Proof of vector property in space

  • I
  • Thread starter chwala
  • Start date
  • Tags
    Proof
In summary, the conversation discussed the importance of time management and setting priorities in order to achieve personal and professional goals. The speakers also mentioned the benefits of creating a schedule and sticking to it, as well as the potential consequences of poor time management. They emphasized the need for balance and prioritizing tasks based on their level of urgency and importance. Ultimately, the conversation highlighted the crucial role that effective time management plays in achieving success.
  • #1
chwala
Gold Member
2,650
351
TL;DR Summary
See attached
1689350162836.png

My interest is on the associative property; is there anything wrong of showing and concluding proof by;

##c(\vec u⋅\vec v)=(c⋅\vec v)⋅\vec u.##

or are we restricted in the prose?
 
Last edited:
Physics news on Phys.org
  • #2
Your equality contains three different types of multiplications: scalar by scalar; scalar by vector and a vector by vector. I do not think that it makes sense to call this "associative property"
 
  • #3
wrobel said:
Your equality contains three different types of multiplications: scalar by scalar; scalar by vector and a vector by vector. I do not think that it makes sense to call this "associative property"
Did you understand my question? I am going through the pdf notes and my question is specifically on: the associative property.

##c(\vec u⋅\vec v)=(c⋅\vec u)⋅\vec v##

as indicated on my pdf notes...

Unless, you are of the opinion that the notes are not correct.

i am asking if the proof could be allowed to take this route

...

##c(\vec u⋅\vec v)=(cv_1, cv_2, cv_3)⋅(u_1,u_2, u_3)##

...

to end up with,

##c(\vec u⋅\vec v)=(c⋅\vec v)⋅\vec u##
 
Last edited:
  • #4
$$c(u,v)=(cu,v),\quad (u,v)=(v,u)\Longrightarrow c(u,v)=c(v,u)=(cv,u)=(u,cv)$$
 
  • #5
What is c a scalar or a vector?

On the LHS you use c as a scalar multiplied by the scalar inner product of U and V

But on the RHS, you've dotted c with the U vector.

Since there is no hat on c then it must be a scalar and the RHS operator usage is confusingly wrong.
 
  • Like
Likes Steve4Physics
  • #6
jedishrfu said:
What is c a scalar or a vector?

On the LHS you use c as a scalar multiplied by the scalar inner product of U and V

But on the RHS, you've dotted c with the U vector.

Since there is no hat on c then it must be a scalar and the RHS operator usage is confusingly wrong.
I put arrows on ##u## and ##v## to indicate that they are vectors...if that is not correct then you may guide me. I did not get it right on latex, sorry for that confusion and i ought to have clearly stated that ##c## is a scalar and ##u,v## are vectors... now can we focus on my question? Thanks...
 
  • #7
chwala said:
...

##(c\vec v_1, c\vec v_2, c\vec v_3)⋅(\vec u_1,\vec u_2,\vec u_3)##
what's this?
 
  • #8
Amended
wrobel said:
what's this?
Amended. The correct position is as follows:

i am asking if the proof could be allowed to take this route

...

##c(\vec u⋅\vec v)=(cv_1, cv_2, cv_3)⋅(u_1,u_2, u_3)##

...

to end up with,

##c(\vec u⋅\vec v)=(c⋅\vec v)⋅\vec u##
 
  • #9
Yes that's completely fine due to your proof above it of the commutative property.
 
  • Like
Likes chwala
  • #10
@chwala, for information, part of the confusion is that you have written expressions containing ##c⋅\vec u## and ##c⋅\vec v##. But these are wrong.

##c## is a scalar.
##⋅## in this context is the dot (inner) product of two vectors.
##\vec u## and ##\vec v## are vectors.

##c⋅\vec u## should be ##c\vec u##
##c⋅\vec v## should be ##c\vec v##

For example, in Post #8 you wrote "##c(\vec u⋅\vec v)=(c⋅\vec v)⋅\vec u##". This is wrong and should be written as ##c(\vec u⋅\vec v)=(c\vec v)⋅\vec u##.

Edit: @jedishrfu already pointed out (Post #5) this problem.
 
  • Like
  • Informative
Likes jedishrfu, Mark44 and chwala

1. What is a vector in space?

A vector in space is a mathematical quantity that has both magnitude and direction. It is represented by an arrow pointing in the direction of the vector, with the length of the arrow representing the magnitude of the vector.

2. What is the proof of vector property in space?

The proof of vector property in space is a mathematical demonstration that shows how vectors behave in three-dimensional space. It involves using mathematical operations such as addition, subtraction, and multiplication to show that vectors follow specific rules and properties.

3. What are the basic properties of vectors in space?

The basic properties of vectors in space include commutativity, associativity, and distributivity. Commutativity means that the order of vector addition does not change the result. Associativity means that the grouping of vectors in an addition or multiplication does not change the result. Distributivity means that multiplying a vector by a scalar and then adding it to another vector is the same as multiplying each vector by the scalar and then adding them together.

4. How do vectors behave in space?

Vectors behave in space according to the basic properties mentioned above. They can be added, subtracted, and multiplied by scalars, and the result will follow these properties. Vectors also have a direction and magnitude, which can be used to represent physical quantities such as force and velocity.

5. Why is understanding vector properties in space important?

Understanding vector properties in space is important because vectors are used in many fields of science, including physics, engineering, and mathematics. They are essential for describing and analyzing physical phenomena, and understanding their properties allows scientists to make accurate predictions and solve complex problems.

Similar threads

  • Linear and Abstract Algebra
Replies
3
Views
303
  • Linear and Abstract Algebra
Replies
7
Views
2K
  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
8
Views
1K
  • Linear and Abstract Algebra
Replies
5
Views
2K
  • Linear and Abstract Algebra
Replies
7
Views
253
  • Linear and Abstract Algebra
Replies
12
Views
2K
  • Linear and Abstract Algebra
Replies
2
Views
1K
  • Linear and Abstract Algebra
Replies
7
Views
1K
Replies
5
Views
1K
Back
Top