Help with vector spaces axioms

In summary, the 2x2 matrix [a 12;12 b] does not form a vector space because it fails to hold the axioms of closure under addition, existence of a zero vector, existence of an additive inverse, and closure under scalar multiplication.
  • #1
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Homework Statement


for the 2x2 matrix [a 12;12 b] is it a vector space

Homework Equations


1. If u and v are objects in V, then u+v is in V
2. u+v = v + u
3. u+(v+w) = (u+v)+w
4. There is an object 0 in V, called a zero vector for V, such that 0+u = u+0 = u for all u in V
5. For each u in V, there is an object -u in V, called a negative of u, such that u+(-u) = (-u)+u = 0
6. If k is any scalar and u is any object in V, then ku is in V
7. k(u+v) = ku+kv
8. (k+m)u = ku+mu
9. k(mu) = (km)(u)
10. 1u = u

The Attempt at a Solution


axioms 1,4,5,6 fail to hold.

axiom 1:
for any vectors u = [u1,12; 12, u2], v = [v1,12 ; 12 v2]in the space, u + v must also be in the space
this is obviously false, since
u + v = [u1+v1,12 + 12; 12+12, u2 + v2]
= [u1+v1,24; 24, u2 + v2]
which is not in the space

axiom 4:
let u = [u1,12; 12, u2], we need to find a 0 vector such that
u + 0 = 0 + u = u
but 0 must have the form [z1,12; 12, z2] to be in the space
and so u + 0 = [u1,12; 12, u2] + [z1,12; 12, z2]
= [u1+z1,12+12 ; 12+12, u2+z2]
= [u1+z1, 24 ; 24, u2+z2]
which is not equal to vector u, regardless of z1 and z2 values.

axiom 5:
can't have an additive inverse, if there's no 0 vector

axiom 6:
let u = [u1,12; 12, u2]
according to this axiom, for any scalar k, k*u is also in the space
but this is false for any k =/= 1:
k*u = k*[u1,12; 12, u2]
=[k*u1,k*12; k*12, k*u2]
which is not in space unless k = 1

however I am not sure if I did this correctly and need confirmation.
 
Last edited:
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  • #2
You did them all correctly. Note that you only need to find one property that doesn't work to conclude that V isn't a vector space. So you could have just done the first one and be done with it.
 
  • #3
thanks for the confirmation :)
 

What are vector spaces axioms?

Vector space axioms are a set of rules that define the properties and operations of a vector space. They are used to understand and manipulate vectors in a mathematical context.

Why is it important to understand vector spaces axioms?

Understanding vector space axioms is crucial for studying and solving problems in linear algebra, physics, and engineering. It allows for the manipulation and analysis of vectors in a systematic and consistent manner.

How many vector space axioms are there?

There are 8 vector space axioms, which include the existence of a zero vector, closure under addition and scalar multiplication, associativity and commutativity of addition, and distributivity of scalar multiplication over addition.

Can vector space axioms be violated?

No, vector space axioms cannot be violated. They are fundamental rules that must hold true for a set of vectors to be considered a vector space. If one or more of the axioms are not satisfied, then the set is not a vector space.

What are some real-life applications of vector space axioms?

Vector space axioms have various real-life applications, such as in computer graphics, where they are used to manipulate and transform 2D and 3D images. They are also used in machine learning and data analysis to represent and analyze data in high-dimensional spaces.

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