A0 = 0 (0 of a vector space)

In summary, to prove that a0 = 0, we can consider the properties of vector spaces and fields. By showing that a0 satisfies the property of the zero vector in V, and that it is unique, we can conclude that a0 = 0, as desired. This can be done by considering that scalar multiplication is distributive in all vector spaces and that for each element a in F and each element x in V, there is a unique element ax in V. Thus, any element x of V can be expressed as a scalar multiplication of a member of the field and another member of V, and this includes the element 0_V, which is the unique vector such that x + 0_V = x. Therefore,
  • #1
1MileCrash
1,342
41

Homework Statement



Prove that a0 = 0

Homework Equations


The Attempt at a Solution



Let V be a vector space on a field F. Let x be a member of V and a be a member of F.

Consider that the 0 vector is the unique vector such that

x + 0 = x

Now, apply a scalar multiplication by a to both sides of the equation. Because scalar multiplication is distributive in all vector spaces,

ax + a0 = ax

Thus, we see that a0 has the same property of the 0 vector in V. Since the 0 vector in V is also unique, it must be the case that

a0 = 0

QEDCan I do that?
 
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  • #2
1MileCrash said:

Homework Statement



Prove that a0 = 0

Homework Equations





The Attempt at a Solution



Let V be a vector space on a field F. Let x be a member of V and a be a member of F.

Consider that the 0 vector is the unique vector such that

x + 0 = x

Now, apply a scalar multiplication by a to both sides of the equation. Because scalar multiplication is distributive in all vector spaces,

ax + a0 = ax

Thus, we see that a0 has the same property of the 0 vector in V. Since the 0 vector in V is also unique, it must be the case that

a0 = 0

QED


Can I do that?

I don't think you quite have it. Have you shown that for ALL y you have y + a0 = y?
 
  • #3
LCKurtz said:
I don't think you quite have it. Have you shown that for ALL y you have y + a0 = y?
But if

x + 0 = x

is true for all x (which it is by definition of the zero vector) then

ax + a0 = ax

is also true for all x, and it is true for all a (because scalar multiplication is distributive in all vector spaces), so then it is always true, so it is true for any ax (or y).

Right?
 
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  • #4
It may be trivial, but you haven't shown that any y can be written in the form ax.
 
  • #5
LCKurtz said:
It may be trivial, but you haven't shown that any y can be written in the form ax.

Oh, ok.

So, I need to justify that ax is also an element of V? Am I understanding that correctly?

If so, then can I just say that in all vector spaces, for each element a in F and each element x in V, there is a unique element ax in V, thus, let ax = y, which is a known element of V (and then the result follows)?
 
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  • #6
1MileCrash said:
Oh, ok.

So, I need to justify that ax is also an element of V? Am I understanding that correctly?

If so, then can I just say that in all vector spaces, for each element a in F and each element x in V, there is a unique element ax in V, thus, let ax = y, which is a known element of V (and then the result follows)?

You have shown that a0 works as an additive identity on all elements of the form ax. If every y in V can be written that way you have it as an additive identity on all of V, which is what you want. Think about ##y = a(\frac 1 a y)##.

As an alternative approach to the problem think about a(0+0) in the first place.
 
  • #7
Ok, instead of saying "the result follows" I'll just write it out.

"for each element a in F and each element x in V, there is a unique element ax in V, thus, let ax = y, which is a known element of V (and then the result follows)?"

ax = y
=>
x = (1/a)y

(1/a) is the multiplicative inverse of a and is therefore a member of F. y is already known as a member of V. Therefore any element x of V can be expressed as a scalar multiplication of a member of the field and another member of V.

That's what I was getting at, would you say that is adequate?

Thanks again.
 
  • #8
Using LC's hint :

a0 = a(0+0) = a0 +a0

So you have :

a0 = a0 + a0

Hmm what property of vector spaces would help you here now? There aren't too many to consider so I'm sure you will see it any moment.
 
  • #9
Zondrina said:
Using LC's hint :

a0 = a(0+0) = a0 +a0

So you have :

a0 = a0 + a0

Hmm what property of vector spaces would help you here now? There aren't too many to consider so I'm sure you will see it any moment.

I'd rather just complete the attempt I've done myself, this is the proof my book gives.
 
  • #10
1MileCrash said:
Ok, instead of saying "the result follows" I'll just write it out.

"for each element a in F and each element x in V, there is a unique element ax in V, thus, let ax = y, which is a known element of V (and then the result follows)?"

ax = y
=>
x = (1/a)y

(1/a) is the multiplicative inverse of a and is therefore a member of F. y is already known as a member of V. Therefore any element x of V can be expressed as a scalar multiplication of a member of the field and another member of V.

That's what I was getting at, would you say that is adequate?

Thanks again.

No, I don't think so. At the very least, it is confusing. Summarizing your argument so far you have shown that for any ##a\in F## and ##{\bf x} \in V## that ##a{\bf x} + a{\bf 0} = a{\bf x}##. What you need to show is that for any ##{\bf y}\in V## you have ##{\bf y} + a{\bf 0} = {\bf y}##. You have to start with ##\bf y##. You can't start with ##a{\bf x}## and call it ##\bf y##. Look at my suggestion in post #6 again.
 
  • #11
Well you know that ##a \in F## and I would recommend writing ##0## as ##0_V## as to be more explicit.

So really you want to show ##a0_V = 0_V##.

##F## is a field of scalars. Since ##V## is a vector space, it is closed under addition and scalar multiplication. You know that ##\forall v \in V## and ##\forall a \in F## that ##av \in V## because ##V## is closed.

Now, we've shown there are basically infinitely many vectors of the form ##av## inside of ##V##. So if you want to proceed your way from before, add ##av## to both sides :

##a0_V + av = 0_V + av##

Now because ##0_V## is the unique vector such that ##0_V + v = v, \forall v \in V## ( Prove this if you havent! ) we can proceed :

##a0_V + av = av##

I'll let you finish that one if you want to. Your argument in your last post wouldn't work though. All you did was set y=ax and say y was in V. LC stated if you can show every ##y \in V## can be written as some ##ax##, then you know that ##a0## will work perfectly as an identity.
 
  • #12
Why can't I call ax, y? It's just an element of V.

Looking at y=a((1/a)y) makes me fall back to the same reasoning. If y is an element of V then so is (1/a)y, so a((1/a)y) is an expression for y that is a scalar multiplication of an element of F and an element of V. But that's exactly what I did before. What is wrong with this reasoning?
 
  • #13
1MileCrash: I think you can't say for each ##a## because you are given ##a##. Given ##a##, you must show that a##0_v = 0_v##. I can see a much quicker proof using components.

-edit- Hmm, I suppose this component idea is limited (without choice) to finite-dimensional vector spaces, better to prove this in general.
 
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  • #14
1MileCrash said:
Why can't I call ax, y? It's just an element of V.

Looking at y=a((1/a)y) makes me fall back to the same reasoning. If y is an element of V then so is (1/a)y, so a((1/a)y) is an expression for y that is a scalar multiplication of an element of F and an element of V. But that's exactly what I did before. What is wrong with this reasoning?

Because you have to start with an arbitrary ##{\bf y}\in V##. You have all the pieces but your argument should be written like this:

Suppose ##{\bf y}\in V## and ##a \in F##.

Let ##{\bf x} =\frac 1 a{\bf y}##

##{\bf x} + {\bf 0} = {\bf x}##

##a{\bf x} + a{\bf 0} = a{\bf x}##

##a\frac 1 a{\bf y} +a{\bf 0} = a\frac 1 a{\bf y}##

##{\bf y} +a{\bf 0} ={\bf y}##

Therefore ##a{\bf 0}## is the unique additive identity.
 
  • #15
Oh, I see, that comes out very nicely. I just thought that since x was an arbitrary vector, then so is ax or y. I don't see a difference between letting ax=y and letting x=(1/a)y.

Thanks again.
 
  • #16
EDIT: nevermind, got it backwards.
 
  • #17
There is still a mistake here. Given a, we aren't told that it isn't 0.

Gotta keep your apples in order. If you start with a given ##a \in F##, you must be faithful to that.
 
  • #18
verty said:
Gotta keep your apples in order. If you start with a given ##a \in F##, you must be faithful to that.

I have no idea what you are saying. Could you explain how I have not done that? Or what that means?

All I did was define a to be an element of F so that I could use it in an expression without the reader not knowing what it is. What do you mean by "starting" with it?
 

1. What does A0 = 0 mean in the context of a vector space?

In a vector space, A0 = 0 means that the zero vector, or the vector with all components equal to zero, is the additive identity. This means that when the zero vector is added to any other vector in the space, the result is the original vector.

2. Why is it important for A0 to equal 0 in a vector space?

A0 = 0 is important because it allows for the existence of a unique additive identity in a vector space. This property is necessary for defining vector addition and other operations in a consistent and meaningful way.

3. Can A0 ever equal a non-zero value in a vector space?

No, in a vector space, A0 will always equal 0. This is because the zero vector is the only vector with all components equal to 0, and it is the unique additive identity in the space.

4. How does A0 = 0 relate to the concept of linear independence in a vector space?

A0 = 0 is a crucial property for determining linear independence in a vector space. If a set of vectors contains the zero vector, then it is automatically linearly dependent because the zero vector can be written as a linear combination of any other vector in the set.

5. Is A0 = 0 a necessary condition for a set of vectors to form a vector space?

Yes, A0 = 0 is one of the axioms, or basic properties, that must be satisfied for a set of vectors to form a vector space. Without this property, the set would not be considered a valid vector space.

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