Understanding Nabla and its Derivatives in 3D Systems

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Homework Help Overview

The discussion revolves around the Nabla operator and its derivatives in three-dimensional systems, focusing on its significance and representation, particularly in relation to partial derivatives and their interpretations in multiple dimensions.

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the meaning of the Nabla operator and its role in vector calculus, questioning its representation and significance in higher dimensions. There are discussions about the relationship between partial derivatives and standard derivatives in one dimension, as well as the implications of these concepts in understanding gradients.

Discussion Status

The conversation includes differing viewpoints on the nature of partial derivatives and their relationship to the Nabla operator. Some participants provide clarifications about the gradient vector and its properties, while others seek further explanation on specific points, indicating an ongoing exploration of the topic.

Contextual Notes

Participants are examining foundational concepts in vector calculus, with an emphasis on the definitions and implications of the Nabla operator and partial derivatives in multi-dimensional contexts. There is a recognition of the complexity involved in these definitions and their applications.

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Could some one explain what does Nabla operator actually signify ? I understand that the various products with nabla are used to find curl,divergence,gradient in EM, but what does Nabla represent in itself ? A more basic question would be, what does del operator(partial derivative) represent , in a 3d system ?
 
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It's a generalization of the derivative operator to multiple dimensions. That's all.

In one dimension, say along the x-axis, the derivative operator looks like this:

[itex] \frac{d}<br /> {{dx}} = \frac{\partial }<br /> {{\partial x}} = \vec i \frac{\partial }<br /> {{\partial x}}[/itex]

Since there's only one dimension, the "normal" derivative and partial derivative are the same. Also, there's only way way to take a derivative in one dimension -- along that dimension. Thus, the [itex]\vec i[/tex] is implied.<br /> <br /> In multiple dimensions, say x, y and z, it looks like:<br /> <br /> [itex] \nabla = <br /> \vec i \frac{\partial }<br /> {{\partial x}} + \vec j \frac{\partial }<br /> {{\partial y}} + \vec k \frac{\partial }<br /> {{\partial z}}[/itex]<br /> <br /> Same thing, just with more dimensions.<br /> <br /> - Warren[/itex]
 
I would disagree there, chroot.
The one-dimensional analogue of the partial derivative at a point, is the derivative with respect to the elements of some particular sequence converging to that point.

Remember that existence of all partial derivatives does not guarantee differentiability at that point; some similar restriction ought to be provable for "sequential" derivatives in the one-dimensional case.
 
arildno said:
I would disagree there, chroot.
The one-dimensional analogue of the partial derivative at a point, is the derivative with respect to the elements of some particular sequence converging to that point.

So you're saying that del doesn't reduce to the standard one-dimensional derivative d/dx? Can you explain a bit more?

- Warren
 
What I was referring to was, what does a partial derivative represent (in multiple dimensions) like it represents slope in one dimension co-ordinate system ?
 
a gradient vector. the direction in which the function is changing most rapidly, and the magnitude is the amount its changing
 
FunkyDwarf said:
a gradient vector. the direction in which the function is changing most rapidly, and the magnitude is the amount its changing
If it acts on a scalar field.
 
chroot said:
So you're saying that del doesn't reduce to the standard one-dimensional derivative d/dx? Can you explain a bit more?

- Warren
Hmm..what I meant is that a partial derivative is the derivative with respect to some proper subset of arguments in the vicinity of the point.
For example along the x-axis (or some line parallell to that) in 2-D, or along the rationals in the 1-D case.
 
Last edited:
chroot said:
So you're saying that del doesn't reduce to the standard one-dimensional derivative d/dx? Can you explain a bit more?

- Warren

It's still a vector operator...so I would say that in one dimension:

[tex]\nabla = \hat{x}\frac{d}{dx}[/tex]


I'm sure Arildno's answer was better, but I didn't follow what he was saying.
 

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