Does Vector Calculus Allow Operators to Function Like Vectors?

In summary, the author mentions that operators in vector calculus behave similarly to vectors, with the exception of the partial del operator which can change its side.
  • #1
henpen
50
0
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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  • #2
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

$$\vec{a}\cdot (\vec{b}\times \vec{a})= \vec{b}\cdot (\vec{a}\times \vec{a})=0$$
 
  • #3
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?
 
  • #4
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.
 

Related to Does Vector Calculus Allow Operators to Function Like Vectors?

What is vector calculus?

Vector calculus is a branch of mathematics that deals with the properties and behavior of vector fields. It involves the study of vector functions, differentiation and integration of vector fields, and the use of mathematical operations such as gradient, curl, and divergence.

How is vector calculus different from regular calculus?

Vector calculus deals with quantities that have both magnitude and direction, while regular calculus only deals with quantities that have magnitude. Vector calculus also involves the use of vector operations, such as dot and cross products, which are not used in regular calculus.

What are some real world applications of vector calculus?

Vector calculus is used in many fields, including physics, engineering, and computer graphics. It is used to model fluid flow, electromagnetism, and motion in three-dimensional space. It is also used in computer graphics to calculate lighting and shading effects.

What are the basic operations in vector calculus?

The basic operations in vector calculus include differentiation, integration, and vector operations such as dot and cross products. Other operations include gradient, divergence, and curl, which are used to describe the behavior of vector fields.

Is vector calculus difficult to learn?

Like any branch of mathematics, vector calculus can be challenging to learn. It requires a strong understanding of calculus and linear algebra. However, with practice and dedication, it can be mastered and applied to various real-world problems.

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