Vector calculus and order of operations

In summary, the order of operations for vectors is the same as for scalars. In particular, r- r' is in parentheses. Of course, you do that first. That is what parentheses mean. Finally, \nabla f, written in that way, is a scalar operator. You are essentially "multiplying" the scalar f by the vector \nabla. Since it is to be applied to a scalar, not a vector you must take the dot product first to get a scalar.
  • #1
PhysicalProof
10
0
2cwwkjr.png


I understand how to do (a). However, I'm having trouble with the rest, here. I've never properly learned the order of operation for vectors like this.

For example, for (b) does one dot (r - r') with itself BEFORE using the del operator?

Thanks guys, help appreciated. Even if you point me to a good source for understanding this stuff I will be grateful.
 
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  • #2
Yes, (r-r').(r-r') then find the gradient. That's really the only way to interpret it.
 
  • #3
PhysicalProof said:
2cwwkjr.png


I understand how to do (a). However, I'm having trouble with the rest, here. I've never properly learned the order of operation for vectors like this.

For example, for (b) does one dot (r - r') with itself BEFORE using the del operator?
The order of operations for vectors is the same as for scalars. In particular, r- r' is in parentheses. Of course, you do that first. That is what parentheses mean. Finally, \(\displaystyle \nabla f\), written in that way, is a scalar operator. You are essentially "multiplying" the scalar f by the vector [itex]\nabla[/itex]. Since it is to be applied to a scalar, not a vector you must take the dot product first to get a scalar.

For (c), note the "dot" between [itex]\nabla[/itex] and the vector. That is a dot product which has to be done between vectors. Now you are taking the dot product of the two "vectors" \(\displaystyle \nabla\) and r- r'.

You may not have learned it yet but you should shortly learn [itex]\nabla\times \vec{f}(x,y,z)[/itex], the "cross product" of [itex]\nabla[/itex] and the vector function [itex]\vec{f}(x,y,z)[/itex].

Thanks guys, help appreciated. Even if you point me to a good source for understanding this stuff I will be grateful.
 
Last edited by a moderator:
  • #4
PhysicalProof said:
2cwwkjr.png


I understand how to do (a). However, I'm having trouble with the rest, here. I've never properly learned the order of operation for vectors like this.

For example, for (b) does one dot (r-r') with itself BEFORE using the del operator?

Thanks guys, help appreciated. Even if you point me to a good source for understanding this stuff I will be grateful.


I am no expert, I'll try!

I don't know b) the way you wrote it. Do you mean [itex]\nabla |\vec{r}-\vec {r}'|^2[/itex]? If so then it is [itex]\nabla [ (\vec{r}-\vec {r}') \cdot (\vec{r}-\vec {r'}) ] [/itex].

c) Is just [tex](\frac{\partial}{\partial x}\widehat{x} + \frac{\partial}{\partial y}\widehat{y}) \cdot (\vec{r}-\vec {r}') [/tex]

d) Remember [itex] \vec{a} \cdot \vec {b} =\vec{b} \cdot \vec {a} [/itex]. so it is just [itex] (\nabla \cdot \widehat{r} ) \widehat{r} [/itex]
 
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  • #5
Thanks for your assistance everyone! I'm trying to work through them now. Are you sure about C youngman? Aren't there three components in each of those r vectors that we need to use?
 
  • #6
PhysicalProof said:
Thanks for your assistance everyone! I'm trying to work through them now. Are you sure about C youngman? Aren't there three components in each of those r vectors that we need to use?

I am sorry, I just use R2. Yes R3(3 dimemsion in space ) is exactly the same. Just add the z component or in your case use x1, x2 and x3.

[tex] \nabla \cdot (\vec{r}-\vec{r}') = (\frac{\partial}{\partial x_1} \hat{x}_1 + \frac{\partial}{\partial x_2} \hat{x}_2 + \frac{\partial}{\partial x_3} \hat{x}_3) \cdot (\vec{r}-\vec{r}')[/tex]

I am just assuming we are using rectangular coordinates. It would be a little different with cylindrical and spherical coordinates. I thought your question concentrate on the [itex]\nabla[/itex] operator so I really did not get into the coordinates.
 

Related to Vector calculus and order of operations

1. What is vector calculus?

Vector calculus is a branch of mathematics that deals with the study of vectors and their properties, including vector fields, vector functions, and vector operations. It is used to model and analyze physical phenomena involving quantities that have both magnitude and direction, such as velocity, force, and electric fields.

2. What are the basic operations in vector calculus?

The basic operations in vector calculus include addition, subtraction, scalar multiplication, and dot and cross products. Addition and subtraction are performed by adding or subtracting corresponding components of two or more vectors. Scalar multiplication involves multiplying a vector by a scalar, which changes the magnitude but not the direction of the vector. Dot and cross products are used to find the angle between two vectors and to determine the direction of a vector perpendicular to two other vectors, respectively.

3. What is the order of operations in vector calculus?

The order of operations in vector calculus follows the same rules as in regular algebra: parentheses, exponents, multiplication and division, and addition and subtraction. However, when dealing with vector operations, it is important to pay attention to the order in which the operations are performed, as they can affect the final result.

4. How is vector calculus used in real life?

Vector calculus has many applications in real life, particularly in the fields of physics, engineering, and computer graphics. It is used to study and analyze physical phenomena like motion, fluid dynamics, and electromagnetic fields. It is also used to design and optimize structures and systems, such as bridges, airplanes, and electrical circuits. In computer graphics, vector calculus is used to create 3D models and animations, as well as to simulate realistic physical interactions.

5. What are some common misconceptions about vector calculus?

One common misconception about vector calculus is that it is only used in advanced mathematics and has no practical applications. In reality, vector calculus is widely used in many fields and has numerous real-life applications. Another misconception is that it is only relevant in 3D space, when in fact it can be applied in any number of dimensions. Additionally, some people may think that vector calculus is only used to solve complex problems, when in fact it can also be used for simpler calculations and visualizations.

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