Does Vector Calculus Allow Operators to Function Like Vectors?

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Discussion Overview

The discussion revolves around the behavior of operators in vector calculus, particularly whether operators can function similarly to vectors. Participants explore the implications of various vector identities and the properties of derivatives, focusing on the application of these concepts in mathematical expressions and identities.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant notes an analogy between vector operations and operator behavior, questioning if operators generally behave like vectors in vector calculus.
  • Another participant highlights that derivatives conventionally act to the right and provides examples of vector identities that do not hold when the order is reversed.
  • A participant raises a question about how certain properties apply to the proof of the identity involving the curl of a gradient.
  • Discussion includes the assertion that the curl of a gradient is zero, suggesting that the operator del does not yield useful results when crossed with itself.
  • There is mention of a partial derivative that behaves differently, allowing for certain manipulations that do not apply to standard derivatives.

Areas of Agreement / Disagreement

Participants express varying views on the behavior of operators and their relationship to vector calculus identities. No consensus is reached on the applicability of certain rules or the implications of the discussed identities.

Contextual Notes

Participants reference specific mathematical identities and properties, but there are limitations regarding the assumptions made about the operators and the context in which these identities hold. The discussion does not resolve the nuances of operator behavior in all cases.

henpen
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Reading the Feynman Lectures,

[tex]\nabla \times (\nabla T)=(\nabla \times \nabla) T[/tex], is achieved by analogy to the analogous case for [itex]\mathbf{A} \times (\mathbf{A} T)=(\mathbf{A} \times \mathbf{A}) T[/itex],where T is a scalar field in all cases.

While this is obvious if [itex]\nabla[/itex] were to be replaced by a vector, I'm a complete novice when it comes to operators- is it a general rule in vector calculus that operators behave pretty much like vectors (apart from needing 'feeding', of course)?
 
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So aside from some nit picky stuff about continuity, convergence, and connected spaces the main issue is these derivatives by convention act to the right. A vector identity with have an analogous vector calculus identity when it does not require reversing order.

$$(\vec{a}\cdot \vec{\nabla})\vec{b}\ne \vec{b}(\vec{\nabla}\cdot \vec{a})$$

It is possible to define a new bidirectional operator to work these things out. Another one that surprises some people is

$$\vec{a}\cdot (\vec{\nabla}\times \vec{a})\ne \vec{\nabla}\cdot (\vec{a}\times \vec{a})=0$$

but

$$\vec{a}\cdot (\vec{b}\times \vec{a})= \vec{b}\cdot (\vec{a}\times \vec{a})=0$$
 
lurflurf, thanks for that. Sorry for not seeing it yet, but how do these properties apply in proving [itex](\nabla \times \nabla) \mathbf{F}= \nabla \times (\nabla \mathbf{F})[/itex], though?
 
Since it does not require reversing the direction the same rule apply as in

$$\vec{a}\times (\vec{a}T)=(\vec{a}\times \vec{a})T$$

Also curl of gradient is zero so del cross del is not a useful operator.

So again given a vector rule the rule with del will hold as long as nothing changes which side of del it is on. There is something about that in The Feynman Lectures. There is a partial del

$$\vec{\nabla}_b (\vec{a}\cdot\vec{b})=\vec{a}\times(\vec{\nabla} \times \vec{b} )+(\vec{a}\cdot \vec{\nabla})\vec{b}$$

a can change sides because this del ignores it while the usual one does not.
 

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