Additive identity over linear transformation

In summary: T(0) is the additive inverse of T(0)T(0) = 0 because 0 is the additive identity of WIn summary, when given vector spaces V, W over a field, and a linear transformation T:V\rightarrow W, we can prove that T(0_{v})=0_{w} by using the definition of additive identity and the fact that the additive inverse of T(0) must exist. By manipulating the equation T(0) + (-T(0)) = T(0) + T(0) + (-T(0)), we can show that T(0) = 0, which is the additive identity of W.
  • #1
autre
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Given vector spaces V, W over a field, and linear transformation [itex]T:V\rightarrow W[/itex], prove [itex]T(0_{v})=0_{w} [/itex] where 0_v and 0_w are additive identities of V and W.

I'm trying to use the definition of additive identity. So, [itex]\forall\vec{v}\in V,\vec{v}+0=\vec{v+0=0} [/itex]. Where do I go from here?
 
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  • #2
I don't really see why v + 0 = 0... unless v = 0.
However, you may want to look at v + (-v) = 0.
 
  • #3
Woops, I meant [itex]\forall\vec{v}\in V,\vec{v}+0=\vec{0+v=\vec{v}}. [/itex] Not the additive inverse.
 
  • #4
Yep, I guess you can use that as well.
You will still need the additive inverse at some point though (if not in V, then at least in W to show that T(v) - T(v) = 0W).
 
  • #5
Here's a hint: Consider [itex]T(0_v+0_v)[/itex].
 
  • #6
Would this line of reasoning work?

[itex]T(0_{v})=T(0_{v}+0_{v})=T(0_{v}+\vec{v}-\vec{v}+0_{v})=T(0_{v}+\vec{v})-T(0_{v}+\vec{v})=T(\vec{v})-T(\vec{v})=\vec{w}-\vec{w}=0_{w}. [/itex]
 
  • #7
That looks good to me! In fact you can make it even simpler If you want by noting [itex]T(0_v)=T(0_v+0_v)=T(0_v) + T(0_v) [/itex] which is only possible if [itex]T(0_v)=?[/itex]
 
  • #8
[itex]T(0_{v})=0_{w}[/itex], or the additive identity in W?
 
  • #9
Exactly , it must be the zero of W.
 
  • #10
autre said:
Would this line of reasoning work?

[itex]T(0_{v})=T(0_{v}+0_{v})=T(0_{v}+\vec{v}-\vec{v}+0_{v})=T(0_{v}+\vec{v})-T(0_{v}+\vec{v})=T(\vec{v})-T(\vec{v})=\vec{w}-\vec{w}=0_{w}. [/itex]
It's correct, but you're using the following two results without proving them
  • T(-x) is the additive inverse of T(x) for all x.
  • -0=0
The first one is no more obvious than the statement you're trying to prove.

If you're going to use these results, there's no need to involve a new vector v. You could just write [tex]T(0)=T(0+0)=T(0+(-0))=T(0)+T(-0)=T(0)-T(0)=0.[/tex] I prefer the method Theorem suggested.
 
  • #11
An alternative way to write it down is:
T(0) = T(0 + 0) = T(0) + T(0) because of linearity.
Now add the additive inverse of T(0) (whatever it is, but there must be one) to both sides, and you get
T(0) + (-T(0)) = T(0) + T(0) + (-T(0))
0 = T(0)
 

FAQ: Additive identity over linear transformation

What is an additive identity over linear transformation?

An additive identity over linear transformation is a special type of linear transformation that preserves the identity of addition. This means that when this transformation is applied to any vector, the resulting vector will be the same as the original vector. In other words, the transformation does not change the vector in any way.

How is an additive identity over linear transformation represented mathematically?

An additive identity over linear transformation is represented by the matrix I, also known as the identity matrix. This is a square matrix with 1's on the main diagonal and 0's everywhere else. For example, a 3x3 identity matrix looks like this:

I = [1 0 0; 0 1 0; 0 0 1]

What is the importance of additive identity over linear transformation?

Additive identity over linear transformation is important because it allows us to perform operations on vectors without changing their values. This makes it easier to solve systems of linear equations and perform other mathematical operations. It also serves as a building block for other types of linear transformations.

How is additive identity over linear transformation used in real-world applications?

Additive identity over linear transformation is used in a variety of real-world applications, such as computer graphics, data analysis, and physics. For example, in computer graphics, it is used to transform objects on a screen without distorting their shapes. In data analysis, it is used to standardize data and remove any bias. In physics, it is used to describe the behavior of physical systems.

Can an additive identity over linear transformation be combined with other linear transformations?

Yes, an additive identity over linear transformation can be combined with other linear transformations. This is known as the composition of linear transformations. When two linear transformations are composed, the resulting transformation is also a linear transformation. This allows us to perform more complex operations on vectors and solve more complicated problems.

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