}[/itex].
Or you ask how did i get: [itex]y= \bar {y}\cdot \cos \phi - \bar {z}\cdot \sin \phi[/itex]?
 
  • #6
[itex]-sin(\phi)[/itex] is the derivative of [itex]cos(\phi)[/itex] with respect to [itex]\phi[/itex]. You are not differentiating with respect to [itex]\phi[/itex]. [itex]\phi[/itex] is a constant.
 
  • #7
Thanks!
 

1. What is a gradient transform under axes rotation?

A gradient transform under axes rotation refers to the mathematical process of rotating the coordinate axes of a gradient vector field. This allows for a change in the orientation of the gradient vectors, while keeping their magnitude and direction unchanged.

2. Why is it important to rotate the axes in a gradient transform?

Rotating the axes in a gradient transform allows for a more intuitive understanding of the gradient vector field. It also allows for easier visualization and analysis of the field, as it can be aligned with the direction of the greatest change in a given direction.

3. How is a gradient transform under axes rotation performed?

A gradient transform under axes rotation is performed using matrix multiplication. The rotation matrix, which is dependent on the desired angle of rotation, is multiplied with the gradient vector field to obtain the new rotated field.

4. What are some applications of gradient transforms under axes rotation?

Gradient transforms under axes rotation have various applications in mathematics and physics. They can be used to analyze the behavior of gradient fields in different orientations, and in modeling physical phenomena such as fluid flow and heat transfer.

5. Are there any limitations to gradient transforms under axes rotation?

One limitation of gradient transforms under axes rotation is that they only work for two-dimensional vector fields. They also do not change the shape or size of the gradient field, only its orientation. Additionally, they can only be applied to continuous and differentiable functions.

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