Is Scalar Multiplication Consistent for Different Scalars and Vectors in V?

Click For Summary

Homework Help Overview

The discussion revolves around the properties of scalar multiplication in a vector space, specifically examining whether the defined scalar multiplication holds consistently for different scalars and vectors. The original poster expresses confusion regarding axioms related to scalar multiplication and vector addition.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to understand if the scalar multiplication defined as ku = (0, ku2) applies similarly for different scalars and vectors. They provide examples and question the validity of their reasoning regarding the axioms of vector spaces.
  • Some participants clarify that the definitions of scalar multiplication must hold for any vectors in the vector space and emphasize the importance of the distributive property in scalar multiplication.

Discussion Status

Participants are actively engaging with the original poster's examples and providing clarifications about the axioms. There is a recognition of the need to carefully apply the definitions of scalar multiplication and vector addition. While some confusion remains, guidance has been offered to help clarify the original poster's understanding.

Contextual Notes

The original poster references axioms 7, 8, and 9, indicating a specific framework for their questions. There is an emphasis on the generality of the definitions and the need for consistency across different scalars and vectors.

ryan8642
Messages
24
Reaction score
0
u and v are contained in V

Lets say the scalar multiplication is defined as:

ex.

ku=k^2 u or ku = (0,ku2) u=(u1,u2)

does this mean that this is also the same for different scalar m?

mu=m^2 u or mu = (0,mu2) u=(u1,u2)

and does this mean the same for any vector v

kv=k^2 v or kv = (0,kv2) v=(v1,v2)

Is this correct?

Axioms 7,8,9 contain the 2 different scalars as well as vectors. it really confuses me.

Can someone please put me on the right track :s


_____________

so u guys know and I am not confusing you guys i showed 2 examples there to help show my problem.

Ex 1.

Lets say the scalar multiplication is defined as:

ku = (0,ku2) u=(u1,u2)

does this then mean that this is also the same for different scalar m?

mu = (0,mu2) u=(u1,u2)

and also this for any vector v

kv = (0,kv2) v=(v1,v2)

_____________________
addition u+v=(u1+v1, u2+v2)

ex.. axiom 8 (to help explain my problem)

using what is described above.

(k+m)u = ku + mu
(k+m)(u1,u2)=k(u1,u2) + m(u1,u2)
(0,(k+m)u2)=(0,ku2) + (0,mu2)
(0,(k+m)u2)=(0,ku2+mu2)
(0,(k+m)u2)=(0,(k+m)u2)

LS=RS therefore axiom 8 holds for the set.

now using just ku=(0,ku2)

(k+m)u = ku + mu
(k+m)(u1,u2) = k(u1,u2) + m(u1,u2)
((k+m)u1, (k+m)u2) = (0,ku2) + (mu1,mu2)
((k+m)u1, (k+m)u2) = (0+mu1, ku2+mu2)
(ku1+mu1,ku2+mu2) = (mu1, ku2 +mu2)

LS ≠ RS so axiom 8 doesn't hold for the set.

hopefully that helps explain my problem...

which way is correct?? please help!
 
Physics news on Phys.org


Axioms 7,8,9 contain the 2 different scalars as well as vectors. it really confuses me.
Not clear why this should confuse you ... the definitions are general and have to work for any vector in the vector space... so they also work for any pair of vectors each a member of the vector space.
Can someone please put me on the right track :s
Helps if you state the axiom in question - not everyone numbers them the same. eg. http://en.wikipedia.org/wiki/Vector_space#Definition

Lets start by asserting that ##\vec{u}=(u_1,u_2)## and ##\vec{v}=(v_1,v_2)## are both members of the same vector space - so I don't have to keep writing it out. Let's look at your examples:

Lets say the scalar multiplication is defined as:

##k\vec{u} = (0,ku_2)##
OK - and this should work for any other scalar ##m \neq k## and for any other vector ##\vec{v} \neq \vec{u}## ... the definition has to work for any vectors in the space.

using what is described above.

##(k+m)\vec{u} = k\vec{u} + m\vec{u}##
##(k+m)(u_1,u_2)=k(u_1,u_2) + m(u_1,u_2)##
##(0,(k+m)u_2)=(0,ku_2) + (0,mu_2)##
##(0,(k+m)u_2)=(0,ku2+mu_2)##
##(0,(k+m)u_2)=(0,(k+m)u_2)##

LS=RS therefore axiom 8 holds for the set.

You are using the distributive property for scalar multiplication.
The axiom says that ##(a+b)\vec{v}=a\vec{v}+b\vec{v}##

We need to be careful...
##LHS = (a+b)\vec{v}= (0, (a+b)v_2## from the definition.
##RHS = a\vec{v}+b\vec{v} = (0,av_2)+(0,bv_2) = (0, (a+b)v_2) = (a+b)\vec{v}##
Then we can observe that RHS = LHS and so the distributive law holds according to the rule for adding vectors. Explicitly separating the LHS and RHS like this helps to keep confusion at bay.

Notice that it does not matter what we call the scalars - you used k and m, I used a and b: it makes no difference to the math.
After all - the number "2" is a scalar - how does the vector know if that scalar is a k or an m or an a or a b or a whatever?

now using just ##k\vec{u}=(0,ku_2)##

##(k+m)\vec{u} = k\vec{u} + m\vec{u}##
##(k+m)(u_1,u_2) = k(u_1,u_2) + m(u_1,u_2)##
##((k+m)u_1, (k+m)u_2) = (0,ku_2) + (mu_1,mu_2)##
Nonsense! You did not follow the rule for scalar multiplication ... of course you got a different result!

Just as the rule works for k and m so it also works for any other scalar, and (k+m) is a scalar and so is m.
The letters are just labels and don't have any intrinsic meaning to themselves. You could as easily use a and b and (a+b) or fruit and vegetable names or geometric shapes.
If we have a scalar called "bob" then I'd write ##(bob)\vec{u}=(0, (bob)u_2)##
 
Last edited:


okk,

Thanks for the detailed explanation!
That clarifies what i thought
 


No worries: it is easy to get tied up in knots about this stuff.
 

Similar threads

  • · Replies 17 ·
Replies
17
Views
5K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
5K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 10 ·
Replies
10
Views
5K