Does V Qualify as a Vector Space?

In summary: V is not a vector space In summary, the set V of ordered pairs (x, y) of real numbers with vector addition (x, y) + (x', y') = (y + y', x + x') and scalar multiplication c(x, y) = (cx, cy) is not a vector space. This is because it fails to hold the property of associativity of vector addition, as shown by the counterexample (a + u + y, b + v + x) ≠ (x + u + b, y + v + a). Additionally, there is no universal zero vector (p, q) that satisfies the property of v + 0 = v for all v, as shown by
  • #1
-Dragoon-
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7

Homework Statement


Let V be the set of ordered pairs (x, y) of real numbers with the operations of vector addition and scalar multiplication given by:
(x, y) + (x', y') = (y + y', x + x')
c(x, y) = (cx, cy)

V is not a vector space. List one of the properties from the definition of vector space that fails to hold for V. Justify your answer.


Homework Equations


N/A


The Attempt at a Solution



I really do not have any idea on how to get started on this question. I've tried all 8 properties of a vector space and, at least to me, it holds for all 8 properties and should thus be a vector space, but the question explicitly says it is not. I have the answer to the question, but would like to try a different approach to proving it is not a vector space. Any help?
 
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  • #2
not the first one interchanges x & y, try and use that to find a counterexample... does a zero element exist such that v+0=0 for all v?
 
  • #3
lanedance means "v+ 0= v".

What is (x, y)+ (0, 0)?

You should see that (0, 0) is NOT the "0 vector" but then you have to show that no other vector can be:
(x, y)+ (u, v)= (y+ v, x+ u)= (x, y) gives what?
 
  • #4
HallsofIvy said:
lanedance means "v+ 0= v".

What is (x, y)+ (0, 0)?

You should see that (0, 0) is NOT the "0 vector" but then you have to show that no other vector can be:
(x, y)+ (u, v)= (y+ v, x+ u)= (x, y) gives what?

How exactly did you get (x, y) from (y + v, x + u)?

As to your first question: (x, y) + (0, 0) = (y + 0, x + 0) = (y, x)

But, (x, y) - (y, x) = (y - x, x - y) ≠ (0, 0) assuming, of course, that x ≠ y.

Is this sufficient to prove that V is not a vector space?
 
  • #5
No, that only shows that (0, 0) is not the 0 vector. It doesn't mean that some other vector, a, say, does not have the property that v+ a= v for all v.

That was why I wrote (x, y)+ (u, v)= (y+ v, x+ u)= (x, y).
I did NOT get (x,y) from (y+ v, x+ u), I am saying that if (u, v) is the 0 vector then that must be true. Now, show that u and v cannot be independent of x and y.
 
  • #6
HallsofIvy said:
No, that only shows that (0, 0) is not the 0 vector. It doesn't mean that some other vector, a, say, does not have the property that v+ a= v for all v.

That was why I wrote (x, y)+ (u, v)= (y+ v, x+ u)= (x, y).
I did NOT get (x,y) from (y+ v, x+ u), I am saying that if (u, v) is the 0 vector then that must be true. Now, show that u and v cannot be independent of x and y.
Ah, yes. I was thinking in terms of subspaces (where the standard zero vector exists in the vector space it is a subset of).

Let's say (a, b) is part of the set V, then using the associativity property of addition:

(a,b) + ((x, y) + (u, v)) = (y + v, x + u) + (a, b) = (x + u + b, y + v + a)

(x, y) + ((a, b) + (u, v)) = (b + v, a + u) + (x, y) = (a + u + y, b + v + x)

Since (a + u + y, b + v + x) ≠ (x + u + b, y + v + a), the associativity property of vector addition does not hold, and hence, V is not a vector space. Correct?
 
  • #7
HallsofIvy said:
lanedance means "v+ 0= v".
exactly, cheers
 
  • #8
Retribution said:
Ah, yes. I was thinking in terms of subspaces (where the standard zero vector exists in the vector space it is a subset of).

Let's say (a, b) is part of the set V, then using the associativity property of addition:

(a,b) + ((x, y) + (u, v)) = (y + v, x + u) + (a, b) = (x + u + b, y + v + a)

(x, y) + ((a, b) + (u, v)) = (b + v, a + u) + (x, y) = (a + u + y, b + v + x)

Since (a + u + y, b + v + x) ≠ (x + u + b, y + v + a), the associativity property of vector addition does not hold, and hence, V is not a vector space. Correct?

good enough for me
 
  • #9
thw way I was hinting about the zero vector was as follows:

say the additive identity element 0 exists, let's call it 0=(p,q)

now take an arbitrary element (x,y), it must satisfy
(x,y)+(p,q) = (x,y)

but
(x,y)+(p,q) = ((y+q), (x+p))

for the "zero: property to be true we must have
q=x-y
p=y-x

hence no universal 0=(p,q) element exists
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of elements (vectors) that can be added together and multiplied by scalars (numbers) to produce new vectors. It follows a set of axioms that define its properties, such as closure under addition and multiplication, and the existence of an identity and inverse element.

2. How do you prove that a set is a vector space?

To prove that a set is a vector space, you need to show that it satisfies all the axioms of a vector space. This includes showing that the set is closed under vector addition and scalar multiplication, has an identity and inverse element, and follows the properties of commutativity, associativity, and distributivity.

3. What is the difference between a vector space and a subspace?

A subspace is a subset of a vector space that also satisfies all the axioms of a vector space. In other words, it is a smaller vector space contained within a larger one. This means that all the properties of a vector space also hold for a subspace, but a vector space may have additional elements and operations that are not present in the subspace.

4. Can a vector space have infinite dimensions?

Yes, a vector space can have infinite dimensions. In fact, many important vector spaces in mathematics, such as the space of all real numbers or the space of all continuous functions, have infinite dimensions. The number of dimensions of a vector space is determined by the number of independent vectors needed to span the space.

5. Why is proving a set to be a vector space important?

Proving a set to be a vector space is important because it allows us to use the tools and techniques of linear algebra to understand and solve problems in various fields, such as physics, engineering, and economics. It also helps us to identify and study the properties and structures of different types of vector spaces, which can lead to new insights and discoveries in mathematics.

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