The correct way to write the range of a linear transformation

In summary: If we disallow the zero vector, then this fundamental theorem would no longer hold. In summary, The transformation ##T: V_2 \to V_2## is linear, with a range of the line ##y=x##, written symbolically as ##T(V_2) = \{(x,x) | x \in \mathcal{R}\}##. This is because ##V_2## is the Cartesian product of ##V## with itself, where the members of ##T(V_2)## have the property that their first and second components are equal. Additionally, a singleton set can be a linear space if it contains only the zero element, and an empty set cannot be a linear space because it violates the
  • #1
Hall
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Homework Statement
Find the range of T.
Relevant Equations
Range of T is written as ##T(V_2)##.
We have a transformation ##T : V_2 \to V_2## such that:
$$
T (x,y)= (x,x)
$$

Prove that the transformation is linear and find its range.

We can prove that the transformation is Linear quite easily. But the range ##T(V_2)## is the the line ##y=x## in a two dimensional (geometrically) space. Is that the correct way to write the range of T?

For another case, if ##T(x,y) = (x,0)## then the range ##T(V_2)## will be the x-axis. But I think they need to be written more symbolically rather than saying "the line y=x is the range" or "the x-axis is the range".
 
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  • #2
Do you know set notation?$$S = \{X \in U: P(X) \}$$The set ##S## is defined as a subset of some universal set ##U##, where the members of ##S##, denoted by ##X##, have the property ##P(X)##
 
  • #3
PeroK said:
Do you know set notation?$$S = \{X \in U: P(X) \}$$The set ##S## is defined as a subset of some universal set ##U##, where the members of ##S##, denoted by ##X##, have the property ##P(X)##
Okay.
$$
T(V_2 )= \{ (x,x) | x \in \mathcal{R}\}
$$
 
  • #4
Hall said:
Okay.
$$
T(V_2 )= \{ (x,x) | x \in \mathcal{R}\}
$$
Is ##V_2## the Cartesian product of ##V## with itself? In that case, it's ##x \in V##.
 
  • #5
PeroK said:
Is ##V_2## the Cartesian product of ##V## with itself? In that case, it's ##x \in V##.
I had two basic questions -- having a new thread for that doesn't seem the need--
1. Can a singleton set be a Linear space?
2. Is an empty set a Linear space?
 
  • #6
Hall said:
I had two basic questions -- having a new thread for that doesn't seem the need--
1. Can a singleton set be a Linear space?
2. Is an empty set a Linear space?
1) Yes. 2) No.

Look at the definition.

Can you think of an example of a linear space that is often the singleton ##\{0\}##?

Why cannot ##\emptyset## be a linear space? What property does it lack?
 
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  • #7
PeroK said:
Can you think of an example of a linear space that is often the singleton {0}?
Amm... yes. Every set which contains the zero element only, is a singleton set, satisfies all the axioms of a linear space. Examples: ##\{(0,0)\}##, the set containing the zero polynomial, et cetra.

PeroK said:
Why cannot ∅ be a linear space? What property does it lack?
I just re-looked at the definition of linear space and there it was written "A nonempty set V is called a linear space if..."

Can you please tell me why the dimension of a linear space, which contains the zero element only, is 0? I mean that space can be spanned by the zero element itself, can't it be?
 
  • #8
Hall said:
Can you please tell me why the dimension of a linear space, which contains the zero element only, is 0? I mean that space can be spanned by the zero element itself, can't it be?
It's similar to defining a point as zero dimensional. The dimension is zero by definition. Otherwise it would mess up counting dimensions.

You still haven't found an important example of why we must allow the zero vector to be a linear space?

What aspect of linear algebra theory would be messed up by disallowing the zero dimensional space?
 
  • #10
PeroK said:
You still haven't found an important example of why we must allow the zero vector to be a linear space?
I mean, the closure axioms are followed and the set containing the zero element is a subset of a Linear space, hence it is a subspace.
 
  • #11
PeroK said:
What aspect of linear algebra theory would be messed up by disallowing the zero dimensional space?
The most recent I have found is :

Nullity + Rank = dimension of domain

Will be violated.
 
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  • #12
Hall said:
The most recent I have found is :

Nullity + Rank = dimension of domain

Will be violated.
In other words, the kernel of a linear transformation is a subspace which often has dimension zero.
 

FAQ: The correct way to write the range of a linear transformation

What is the correct way to write the range of a linear transformation?

The correct way to write the range of a linear transformation is to use set notation, where the range is written as a set of all possible output values of the transformation. For example, if the transformation is represented by the matrix A and the input vector x, the range would be written as {Ax | x ∈ ℝⁿ}.

How is the range of a linear transformation related to its image?

The range of a linear transformation is a subset of its image. The image of a transformation is the set of all possible output vectors, while the range is the set of all possible output values. Therefore, the range is a one-dimensional representation of the image.

Can the range of a linear transformation be a single point?

Yes, the range of a linear transformation can be a single point if the transformation is a scalar multiplication. In this case, the range would be a one-dimensional subspace of the vector space.

How can I determine the range of a linear transformation?

To determine the range of a linear transformation, you can use the transformation matrix and the input vector space. Apply the transformation to all possible input vectors and collect the resulting output vectors. The range will be the set of all unique output vectors.

Is the range of a linear transformation always a subspace of the output vector space?

Yes, the range of a linear transformation is always a subspace of the output vector space. This is because the range is a subset of the image, which is a subspace of the output vector space. Additionally, the range must also satisfy the properties of a vector space, making it a subspace by definition.

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