Not Satisfied with Linear Algebra Theorem

In summary: T is one to oneIn summary, the theorem states that a linear transformation T: R^n -> R^m is one-to-one if and only if the equation T(x) = 0 has only the trivial solution, meaning that the only vector that maps to the zero vector is the zero vector itself. This is proven by showing that if T is not one-to-one, then there are two different vectors U and V such that T(U) = T(V) = some vector B. By linearity, this means that T(U-V) = T(U) - T(V) = B - B = 0. Therefore, there are nontrivial solutions to T(x) = 0, contradicting the
  • #1
Vorde
788
0
Hello,

I am just not satisfied with the following theorem (I don't know it's name):

Let T:R^n -> R^m be a linear transformation. Then T is one-to-one if and only if the equation T(x) = 0 has only the trivial solution.

The "proof" involves saying that if T is not one-to-one, then there are two different vectors U and V such that T(U)=T(V)= some vector B. And since T is linear it follows that T(U-V) = T(U)-T(V) = B - B = 0. It then concludes by saying "hence there are nontrivial solutions to T(X)= 0. So, either the two conditions in the theorem are both true or they are both false."

I just don't see how that proved the theorem in any way, perhaps because I don't fully understand which two conditions it is talking about.

Could anyone help me here? Thank you.
 
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  • #2
Hey Vorde.

A 1-1 would imply that T(U-V) = T(U) - T(V) != 0 for U != V. If however this were false then it would imply that for some U != V that T(U) = T(V) proving that the mapping is not 1-1.

But then you have to take into account the trivial solution (i.e. the zero vector) as a special case where T(U) = 0 for U = 0.

The formal proof for 1-1-ness is to show that for U != V then T(U) != T(V) for all U and V in the domain of the mapping.
 
  • #3
Hey Chiro,

Right, so I understand that part. What I don't understand is how it is enough to show that there aren't any non-zero vectors that map to the zero-vector to know that the mapping is one-to-one everywhere.

Why couldn't the zero vector be the only vector that maps to the zero vector but still have non 1-1-ness elsewhere?
 
  • #4
We know that the zero vector always maps to the zero vector, but we also know that if everything is 1-1, then it means that only the zero vector maps to the zero vector and everything else maps to some other vector (that isn't the zero vector).
 
  • #5
Vorde said:
Why couldn't the zero vector be the only vector that maps to the zero vector but still have non 1-1-ness elsewhere?

Take two vectors, u and v.
Suppose T(u) = T(v).
Then T(u) - T(v) = 0.
But be linearity, T(u) - T(v) = T(u-v).
Then only vector that maps to 0 is the zero vector.
Hence, u - v = 0, so u = v, proving T was 1-to-1.
 
  • #6
Okay, but that only works if you posit that the transformation is 1-1, and the theorem doesn't start with the assumption that the transformation is 1-1. I understand that the zero vector will always map to itself, just not why that says anything about the rest of the transformation.

Ah, wait, I think I might see it now.
 
  • #7
Let [itex]T[/itex] be injective (sorry I absolutely hate the term 1 - 1 god knows why it is even used). Because T is linear, [itex]T(0) = 0[/itex]. This immediately implies this is the only vector for which this is true because if [itex]\exists v\in V :T(v) = 0[/itex], then the injectivity of [itex]T[/itex] implies that [itex]v = 0[/itex]. Now let [itex]T(v) = 0[/itex] be true only for the zero element then if [itex]T(v) = T(w)[/itex] we have that [itex]T(v - w) = 0\Rightarrow v = w[/itex] thus [itex]T[/itex] is injective. This is essentially what the proof you quoted is saying but the quoted proof is more concise.

EDIT: Seems like people responded while I was typing this up but I guess I'll leave it here anyways =D.
 
  • #8
Okay, thank you to all who have been helping.

What was really bothering me was that I didn't see why the trivial solution had to be the only solution for the zero vector. But I just went back and thought about it and now I can see that this must be the case.

That assumed, I can follow the rest of the theorem.

Once again, thank you all.
 
  • #9
T is one to one if
whenever
T(u)=T(v)
we must have
u=v

now suppose
T(x)=0
only when
x=0

If
T(u)=T(v)
by linearity
T(u-v)=0
then we must have
u-v=0
so
u=v
 

What is Linear Algebra Theorem?

Linear Algebra Theorem is a mathematical concept that deals with the study of linear equations and their properties. It involves the manipulation of matrices and vectors to solve systems of equations and analyze geometric transformations.

Why might someone not be satisfied with Linear Algebra Theorem?

Some individuals may not be satisfied with Linear Algebra Theorem because it can be complex and difficult to understand. It also requires a strong foundation in algebra and geometry, which some people may struggle with.

What are the practical applications of Linear Algebra Theorem?

Linear Algebra Theorem has many practical applications in various fields such as physics, engineering, computer science, and economics. It is used to solve problems involving systems of equations, optimize processes, and analyze data.

What are some common challenges when studying Linear Algebra Theorem?

Some common challenges when studying Linear Algebra Theorem include understanding abstract concepts, memorizing complex formulas and theorems, and mastering techniques for manipulating matrices and vectors.

How can one improve their understanding of Linear Algebra Theorem?

One can improve their understanding of Linear Algebra Theorem by practicing regularly, seeking help from teachers or tutors, and using various resources such as textbooks, online tutorials, and practice problems. It is also helpful to have a strong foundation in algebra and geometry.

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